30k
LearnersWeekend/WeekdayLive
Class
- 2 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
Career Transition
Career Gap
Placement Activities
Placement Drives
Latest Hiring
Whats App Reviews
Course Offered By
Become a certified machine learning engineer under expert guidance at Croma Campus
4.2/5
4.8/5
4.6/5
4.3/5
4.5/5Course Duration
Hrs.Live Project
0 ProjectCertification Pass
GuranteedTraining Format
Live Online /Self-Paced/ClassroomWatch Live Classes
Speciality
200 +
Professionals Trained
3 +
Batches every month
20+
Countries & Counting
100+
Corporate Served- The Azure Machine Learning Certification equips individuals with skills for machine learning on Microsoft Azure. It covers various topics, offering hands-on experience and theoretical knowledge.
- Key Features:
- Who Can Enroll:
- The Azure Machine Learning Certification is suitable for:
- Prerequisites
- To enroll in the Azure Machine Learning Certification, participants should have:
Hands-on Labs: The certification offers practical labs for a real-world understanding of Azure machine learning tools and techniques.
Industry-Relevant Curriculum: Aligned with industry requirements, the course ensures participants are prepared for challenges in the field.
Expert Instructors: Learn from experienced instructors with in-depth knowledge of Azure machine learning and practical applications.
Certification Exam: Completing the course qualifies participants to take the official Azure Machine Learning Certification exam.
Data Scientists
Machine Learning Engineers
IT Professionals
Software Developers
Business Intelligence Professionals
Basic programming knowledge (preferably in Python or R)
Understanding of fundamental machine learning concepts
Familiarity with cloud computing concepts (Azure platform knowledge is a plus)
Azure Machine Learning Certification
- The primary objectives of the Azure Machine Learning Certification include:
Mastering Azure Machine Learning Tools: Gain proficiency in using Azure's machine learning tools and services.
Implementing Machine Learning Models: Learn to build, train, and deploy machine learning models on the Azure platform.
Real-world Applications: Apply machine learning concepts to real-world scenarios and business problems.
Azure Services Integration: Understand how Azure machine learning integrates with other Azure services for comprehensive solutions.
- Upon completing the Azure Machine Learning Certification, participants can expect competitive salaries in the machine learning and data science domain. Salary potential is influenced by factors such as experience, geographical location, and industry demand.
- Geographical Location:
- Industry Verticals:
- Experience Level:
- Job Roles and Responsibilities:
- Certification Impact:
- Continued Learning and Specialization:
Salaries may vary based on the region or country. For instance, technology hubs often offer higher compensation.
Different industries value machine learning skills differently. Sectors like finance, healthcare, and technology tend to offer lucrative packages.
Entry-level professionals may start with a competitive base salary, while those with advanced experience and expertise can command higher pay.
The complexity and responsibility of the roles undertaken influence salary levels. Senior or specialized roles generally come with higher compensation.
Holding an Azure Machine Learning Certification validates skills and can positively impact salary negotiations.
Professionals who pursue continuous learning, specialize in niche areas, or acquire additional certifications may command higher salaries.
- The certification opens doors to various career paths, including:
- Machine Learning Engineer:
- Data Scientist:
- AI Developer:
- Cloud Solutions Architect:
- Business Intelligence Analyst:
- Specialized Roles:
- Management Positions:
- Entrepreneurship:
Transition into roles focused on designing and implementing machine learning models, algorithms, and solutions.
Apply machine learning techniques to analyze and interpret complex datasets, deriving valuable insights for decision-making.
Dive into artificial intelligence development, creating solutions that emulate human-like intelligence and enhance automation.
Advance to roles involving the design and implementation of scalable, secure, and efficient cloud-based machine learning solutions.
Specialize in leveraging machine learning for business intelligence, providing actionable insights to enhance organizational strategies.
Explore specialized roles in areas such as natural language processing, computer vision, or reinforcement learning for further expertise.
Progress into leadership or management roles, overseeing machine learning teams and strategies.
Pursue entrepreneurial endeavors by applying machine learning skills to develop innovative products or services.
- Some factors to Azure Machine Learning Certification popularity:
Industry Demand: With the increasing adoption of Azure in various industries, the demand for certified professionals is on the rise.
Comprehensive Curriculum: The certification covers a broad spectrum of machine learning topics, making participants well-rounded professionals.
Practical Applications: Emphasis on hands-on labs and real-world scenarios ensures participants can apply their knowledge effectively.
- Designing Machine Learning Models:
- Implementation and Optimization:
- Data Analysis and Interpretation:
- Continuous Model Monitoring and Improvement:
- Collaboration with Data Engineers and Scientists:
- Integration of Predictive Analytics:
- Ensuring Data Security and Compliance:
- Communication of Results:
- Troubleshooting and Issue Resolution:
- Staying Updated with Azure ML Advancements:
- Collaborating in Cross-Functional Teams:
Develop and design machine learning models tailored to meet specific business requirements.
Utilize Azure Machine Learning services to create effective and efficient models.
Implement machine learning algorithms and optimize them for improved performance.
Ensure the seamless integration of machine learning solutions within Azure environments.
Analyze large datasets using Azure tools to extract meaningful insights.
Interpret data trends and patterns to facilitate informed decision-making.
Monitor machine learning models in real-time to assess their performance.
Implement improvements and optimizations to enhance model accuracy over time.
Collaborate with data engineers and scientists to streamline data pipelines.
Work in tandem to ensure the smooth flow of data for effective machine learning processes.
Implement predictive analytics using Azure Machine Learning capabilities.
Integrate predictive models into existing business processes for actionable insights.
Implement security measures to protect machine learning models and data.
Ensure compliance with data privacy regulations and industry standards.
Effectively communicate complex results and insights to non-technical stakeholders.
Use data visualization tools within the Azure environment for clear communication.
Identify and address issues related to machine learning models promptly.
Troubleshoot challenges that may arise during the deployment and execution of models.
Stay abreast of the latest advancements in Azure Machine Learning.
Continuously update skills and knowledge to leverage new features and functionalities.
Collaborate with cross-functional teams to align machine learning initiatives with overall business goals.
Participate in discussions and contribute insights to enhance data-driven decision-making.
- Top Hiring Industries Like:
Technology and IT: Demand for Azure machine learning professionals in tech companies for innovative solutions.
Healthcare: Utilization of Azure machine learning for improved patient outcomes and operational efficiency.
Finance: Application of Azure machine learning in financial institutions for risk management and fraud detection.
E-commerce: Leveraging Azure machine learning to enhance customer experience and optimize business operations.
Manufacturing: Implementation of Azure machine learning for efficiency and quality improvement in manufacturing.
- Upon successful completion of the Azure Machine Learning Certification, participants receive a prestigious training certificate. This certificate serves as tangible evidence of their acquired skills and knowledge in the field of Azure machine learning. Recognized by industry professionals, the certificate enhances the graduates' credibility and employability.
- You May Also Read:
Why Should You Learn Azure Machine Learning Certification Course?
Not just learning –
we train you to get hired.
Not just learning –
we train you to get hired.
By registering here, I agree to Croma Campus Terms & Conditions and Privacy Policy
Azure Machine Learning Certification Programs
Azure Machine Learning Certification
Programming with Python Training
- Python is a very powerful high-level, object-oriented programming language. Python is an interpreted language. Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems.
- Python has been a favourite option for Data Scientists who use it for building and using Machine Learning Applications and other Scientific Computations.
- Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built in debugger.
- In this program you will learn:
Python Training Curriculum
Data Analysis and Visualization using NumPy, Pandas, and MatPlotLib,Seaborn
Get full course syllabus in your inbox
- In this program you will learn:
- Installation and Working with Python
- Understanding Python variables
- Python basic Operators
- Understanding the Python blocks.
Introduction To Python
- In this program you will learn:
- Python Keyword and Identifiers
- Python Comments, Multiline Comments.
- Python Indentation
- Understating the concepts of Operators
- Arithmetic
- Relational
- Logical
- Assignment
- Membership
- Identity
Python Keyword and Identifiers
- In this program you will learn:
- Variables, expression condition and function
- Global and Local Variables in Python
- Packing and Unpacking Arguments
- Type Casting in Python
- Byte objects vs. string in Python
- Variable Scope
Introduction To Variables:
- In this program you will learn:
- Declaring and using Numeric data types
- Using string data type and string operations
- Understanding Non-numeric data types
- Understanding the concept of Casting and Boolean.
- Strings
- List
- Tuples
- Dictionary
- Sets
Python Data Type:
- In this program you will learn:
- Statements – if, else, elif
- How to use nested IF and Else in Python
- Loops
- Loops and Control Statements.
- Jumping Statements – Break, Continue, pass
- Looping techniques in Python
- How to use Range function in Loop
- Programs for printing Patterns in Python
- How to use if and else with Loop
- Use of Switch Function in Loop
- Elegant way of Python Iteration
- Generator in Python
- How to use nested Loop in Python
- Use If and Else in for and While Loop
- Examples of Looping with Break and Continue Statement
- How to use IN or NOT IN keyword in Python Loop.
Control Structure & Flow
- In this program you will learn:
- Python Syntax
- Function Call
- Return Statement
- Arguments in a function – Required, Default, Positional, Variable-length
- Write an Empty Function in Python –pass statement.
- Lamda/ Anonymous Function
- *args and **kwargs
- Help function in Python
- Scope and Life Time of Variable in Python Function
- Nested Loop in Python Function
- Recursive Function and Its Advantage and Disadvantage
- Organizing python codes using functions
- Organizing python projects into modules
- Importing own module as well as external modules
- Understanding Packages
- Random functions in python
- Programming using functions, modules & external packages
- Map, Filter and Reduce function with Lambda Function
- More example of Python Function
Python Function, Modules and Packages
- In this program you will learn:
- Day, Month, Year, Today, Weekday
- IsoWeek day
- Date Time
- Time, Hour, Minute, Sec, Microsec
- Time Delta and UTC
- StrfTime, Now
- Time stamp and Date Format
- Month Calendar
- Itermonthdates
- Lots of Example on Python Calendar
- Lots of Example on Python Calendar
- Create 12-month Calendar
- Strftime
- Strptime
- Format Code list of Data, Time and Cal
- Locale’s appropriate date and time
Python Date Time and Calendar:
- In this program you will learn:
- What is List.
- List Creation
- List Length
- List Append
- List Insert
- List Remove
- List Append & Extend using “+” and Keyword
- List Delete
- List related Keyword in Python
- List Revers
- List Sorting
- List having Multiple Reference
- String Split to create a List
- List Indexing
- List Slicing
- List count and Looping
- List Comprehension and Nested Comprehension
List
- In this program you will learn:
- What is Tuple
- Tuple Creation
- Accessing Elements in Tuple
- Changing a Tuple
- Tuple Deletion
- Tuple Count
- Tuple Index
- Tuple Membership
- TupleBuilt in Function (Length, Sort)
Tuple
- In this program you will learn:
- Dict Creation
- Dict Access (Accessing Dict Values)
- Dict Get Method
- Dict Add or Modify Elements
- Dict Copy
- Dict From Keys.
- Dict Items
- Dict Keys (Updating, Removing and Iterating)
- Dict Values
- Dict Comprehension
- Default Dictionaries
- Ordered Dictionaries
- Looping Dictionaries
- Dict useful methods (Pop, Pop Item, Str , Update etc.)
Dictionary
- In this program you will learn:
- What is Set
- Set Creation
- Add element to a Set
- Remove elements from a Set
- PythonSet Operations
- Frozen Sets
Sets
- In this program you will learn:
- What is Set
- Set Creation
- Add element to a Set
- Remove elements from a Set
- PythonSet Operations
Strings
- In this program you will learn:
- Python Errors and Built-in-Exceptions
- Exception handing Try, Except and Finally
- Catching Exceptions in Python
- Catching Specific Exception in Python
- Raising Exception
- Try and Finally
Python Exception Handling
- In this program you will learn:
- Opening a File
- Python File Modes
- Closing File
- Writing to a File
- Reading from a File
- Renaming and Deleting Files in Python
- Python Directory and File Management
- List Directories and Files
- Making New Directory
- Changing Directory
Python File Handling
- In this program you will learn:
- SQL Database connection using
- Creating and searching tables
- Reading and Storing config information on database
- Programming using database connections
Python Database Interaction
- In this program you will learn:
- Installing SMTP Python Module
- Sending Email
- Reading from file and sending emails to all users
Contacting user Through Emails Using Python
- In this program you will learn:
- Working With Excel
- Reading an excel file using Python
- Writing to an excel sheet using Python
- Python| Reading an excel file
- Python | Writing an excel file
- Adjusting Rows and Column using Python
- ArithmeticOperation in Excel file.
- Play with Workbook, Sheets and Cells in Excel using Python
- Creating and Removing Sheets
- Formatting the Excel File Data
- More example of Python Function
Reading an excel
- In this program you will learn:
- Check Dirs. (exist or not)
- How to split path and extension
- How to get user profile detail
- Get the path of Desktop, Documents, Downloads etc.
- Handle the File System Organization using OS
- How to get any files and folder’s details using OS
Complete Understanding of OS Module of Python
Get full course syllabus in your inbox
- In this program you will learn:
- Introduction to NumPy: Numerical Python
- Importing NumPy and Its Properties
- NumPy Arrays
- Creating an Array from a CSV
- Operations an Array from aCSV
- Operations with NumPy Arrays
- Two-Dimensional Array
- Selecting Elements from 1-D Array
- Selecting Elements from 2-D Array
- Logical Operation with Array
NumPy
- In this program you will learn:
- Working With Excel using Pandas
- Reading an excel & CSV file using Pandas
- Writing to an excel sheet using Pandas
- Adjusting Rows and Column using Pandas
- Arithmetic Operation in Excel file using Pandas.
- Play with Workbook, Sheets and Cells in Excel using Pandas
- Creating and Removing Sheets using Pandas
- Formatting the Excel File Data using Pandas
Pandas
- In this program you will learn:
- Bar Chart using Python MatPlotLib
- Column Chart using Python MatPlotLib
- Pie Chart using Python MatPlotLib
- Area Chart using Python MatPlotLib
- Scatter Plot Chart using Python MatPlotLib
- Export the Chart as Image
- Create Charts as Image
- Other Useful Properties of Charts.
- Plotting Different Charts, Labels, and Labels Alignment etc.
MatPlotLib
- In this program you will learn:
- Introduction to Seaborn
- Making a scatter plot with lists
- Making a count plot with a list
- Using Pandas with seaborn
Introduction to Seaborn
- In this program you will learn:
- Concept of Class, Object and Instances
- Constructor, Class attributes and Destructors
- Real time use of class in live projects
- Inheritance, Overlapping and Overloading operators
- Adding and retrieving dynamic attributes of classes
- Programming using Oops support
Python Object Oriented Programming—Oops Concepts
Get full course syllabus in your inbox
Python Django Full Stack Development Training Program
30k
LearnersWeekend/WeekdayLive
Class
- 2 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
- Python is a very powerful high-level, object-oriented programming language. Python is an interpreted language. Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems.
- Using third-party tools, such as Py2exe or Pyinstaller Python code can be packaged into stand-alone executable programs. Django is an extremely widely used framework, and because it’s open source. Django is a web framework which written in python & follows the MVC architectural pattern.
- It is maintained by the Django software foundation, an independent organization. There are many other frameworks like Pyramid, web2py, Flask etc. which support developers in the design & maintenance of complex applications. Pyjamas & Iron Python can be used to develop the client-side of ajax-based applications.
- In this program you will learn:
HTML
HTML 5
CSS 2.0
CSS 3.0
JavaScript
JQuery
Bootstrap Framework Latest Version (HTML, CSS, and JS Library)
Web Hosting & SEO Basics
Python Training Curriculum
Data Analysis and Visualization using NumPy, Pandas, and MatPlotLib, Seaborn
Placement Guide
Get full course syllabus in your inbox
- HTML
What is HTML
What is a Web Browser
What are Versions of HTML
What can you Do with HTML
HTML Development Environments
Writing Code with a Text Editor
- Review of HTML Elements
Rules of Syntax
Making your Code Readable
Building a Document
Using Colors
Adding Color to your Page
Using Headings
Using Paragraphs
Aligning Block-Level Elements
- Inserting Spaces and Line Breaks
Displaying Preformatted Text
Formatting with Inline Elements
Controlling Fonts
Introducing List Elements
Creating Unordered Lists
Creating Ordered Lists
Nesting Lists
- What is an HTML Table
Building a Table
Cell Padding and Cell Spacing
Controlling Table and Cell Width
Aligning a Table on the Page
Aligning Tables and Text
Aligning Table Data
Spanning Columns and Rows
- Creating a Hyperlink
Understanding and Using URLs
Linking to a Web Document
Linking to a Local Document
Linking to Anchors
Opening a New Browser Window
- Image Formats
Inserting Inline Images
Aligning Images
Using Images to Anchor Links
Sizing Images
Using Transparent Images
Using GIF Animation
- Forms and Controls
Forms and Form Elements
Form Actions, Form Methods, Form Design
Get full course syllabus in your inbox
- Introduction
Laying out a page with HTML5
Page Structure
New HTML5 Strutural Tags
Page Simplification
- HTML 5 - How we got here
New Features of HTML5
The HTML5 Semantic Element
Current State of Browser Support
- SECTIONS AND ARTICLES
The section Tag
The article Tag
The header Tag
The Footer Tag
- HTML5 AUDIO AND VIDEO
Supported Media Types
The audio Element
The video Element
- HTML5 FORMS
New Input Types
- HTML5 NEW FORM ATTRIBUTES
autocomplete
novalidate
- HTML5 NEW FORM FIELD ATTRIBUTES
required
placeholder
autofocus
autocomplete
form
pattern
Get full course syllabus in your inbox
- Introduction of CSS
- CSS Syntax
- CSS Comments
- CSS Type
Inline
Internal
External
- CSS Selector
ID
Class
Attribute
Grouping
Universal
- CSS Color
RGB Value
Hex Value
Color Name
- Background
background-color
background-repeat
background-attachement
background position
background-size
background-image
- CSS Margin
Margin-top
Margin-bottom
Margin-left
Margin-Right
- CSS Padding
Padding -top
Padding -bottom
Padding -left
Padding –Right
- Outline
Outline-Style
Outline-color
Outline Width
Outline-Offset
Outline Shorthand Property
- CSS Height and Width
- CSS Display properties
- CSS Position Properties
- CSS Overflow
- CSS Float and Clear
- Pseudo Class and Element
Get full course syllabus in your inbox
- Introduction to CSS 3
Border
border-radius
- CSS Shadows
Text-shadow
Box-shadow
- Transitions
transition
transition - delay
transition - duration
transition - property
- 2D Transforms
transform
matrix ()
translate (x,y)
scale(x,y)
rotate(angle)
Skew (x - angle, y-angle)
- Animations
@keyframes
animation
animation-direction
animation-duration
animation-name
- Selectors
CSS combinations
Pseudo Elements
- Gradients
Linear Gradients
Radial Gradients
- User Interface
resize
box-sizing
outline-offset
- CSS Filters
Blur
Opacity
- Media Query
What is Responsive Web Design
Intro to the Viewport
The Viewport Tag
Media Queries
Tablet Styles
Mobile Styles
Making a Mobile Drop-down Menu
- Web Fonts
@font-face
font- family
src
font-stretch
font-Style
font-weight
- Flexbox
flex - grow
flex - shrink
flex - basis
flex
flex - wrap
flex - direction
flex - flow
justify - content
align-items
order
Get full course syllabus in your inbox
Django Framework Training Program
30k
LearnersWeekend/WeekdayLive
Class
- 1 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
- Croma Campus's Django course helps you gain expertise in Django REST framework, Django Models, Django AJAX, Django jQuery etc. You'll master Django web framework while working on real-time use cases and receive Django certification at the end of the course.
- In this program you will learn:
Django Web Framework
Getting Started with Django
Create an Application
Django - URL Mapping
Django Template Language (DTL)
Django – Models
Django – Sending E-mails
Django – Form Processing/le handling/cooking handling
Django Admin
Django API (Application Program Interface)
Static les
Placement Guide
Get full course syllabus in your inbox
- Django Web Framework
What is a Framework
Introduction to Django
Django – Design Philosophies
History of Django
Why Django and Features
Environment setup
Web Server
MVC Pattern
MVC Architecture vs MVT Architecture
Django MVC – MVT Pattern
Get full course syllabus in your inbox
- Getting Started with Django
Creating the rst Project
Integrating the Project to sublime text
The Project Structure
Running the server
Solving the issues and Migrations
Database Setup
Setting Up Your Project.
Get full course syllabus in your inbox
- Create an Application
What Django Follows
Structure of Django framework
Model Layer
What are models
Model elds
Query sets
Django – Admin Interface
Starting the Admin Interface
Migrations
Views Layer
Simple View
Basic view (displaying hello world)
Functional views, class based views
Get full course syllabus in your inbox
- Django - URL Mapping
Organizing Your URLs
Role of URLs in Django
Working URLs
Forms
Sending Parameters to Views
Templates layer
The Render Function
Get full course syllabus in your inbox
Python for Data Science Training Program
30k
LearnersWeekend/WeekdayLive
Class
- 2 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
- Python has been a favourite option for Data Scientists who use it for building and using Machine Learning Applications and other Scientific Computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built in debugger.
- In this program you will learn:
Python Training
Data Analysis and Visualization using Pandas.
Data Analysis and Visualization using NumPy and MatPlotLib
Introduction to Data Visualization with Seaborn
Get full course syllabus in your inbox
- Introduction To Python
Installation and Working with Python
Understanding Python variables
Python basic Operators
Understanding the Python blocks.
- Python Keyword and Identiers
- Arithmetic
- Relational
- Logical
- Assignment
- Membership
- Identity
Python Keyword and Identiers
Python Comments, Multiline Comments.
Python Indentation
Understating the concepts of Operators
- Introduction To Variables
Variables, expression condition and function
Global and Local Variables in Python
Packing and Unpacking Arguments
Type Casting in Python
Byte objects vs. string in Python
Variable Scope
- Python Data Type
Declaring and using Numeric data types
Using string data type and string operations
Understanding Non-numeric data types
Understanding the concept of Casting and Boolean.
Strings
List
Tuples
Dictionary
Sets
- Control Structure & Flow
Statements – if, else, elif
How to use nested IF and Else in Python
Loops
Loops and Control Statements.
Jumping Statements – Break, Continue, pass
Looping techniques in Python
How to use Range function in Loop
Programs for printing Patterns in Python
How to use if and else with Loop
Use of Switch Function in Loop
Elegant way of Python Iteration
Generator in Python
How to use nested Loop in Python
Use If and Else in for and While Loop
Examples of Looping with Break and Continue Statement
How to use IN or NOT IN keyword in Python Loop.
- Python Function, Modules and Packages
Python Syntax
Function Call
Return Statement
Arguments in a function – Required, Default, Positional, Variable-length
Write an Empty Function in Python –pass statement.
Lamda/ Anonymous Function
*args and **kwargs
Help function in Python
Scope and Life Time of Variable in Python Function
Nested Loop in Python Function
Recursive Function and Its Advantage and Disadvantage
Organizing python codes using functions
Organizing python projects into modules
Importing own module as well as external modules
Understanding Packages
Random functions in python
Programming using functions, modules & external packages
Map, Filter and Reduce function with Lambda Function
More example of Python Function
- Python Date Time and Calendar
Day, Month, Year, Today, Weekday
IsoWeek day
Date Time
Time, Hour, Minute, Sec, Microsec
Time Delta and UTC
StrfTime, Now
Time stamp and Date Format
Month Calendar
Itermonthdates
Lots of Example on Python Calendar
Create 12-month Calendar
Strftime
Strptime
Format Code list of Data, Time and Cal
Locale’s appropriate date and time
- List
What is List.
List Creation
List Length
List Append
List Insert
List Remove
List Append & Extend using “+” and Keyword
List Delete
List related Keyword in Python
List Revers
List Sorting
List having Multiple Reference
String Split to create a List
List Indexing
List Slicing
List count and Looping
List Comprehension and Nested Comprehension
- Tuple
What is Tuple
Tuple Creation
Accessing Elements in Tuple
Changing a Tuple
Tuple Deletion
Tuple Count
Tuple Index
Tuple Membership
TupleBuilt in Function (Length, Sort)
- Dictionary
Dict Creation
Dict Access (Accessing Dict Values)
Dict Get Method
Dict Add or Modify Elements
Dict Copy
Dict From Keys.
Dict Items
Dict Keys (Updating, Removing and Iterating)
Dict Values
Dict Comprehension
Default Dictionaries
Ordered Dictionaries
Looping Dictionaries
Dict useful methods (Pop, Pop Item, Str , Update etc.)
- Sets
What is Set
Set Creation
Add element to a Set
Remove elements from a Set
PythonSet Operations
Frozen Sets
- Strings
What is Set
Set Creation
Add element to a Set
Remove elements from a Set
PythonSet Operations
- Python Exception Handling
Python Errors and Built-in-Exceptions
Exception handing Try, Except and Finally
Catching Exceptions in Python
Catching Specic Exception in Python
Raising Exception
Try and Finally
- Python File Handling
Opening a File
Python File Modes
Closing File
Writing to a File
Reading from a File
Renaming and Deleting Files in Python
Python Directory and File Management
List Directories and Files
Making New Directory
Changing Directory
- Python Database Interaction
SQL Database connection using
Creating and searching tables
Reading and Storing cong information on database
Programming using database connections
- Contacting user Through Emails Using Python
Installing SMTP Python Module
Sending Email
Reading from le and sending emails to all users
- Reading an excel
Working With Excel
Reading an excel le using Python
Writing to an excel sheet using Python
Python| Reading an excel le
Python | Writing an excel le
Adjusting Rows and Column using Python
ArithmeticOperation in Excel le.
Play with Workbook, Sheets and Cells in Excel using Python
Creating and Removing Sheets
Formatting the Excel File Data
More example of Python Function
- Complete Understanding of OS Module of Python
Check Dirs. (exist or not)
How to split path and extension
How to get user prole detail
Get the path of Desktop, Documents, Downloads etc.
Handle the File System Organization using OS
How to get any les and folder’s details using OS
Get full course syllabus in your inbox
- Statistics
Categorical Data
Numerical Data
Mean
Median
Mode
Outliers
Range
Interquartile range
Correlation
Standard Deviation
Variance
Box plot
- Pandas
Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les
How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function
Using the Excel File class to read multiple sheets More Mapping, Filling
Nonvalue’s
Exploring the Data Plotting, Correlations, and Histograms
Getting statistical information about the data Analysis Concepts, Handle the None Values
Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc
Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows
Applying formulas on the columns Basic Grouping, Concepts of Aggre
gate Function
Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)
Under sting the Properties of Pivot Table in Pandas Advanced Reading
CSVs/HTML, Binning, Categorical Data
Exporting the results to Excel Joins:
Python | Pandas Data Frame Inner Join
Under sting the properties of Data Frame Left Join (Left Outer Join)
Indexing and Selecting Data with Pandas Right Join (Right Outer Join)
Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)
Pandas | Find Missing Data and Fill and Drop NA Appending DataFrame and Data
Pandas | How to Group Data How to apply Lambda / Function on Data
Frame
Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)
Get full course syllabus in your inbox
- NumPy
Introduction to NumPy: Numerical Python
Importing NumPy and Its Properties
NumPy Arrays
Creating an Array from a CSV
Operations an Array from a CSV
Operations with NumPy Arrays
Two-Dimensional Array
Selecting Elements from 1-D Array
Selecting Elements from 2-D Array
Logical Operation with Arrays
Indexing NumPy elements using conditionals
NumPy’s Mean and Axis
NumPy’s Mode, Median and Sum Function
NumPy’s Sort Function and More
- MatPlotLib
Bar Chart using Python MatPlotLib
Column Chart using Python MatPlotLib
Pie Chart using Python MatPlotLib
Area Chart using Python MatPlotLib
Scatter Plot Chart using Python MatPlotLib
Play with Charts Properties Using MatPlotLib
Export the Chart as Image
Understanding plt. subplots () notation
Legend Alignment of Chart using MatPlotLib
Create Charts as Image
Other Useful Properties of Charts.
Complete Understanding of Histograms
Plotting Different Charts, Labels, and Labels Alignment etc.
Get full course syllabus in your inbox
- Introduction to Seaborn
Introduction to Seaborn
Making a scatter plot with lists
Making a count plot with a list
Using Pandas with seaborn
Tidy vs Untidy data
Making a count plot with a Dataframe
Adding a third variable with hue
Hue and scattera plots
Hue and count plots
- Visualizing Two Quantitative Variables
Introduction to relational plots and subplots
Creating subplots with col and row
Customizing scatters plots
Changing the size of scatter plot points
Changing the style of scatter plot points
Introduction to line plots
Interpreting line plots
Visualizing standard deviation with line plots
Plotting subgroups in line plots
- Visualizing a Categorical and a Quantitative Variable
Current plots and bar plots
Count plots
Bar plot with percentages
Customizing bar plots
Box plots
Create and interpret a box plot
Omitting outliers
Adjusting the whisk
Point plots
Customizing points plots
Point plot with subgroups
- Customizing Seaborn Plots
Changing plot style and colour
Changing style and palette
Changing the scale
Using a custom palette
Adding titles and labels: Part 1
Face Grids vs. Axes Subplots
Adding a title to a face Grid object
Adding title and labels: Part 2
Adding a title and axis labels
Rotating x-tics labels
Putting it all together
Box plot with subgroups
Bar plot with subgroups and subplots
Well done! What’s next
Get full course syllabus in your inbox
Machine Learning with Python Training Program
30k
LearnersWeekend/WeekdayLive
Class
- 3 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
- Machine learning is important because it gives enterprises a view of trends in ustomer behavior and business operational patterns, as well as supports the development of new products. Many of today's leading companies, such as Facebook, Google and Uber, make machine learning a central part of their operations
- In this program you will learn:
Python Training Curriculum
Data Analysis and Visualization using Pandas.
Data Analysis and Visualization using NumPy and MatPlotLib
Introduction to Data Visualization with Seaborn
Machine Learning
Get full course syllabus in your inbox
- Introduction To Python
Installation and Working with Python
Understanding Python variables
Python basic Operators
Understanding the Python blocks.
- Python Keyword and Identiers
- Arithmetic
- Relational
- Logical
- Assignment
- Membership
- Identity
Python Keyword and Identiers
Python Comments, Multiline Comments.
Python Indentation
Understating the concepts of Operators
- Introduction To Variables
Variables, expression condition and function
Global and Local Variables in Python
Packing and Unpacking Arguments
Type Casting in Python
Byte objects vs. string in Python
Variable Scope
- Python Data Type
- Strings
- List
- Tuples
- Dictionary
- Sets
Declaring and using Numeric data types
Using string data type and string operations
Understanding Non-numeric data types
Understanding the concept of Casting and Boolean.
- Control Structure & Flow
Statements – if, else, elif
How to use nested IF and Else in Python
Loops
Loops and Control Statements.
Jumping Statements – Break, Continue, pass
Looping techniques in Python
How to use Range function in Loop
Programs for printing Patterns in Python
How to use if and else with Loop
Use of Switch Function in Loop
Elegant way of Python Iteration
Generator in Python
How to use nested Loop in Python
Use If and Else in for and While Loop
Examples of Looping with Break and Continue Statement
How to use IN or NOT IN keyword in Python Loop.
- Python Function, Modules and Packages
Python Syntax
Function Call
Return Statement
Arguments in a function – Required, Default, Positional, Variable-length
Write an Empty Function in Python –pass statement.
Lamda/ Anonymous Function
*args and **kwargs
Help function in Python
Scope and Life Time of Variable in Python Function
Nested Loop in Python Function
Recursive Function and Its Advantage and Disadvantage
Organizing python codes using functions
Organizing python projects into modules
Importing own module as well as external modules
Understanding Packages
Random functions in python
Programming using functions, modules & external packages
Map, Filter and Reduce function with Lambda Function
More example of Python Function
- Python Date Time and Calendar
Day, Month, Year, Today, Weekday
IsoWeek day
Date Time
Time, Hour, Minute, Sec, Microsec
Time Delta and UTC
StrfTime, Now
Time stamp and Date Format
Month Calendar
Itermonthdates
Lots of Example on Python Calendar
Create 12-month Calendar
Strftime
Strptime
Format Code list of Data, Time and Cal
Locale’s appropriate date and time
- List
What is List.
List Creation
List Length
List Append
List Insert
List Remove
List Append & Extend using “+” and Keyword
List Delete
List related Keyword in Python
List Revers
List Sorting
List having Multiple Reference
String Split to create a List
List Indexing
List Slicing
List count and Looping
List Comprehension and Nested Comprehension
- Tuple
What is Tuple
Tuple Creation
Accessing Elements in Tuple
Changing a Tuple
Tuple Deletion
Tuple Count
Tuple Index
Tuple Membership
TupleBuilt in Function (Length, Sort)
- Dictionary
Dict Creation
Dict Access (Accessing Dict Values)
Dict Get Method
Dict Add or Modify Elements
Dict Copy
Dict From Keys.
Dict Items
Dict Keys (Updating, Removing and Iterating)
Dict Values
Dict Comprehension
Default Dictionaries
Ordered Dictionaries
Looping Dictionaries
Dict useful methods (Pop, Pop Item, Str , Update etc.)
- Sets
What is Set
Set Creation
Add element to a Set
Remove elements from a Set
PythonSet Operations
Frozen Sets
- Strings
What is Set
Set Creation
Add element to a Set
Remove elements from a Set
PythonSet Operations
- Python Exception Handling
Python Errors and Built-in-Exceptions
Exception handing Try, Except and Finally
Catching Exceptions in Python
Catching Specic Exception in Python
Raising Exception
Try and Finally
- Python File Handling
Opening a File
Python File Modes
Closing File
Writing to a File
Reading from a File
Renaming and Deleting Files in Python
Python Directory and File Management
List Directories and Files
Making New Directory
Changing Directory
- Python Database Interaction
SQL Database connection using
Creating and searching tables
Reading and Storing cong information on database
Programming using database connections
- Contacting user Through Emails Using Python
Installing SMTP Python Module
Sending Email
Reading from le and sending emails to all users
- Reading an excel
Working With Excel
Reading an excel le using Python
Writing to an excel sheet using Python
Python| Reading an excel le
Python | Writing an excel le
Adjusting Rows and Column using Python
ArithmeticOperation in Excel le.
Play with Workbook, Sheets and Cells in Excel using Python
Creating and Removing Sheets
Formatting the Excel File Data
More example of Python Function
- Complete Understanding of OS Module of Python
Check Dirs. (exist or not)
How to split path and extension
How to get user prole detail
Get the path of Desktop, Documents, Downloads etc.
Handle the File System Organization using OS
How to get any les and folder’s details using OS
Get full course syllabus in your inbox
- Statistics
Categorical Data
Numerical Data
Mean
Median
Mode
Outliers
Range
Interquartile range
Correlation
Standard Deviation
Variance
Box plot
- Pandas
Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les
How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function
Using the Excel File class to read multiple sheets More Mapping, Filling
Nonvalue’s
Exploring the Data Plotting, Correlations, and Histograms
Getting statistical information about the data Analysis Concepts, Handle the None Values
Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc
Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows
Applying formulas on the columns Basic Grouping, Concepts of Aggre
gate Function
Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)
Under sting the Properties of Pivot Table in Pandas Advanced Reading
CSVs/HTML, Binning, Categorical Data
Exporting the results to Excel Joins:
Python | Pandas Data Frame Inner Join
Under sting the properties of Data Frame Left Join (Left Outer Join)
Indexing and Selecting Data with Pandas Right Join (Right Outer Join)
Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)
Pandas | Find Missing Data and Fill and Drop NA Appending DataFrame and Data
Pandas | How to Group Data How to apply Lambda / Function on Data
Frame
Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)
Get full course syllabus in your inbox
- NumPy
Introduction to NumPy: Numerical Python
Importing NumPy and Its Properties
NumPy Arrays
Creating an Array from a CSV
Operations an Array from a CSV
Operations with NumPy Arrays
Two-Dimensional Array
Selecting Elements from 1-D Array
Selecting Elements from 2-D Array
Logical Operation with Arrays
Indexing NumPy elements using conditionals
NumPy’s Mean and Axis
NumPy’s Mode, Median and Sum Function
NumPy’s Sort Function and More
- MatPlotLib
Bar Chart using Python MatPlotLib
Column Chart using Python MatPlotLib
Pie Chart using Python MatPlotLib
Area Chart using Python MatPlotLib
Scatter Plot Chart using Python MatPlotLib
Play with Charts Properties Using MatPlotLib
Export the Chart as Image
Understanding plt. subplots () notation
Legend Alignment of Chart using MatPlotLib
Create Charts as Image
Other Useful Properties of Charts.
Complete Understanding of Histograms
Plotting Different Charts, Labels, and Labels Alignment etc.
Get full course syllabus in your inbox
- Introduction to Seaborn
Introduction to Seaborn
Making a scatter plot with lists
Making a count plot with a list
Using Pandas with seaborn
Tidy vs Untidy data
Making a count plot with a Dataframe
Adding a third variable with hue
Hue and scattera plots
Hue and count plots
- Visualizing Two Quantitative Variables
Introduction to relational plots and subplots
Creating subplots with col and row
Customizing scatters plots
Changing the size of scatter plot points
Changing the style of scatter plot points
Introduction to line plots
Interpreting line plots
Visualizing standard deviation with line plots
Plotting subgroups in line plots
- Visualizing a Categorical and a Quantitative Variable
Current plots and bar plots
Count plots
Bar plot with percentages
Customizing bar plots
Box plots
Create and interpret a box plot
Omitting outliers
Adjusting the whisk
Point plots
Customizing points plots
Point plot with subgroups
- Customizing Seaborn Plots
Changing plot style and colour
Changing style and palette
Changing the scale
Using a custom palette
Adding titles and labels: Part 1
Face Grids vs. Axes Subplots
Adding a title to a face Grid object
Adding title and labels: Part 2
Adding a title and axis labels
Rotating x-tics labels
Putting it all together
Box plot with subgroups
Bar plot with subgroups and subplots
Well done! What’s next
Get full course syllabus in your inbox
Machine Learning Training Program
30k
LearnersWeekend/WeekdayLive
Class
- 2 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
- Machine learning is important because it gives enterprises a view of trends in ustomer behavior and business operational patterns, as well as supports the development of new products. Many of today's leading companies, such as Facebook, Google and Uber, make machine learning a central part of their operations
- In this program you will learn:
Introduction to Machine Learning
Techniques of Machine Learning
Regression
Classification
Unsupervised Learning: Clustering
Distribution Clustering
Get full course syllabus in your inbox
- Introduction to Machine Learning
Articial Intelligence
Machine Learning
Machine Learning Algorithms
Algorithmic models of Learning
Applications of Machine Learning
Large Scale Machine Learning
Computational Learning theory
Reinforcement Learning
Get full course syllabus in your inbox
- Techniques of Machine Learning
Supervised Learning
Unsupervised Learning
Semi-supervised and Reinforcement Learning
Bias and variance Trade-off
Representation Learning
Get full course syllabus in your inbox
- Regression
Regression and its Types
Logistic Regression
Linear Regression
Polynomial Regression
Get full course syllabus in your inbox
- Classification
Meaning and Types of Classification
Nearest Neighbor Classifiers
K-nearest Neighbors
Probability and Bayes Theorem
Support Vector Machines
Naive Bayes
Decision Tree Classifier
Random Forest Classifier
Get full course syllabus in your inbox
Deep Learning Training Program
30k
LearnersWeekend/WeekdayLive
Class
- 2 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
- The Deep learning training program is diligently designed in tandem with industrial needs that helps you master Deep learning fundamentals, machine learning concepts, python programming, and a lot more. The course helps the students to learn about neural networks, logistic regression, TensorFlow concepts, Python libraries, binary classification
- In this program you will learn:
Introduction to Deep Learning
Deep Learning Networks
Deep Learning with Keras
Convolutional Neural Networks (CNN)
Recurrent Neural Network (RNN)
Natural Language Processing
Overview of Tensor Flow
Neural Networks Using Tensor Flow
Get full course syllabus in your inbox
- Introduction to Deep Learning
What are the Limitations of Machine Learning
What is Deep Learning
Advantage of Deep Learning over Machine learning
Reasons to go for Deep Learning
Real-Life use cases of Deep Learning
Get full course syllabus in your inbox
- Deep Learning Networks
What is Deep Learning Networks
Why Deep Learning Networks
How Deep Learning Works
Feature Extraction
Working of Deep Network
Training using Backpropagation
Variants of Gradient Descent
Types of Deep Networks
Feed forward neural networks (FNN)
Convolutional neural networks (CNN)
Recurrent Neural networks (RNN)
Restrict Boltzman Machine (RBM)
Get full course syllabus in your inbox
- Deep Learning with Keras
Dene Keras
How to compose Models in Keras
Sequential Composition
Functional Composition
Predened Neural Network Layers
What is Batch Normalization
Saving and Loading a model with Keras
Customizing the Training Process
Intuitively building networks with Keras
Get full course syllabus in your inbox
- Convolutional Neural Networks (CNN)
Introduction to Convolutional Neural Networks
CNN Applications
Architecture of a Convolutional Neural Network
Convolution and Pooling layers in a CNN
Understanding and Visualizing CNN
Transfer Learning and Fine-tuning Convolutional Neural Networks
Get full course syllabus in your inbox
Data Science Training Program
30k
LearnersWeekend/WeekdayLive
Class
- 5 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
- Understanding Concepts of Excel
Creation of Excel Sheet Data
Range Name, Format Painter
Conditional Formatting, Wrap Text, Merge & Centre
Sort, Filter, Advance Filter
Different type of Chart Creations
Auditing, (Trace Precedents, Trace Dependents)Print Area
Data Validations, Consolidate, Subtotal
What if Analysis (Data Table, Goal Seek, Scenario)
Solver, Freeze Panes
Various Simple Functions in Excel(Sum, Average, Max, Min)
Real Life Assignment work
- Ms Excel Advance
- Lookup
- VLookup
- HLookup
- Column Wise
- Row Wise
- Auto Filter
- Advance Filter
- Goal Seek
- Scenario Manager
- Advance use of Data Tables in Excel
- Reporting and Information Representation
- Pivot Chat
- Slicer with Pivot Table & Chart
- Advance Functions of Excel
- Math & Trig Functions
Advance Data Sorting
Multi-level sorting
Restoring data to original order after performing sorting
Sort by icons
Sort by colours
Lookup Functions
Subtotal, Multi-Level Subtotal
Grouping Features
Consolidation With Several Worksheets
Filter
Printing of Raw & Column Heading on Each Page
Workbook Protection and Worksheet Protection
Specified Range Protection in Worksheet
Excel Data Analysis
Data Table
Pivot Table
Generating MIS Report In Excel
Text Functions
Lookup & Reference Function
Logical Functions & Date and Time Functions
Database Functions
Statistical Functions
Financial Functions
Functions for Calculation Depreciation
Get full course syllabus in your inbox
- SQL Server Fundamentals
SQL Server 2019 Installation
Service Accounts & Use, Authentication Modes & Usage, Instance Congurations
SQL Server Features & Purpose
Using Management Studio (SSMS)
Conguration Tools & SQLCMD
Conventions & Collation
- SQL Server 2019 Database Design
SQL Database Architecture
Database Creation using GUI
Database Creation using T-SQL scripts
DB Design using Files and File Groups
File locations and Size parameters
Database Structure modications
- SQL Tables in MS SQL Server
SQL Server Database Tables
Table creation using T-SQL Scripts
Naming Conventions for Columns
Single Row and Multi-Row Inserts
Table Aliases
Column Aliases & Usage
Table creation using Schemas
Basic INSERT
UPDATE
DELETE
SELECT queries and Schemas
Use of WHERE, IN and BETWEEN
Variants of SELECT statement
ORDER BY
GROUPING
HAVING
ROWCOUNT and CUBE Functions
- Data Validation and Constraints
Table creation using Constraints
NULL and IDENTITY properties
UNIQUE KEY Constraint and NOT NULL
PRIMARY KEY Constraint & Usage
CHECK and DEFAULT Constraints
Naming Composite Primary Keys
Disabling Constraints & Other Options
- Views and Row Data Security
Benets of Views in SQL Database
Views on Tables and Views
SCHEMA BINDING and ENCRYPTION
Issues with Views and ALTER TABLE
Common System Views and Metadata
Common Dynamic Management views
Working with JOINS inside views
- Indexes and Query tuning
Need for Indexes & Usage
Indexing Table & View Columns
Index SCAN and SEEK
INCLUDED Indexes & Usage
Materializing Views (storage level)
Composite Indexed Columns & Keys
Indexes and Table Constraints
Primary Keys & Non-Clustered Indexes
- Stored Procedures and Benets
Why to use Stored Procedures
Types of Stored Procedures
Use of Variables and parameters
SCHEMABINDING and ENCRYPTION
INPUT and OUTPUT parameters
System level Stored Procedures
Dynamic SQL and parameterization
- System functions and Usage
Scalar Valued Functions
Types of Table Valued Functions
SCHEMABINDING and ENCRYPTION
System Functions and usage
Date Functions
Time Functions
String and Operational Functions
ROW_COUNT
GROUPING Functions
- Triggers, cursors, memory limitations
Why to use Triggers
DML Triggers and Performance impact
INSERTED and DELETED memory tables
Data Audit operations & Sampling
Database Triggers and Server Triggers
Bulk Operations with Triggers
- Cursors and Memory Limitations
Cursor declaration and Life cycle
STATIC
DYNAMIC
SCROLL Cursors
FORWARD_ONLY and LOCAL Cursors
KEYSET Cursors with Complex SPs
- Transactions Management
ACID Properties and Scope
EXPLICIT Transaction types
IMPLICIT Transactions and options
AUTOCOMMIT Transaction and usage
Get full course syllabus in your inbox
- Introduction to Power BI
Overview of BI concepts
Why we need BI
Introduction to SSBI
SSBI Tools
Why Power BI
What is Power BI
Building Blocks of Power BI
Getting started with Power BI Desktop
Get Power BI Tools
Introduction to Tools and Terminology
Dashboard in Minutes
Interacting with your Dashboards
Sharing Dashboards and Reports
- Power BI Desktop
Power BI Desktop
Extracting data from various sources
Workspaces in Power BI
- Power BI Data Transformation
Data Transformation
Query Editor
Connecting Power BI Desktop to our Data Sources
Editing Rows
Understanding Append Queries
Editing Columns
Replacing Values
Formatting Data
Pivoting and Unpivoting Columns
Splitting Columns
Creating a New Group for our Queries
Introducing the Star Schema
Duplicating and Referencing Queries
Creating the Dimension Tables
Entering Data Manually
Merging Queries
Finishing the Dimension Table
Introducing the another DimensionTable
Creating an Index Column
Duplicating Columns and Extracting Information
Creating Conditional Columns
Creating the FACT Table
Performing Basic Mathematical Operations
Improving Performance and Loading Data into the Data Model
- Modelling with Power BI
Introduction to Modelling
Modelling Data
Manage Data Relationship
Optimize Data Models
Cardinality and Cross Filtering
Default Summarization & Sort by
Creating Calculated Columns
Creating Measures & Quick Measures
- Data Analysis Expressions (DAX)
What is DAX
Data Types in DAX
Calculation Types
Syntax, Functions, Context Options
DAX Functions
Date and Time
Time Intelligence
Information
Logical
Mathematical
Statistical
Text and Aggregate
Measures in DAX
Measures and Calculated Columns
ROW Context and Filter Context in DAX
Operators in DAX - Real-time Usage
Quick Measures in DAX - Auto validations
In-Memory Processing DAX Performance
- Power BI Desktop Visualisations
How to use Visual in Power BI
What Are Custom Visuals
Creating Visualisations and Colour Formatting
Setting Sort Order
Scatter & Bubble Charts & Play Axis
Tooltips and Slicers, Timeline Slicers & Sync Slicers
Cross Filtering and Highlighting
Visual, Page and Report Level Filters
Drill Down/Up
Hierarchies and Reference/Constant Lines
Tables, Matrices & Conditional Formatting
KPI's, Cards & Gauges
Map Visualizations
Custom Visuals
Managing and Arranging
Drill through and Custom Report Themes
Grouping and Binning and Selection Pane, Bookmarks & Buttons
Data Binding and Power BI Report Server
- Introduction to Power BI Dashboard and Data Insights
Why Dashboard and Dashboard vs Reports
Creating Dashboards
Conguring a Dashboard Dashboard Tiles, Pinning Tiles
Power BI Q&A
Quick Insights in Power BI
- Direct Connectivity
Custom Data Gateways
Exploring live connections to data with Power BI
Connecting directly to SQL Server
Connectivity with CSV & Text Files
Excel with Power BI Connect Excel to Power BI, Power BI Publisher for Excel
Content packs
Update content packs
- Publishing and Sharing
Introduction and Sharing Options Overview
Publish from Power BI Desktop and Publish to Web
Share Dashboard with Power BI Service
Workspaces (Power BI Pro) and Content Packs (Power BI Pro)
Print or Save as PDF and Row Level Security (Power BI Pro)
Export Data from a Visualization
Export to PowerPoint and Sharing Options Summary
- Refreshing Datasets
Understanding Data Refresh
Personal Gateway (Power BI Pro and 64-bit Windows)
Replacing a Dataset and Troubleshooting Refreshing
Get full course syllabus in your inbox
- Introduction To Python
Installation and Working with Python
Understanding Python variables
Python basic Operators
Understanding the Python blocks.
- Python Keyword and Identiers
Python Comments, Multiline Comments.
Python Indentation
Understating the concepts of Operators
Arithmetic
Relational
Logical
Assignment
Membership
Identity
- Introduction To Variables
Variables, expression condition and function
Global and Local Variables in Python
Packing and Unpacking Arguments
Type Casting in Python
Byte objects vs. string in Python
Variable Scope
- Python Data Type
Declaring and using Numeric data types
Using string data type and string operations
Understanding Non-numeric data types
Understanding the concept of Casting and Boolean.
Strings
List
Tuples
Dictionary
Sets
- Control Structure & Flow
Statements - if, else, elif
How to use nested IF and Else in Python
Loops
Loops and Control Statements.
Jumping Statements - Break, Continue, pass
Looping techniques in Python
How to use Range function in Loop
Programs for printing Patterns in Python
How to use if and else with Loop
Use of Switch Function in Loop
Elegant way of Python Iteration
Generator in Python
How to use nested Loop in Python
Use If and Else in for and While Loop
Examples of Looping with Break and Continue Statement
How to use IN or NOT IN keyword in Python Loop.
- List
What is List.
List Creation
List Length
List Append
List Insert
List Remove
List Append & Extend using "+" and Keyword
List Delete
List related Keyword in Python
List Reverse
List Sorting
List having Multiple Reference
String Split to create a List
List Indexing
List Slicing
List count and Looping
List Comprehension and Nested Comprehension
- Tuple
What is Tuple
Tuple Creation
Accessing Elements in Tuple
Changing a Tuple
Tuple Deletion
Tuple Count
Tuple Index
Tuple Membership
TupleBuilt in Function (Length, Sort)
- Dictionary
Dict Creation
Dict Access (Accessing Dict Values)
Dict Get Method
Dict Add or Modify Elements
Dict Copy
Dict From Keys.
Dict Items
Dict Keys (Updating, Removing and Iterating)
Dict Values
Dict Comprehension
Default Dictionaries
Ordered Dictionaries
Looping Dictionaries
Dict useful methods (Pop, Pop Item, Str , Update etc.)
- Sets
What is Set
Set Creation
Add element to a Set
Remove elements from a Set
PythonSet Operations
Frozen Sets
- Strings
What is Set
Set Creation
Add element to a Set
Remove elements from a Set
PythonSet Operations
- Python Function, Modules and Packages
Python Syntax
Function Call
Return Statement
Arguments in a function - Required, Default, Positional, Variable-length
Write an Empty Function in Python -pass statement.
Lamda/ Anonymous Function
*args and **kwargs
Help function in Python
Scope and Life Time of Variable in Python Function
Nested Loop in Python Function
Recursive Function and Its Advantage and Disadvantage
Organizing python codes using functions
Organizing python projects into modules
Importing own module as well as external modules
Understanding Packages
Random functions in python
Programming using functions, modules & external packages
Map, Filter and Reduce function with Lambda Function
More example of Python Function
- Decorator, Generator and Iterator
Creation and working of decorator
Idea and practical example of generator, use of generator
Concept and working of Iterator
- Python Exception Handling
Python Errors and Built-in-Exceptions
Exception handing Try, Except and Finally
Catching Exceptions in Python
Catching Specic Exception in Python
Raising Exception
Try and Finally
- Python File Handling
Opening a File
Python File Modes
Closing File
Writing to a File
Reading from a File
Renaming and Deleting Files in Python
Python Directory and File Management
List Directories and Files
Making New Directory
Changing Directory
- Memory management using python
Threading, Multi-threading
Memory management concept of python
working of Multi tasking system
Different os function with thread
- Python Database Interaction
SQL Database connection using
Creating and searching tables
Reading and Storing cong information on database
Programming using database connections
- Reading an excel
Working With Excel
Reading an excel le using Python
Writing to an excel sheet using Python
Python| Reading an excel le
Python | Writing an excel le
Adjusting Rows and Column using Python
ArithmeticOperation in Excel le.
Play with Workbook, Sheets and Cells in Excel using Python
Creating and Removing Sheets
Formatting the Excel File Data
More example of Python Function
- Complete Understanding of OS Module of Python
Check Dirs. (exist or not)
How to split path and extension
How to get user prole detail
Get the path of Desktop, Documents, Downloads etc.
Handle the File System Organization using OS
How to get any les and folder's details using OS
Get full course syllabus in your inbox
- Introduction to Machine Learning
What is Machine Learning
Machine Learning Use-Cases
Machine Learning Process Flow
Machine Learning Categories
- Time Series Analysis
What is Time Series Analysis
Importance of TSA
Components of TSA
White Noise
AR model
MA model
ARMA model
ARIMA model
Stationarity
ACF & PACF
- Statistical Foundations (Self-Paced)
What is Exploratory Data Analysis
EDA Techniques
EDA Classification
Univariate Non-graphical EDA
Univariate Graphical EDA
Multivariate Non-graphical EDA
Multivariate Graphical EDA
Heat Maps
- Introduction to Text Mining and NLP
Overview of Text Mining
Need of Text Mining
Natural Language Processing (NLP) in Text Mining
Get full course syllabus in your inbox
Artificial Intelligence Training Program
30k
LearnersWeekend/WeekdayLive
Class
- 9 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
- Introduction To Python
Installation and Working with Python
Understanding Python variables
Python basic Operators
Understanding the Python blocks.
- Python Keyword and Identiers
Python Comments, Multiline Comments.
Python Indentation
Understating the concepts of Operators
Arithmetic
Relational
Logical
Assignment
Membership
Identity
- Introduction To Variables
Variables, expression condition and function
Global and Local Variables in Python
Packing and Unpacking Arguments
Type Casting in Python
Byte objects vs. string in Python
Variable Scope
- Python Data Type
Declaring and using Numeric data types
Using string data type and string operations
Understanding Non-numeric data types
Understanding the concept of Casting and Boolean.
Strings
List
Tuples
Dictionary
Sets
- Control Structure & Flow
Statements – if, else, elif
How to use nested IF and Else in Python
Loops
Loops and Control Statements.
Jumping Statements – Break, Continue, pass
Looping techniques in Python
How to use Range function in Loop
Programs for printing Patterns in Python
How to use if and else with Loop
Use of Switch Function in Loop
Elegant way of Python Iteration
Generator in Python
How to use nested Loop in Python
Use If and Else in for and While Loop
Examples of Looping with Break and Continue Statement
How to use IN or NOT IN keyword in Python Loop.
- List
What is List.
List Creation
List Length
List Append
List Insert
List Remove
List Append & Extend using “+” and Keyword
List Delete
List related Keyword in Python
List Reverse
List Sorting
List having Multiple Reference
String Split to create a List
List Indexing
List Slicing
List count and Looping
List Comprehension and Nested Comprehension
- Tuple
What is Tuple
Tuple Creation
Accessing Elements in Tuple
Changing a Tuple
Tuple Deletion
Tuple Count
Tuple Index
Tuple Membership
TupleBuilt in Function (Length, Sort)
- Dictionary
Dict Creation
Dict Access (Accessing Dict Values)
Dict Get Method
Dict Add or Modify Elements
Dict Copy
Dict From Keys.
Dict Items
Dict Keys (Updating, Removing and Iterating)
Dict Values
Dict Comprehension
Default Dictionaries
Ordered Dictionaries
Looping Dictionaries
Dict useful methods (Pop, Pop Item, Str , Update etc.)
- Sets
What is Set
Set Creation
Add element to a Set
Remove elements from a Set
PythonSet Operations
Frozen Sets
- Strings
What is Set
Set Creation
Add element to a Set
Remove elements from a Set
PythonSet Operations
- Python Function, Modules and Packages
Python Syntax
Function Call
Return Statement
Arguments in a function – Required, Default, Positional, Variable-length
Write an Empty Function in Python –pass statement.
Lamda/ Anonymous Function
*args and **kwargs
Help function in Python
Scope and Life Time of Variable in Python Function
Nested Loop in Python Function
Recursive Function and Its Advantage and Disadvantage
Organizing python codes using functions
Organizing python projects into modules
Importing own module as well as external modules
Understanding Packages
Random functions in python
Programming using functions, modules & external packages
Map, Filter and Reduce function with Lambda Function
More example of Python Function
- Decorator, Generator and Iterator
Creation and working of decorator
Idea and practical example of generator, use of generator
Concept and working of Iterator
- Python Exception Handling
Python Errors and Built-in-Exceptions
Exception handing Try, Except and Finally
Catching Exceptions in Python
Catching Specic Exception in Python
Raising Exception
Try and Finally
- Python File Handling
Opening a File
Python File Modes
Closing File
Writing to a File
Reading from a File
Renaming and Deleting Files in Python
Python Directory and File Management
List Directories and Files
Making New Directory
Changing Directory
- Memory management using python
Threading, Multi-threading
Memory management concept of python
working of Multi tasking system
Different os function with thread
- Python Database Interaction
SQL Database connection using
Creating and searching tables
Reading and Storing cong information on database
Programming using database connections
- Reading an excel
Working With Excel
Reading an excel le using Python
Writing to an excel sheet using Python
Python| Reading an excel le
Python | Writing an excel le
Adjusting Rows and Column using Python
ArithmeticOperation in Excel le.
Play with Workbook, Sheets and Cells in Excel using Python
Creating and Removing Sheets
Formatting the Excel File Data
More example of Python Function
- Complete Understanding of OS Module of Python
Check Dirs. (exist or not)
How to split path and extension
How to get user prole detail
Get the path of Desktop, Documents, Downloads etc.
Handle the File System Organization using OS
How to get any les and folder’s details using OS
Get full course syllabus in your inbox
- Data Analysis and Visualization using Pandas.
- Categorical Data
- Numerical Data
- Mean
- Median
- Mode
- Outliers
- Range
- Interquartile range
- Correlation
- Standard Deviation
- Variance
- Box plot
- Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les
- How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function
- Using the Excel File class to read multiple sheets More Mapping, Filling Nonvalue’s
- Exploring the Data Plotting, Correlations, and Histograms
- Getting statistical information about the data Analysis Concepts, Handle the None Values
- Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc
- Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows
- Applying formulas on the columns Basic Grouping, Concepts of Aggre gate Function
- Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)
- Under sting the Properties of Pivot Table in Pandas Advanced Reading CSVs/HTML, Binning, Categorical Data
- Exporting the results to Excel Joins
- Python | Pandas Data Frame Inner Join
- Under sting the properties of Data Frame Left Join (Left Outer Join)
- Indexing and Selecting Data with Pandas Right Join (Right Outer Join)
- Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)
- Pandas | Find Missing Data and Fill and Drop NA Appending Data Frame and Data
- Pandas | How to Group Data How to apply Lambda / Function on Data Frame
- Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)
Statistics
Pandas
Get full course syllabus in your inbox
- Introduction to Statistics
Descriptive Statistics
Sample vs Population Statistics
Random variables
Probability distribution functions
Expected value
Normal distribution
Gaussian distribution
Z-score
Spread and Dispersion
Correlation and Co-variance
- EDA (Exploratory Data Analysis)
Need for structured exploratory data
EDA framework for exploring the data and identifying any problems with the data (Data Audit Report)
Identify missing data
Identify outliers’ data
Imbalanced Data Techniques
- Data Pre-Processing & Data Mining
Data Preparation
Feature Engineering
Feature Scaling, Feature Transformation and Dimensionality Reduction
Datasets
Dimensionality Reduction (PCA, ICA,LDA)
Anomaly Detection
Parameter Estimation
Data and Knowledge
Selected Applications in Data Mining
- Introduction to Predictive Modelling
Difference between Analysis and Analytics
Concept of model in analytics and how it is used
Common terminology used in Analytics & Modelling process
Popular Modelling algorithms, Data Analytics Life cycle
Types of Business problems - Mapping of Techniques
Get full course syllabus in your inbox
- SQL Server Fundamentals
SQL Server 2019 Installation
Service Accounts & Use, Authentication Modes & Usage, Instance Congurations
SQL Server Features & Purpose
Using Management Studio (SSMS)
Conguration Tools & SQLCMD
Conventions & Collation
- SQL Server 2019 Database Design
SQL Database Architecture
Database Creation using GUI
Database Creation using T-SQL scripts
DB Design using Files and File Groups
File locations and Size parameters
Database Structure modications
- SQL Tables in MS SQL Server
SQL Server Database Tables
Table creation using T-SQL Scripts
Naming Conventions for Columns
Single Row and Multi-Row Inserts
Table Aliases
Column Aliases & Usage
Table creation using Schemas
Basic INSERT
UPDATE
DELETE
SELECT queries and Schemas
Use of WHERE, IN and BETWEEN
Variants of SELECT statement
ORDER BY
GROUPING
HAVING
ROWCOUNT and CUBE Functions
- Data Validation and Constraints
Table creation using Constraints
NULL and IDENTITY properties
UNIQUE KEY Constraint and NOT NULL
PRIMARY KEY Constraint & Usage
CHECK and DEFAULT Constraints
Naming Composite Primary Keys
Disabling Constraints & Other Options
- Views and Row Data Security
Benets of Views in SQL Database
Views on Tables and Views
SCHEMA BINDING and ENCRYPTION
Issues with Views and ALTER TABLE
Common System Views and Metadata
Common Dynamic Management views
Working with JOINS inside views
- Indexes and Query tuning
Need for Indexes & Usage
Indexing Table & View Columns
Index SCAN and SEEK
INCLUDED Indexes & Usage
Materializing Views (storage level)
Composite Indexed Columns & Keys
Indexes and Table Constraints
Primary Keys & Non-Clustered Indexes
- Stored Procedures and Benets
Why to use Stored Procedures
Types of Stored Procedures
Use of Variables and parameters
SCHEMABINDING and ENCRYPTION
INPUT and OUTPUT parameters
System level Stored Procedures
Dynamic SQL and parameterization
- System functions and Usage
Scalar Valued Functions
Types of Table Valued Functions
SCHEMABINDING and ENCRYPTION
System Functions and usage
Date Functions
Time Functions
String and Operational Functions
ROW_COUNT
GROUPING Functions
- Triggers, cursors, memory limitations
Why to use Triggers
DML Triggers and Performance impact
INSERTED and DELETED memory tables
Data Audit operations & Sampling
Database Triggers and Server Triggers
Bulk Operations with Triggers
- Cursors and Memory Limitations
Cursor declaration and Life cycle
STATIC
DYNAMIC
SCROLL Cursors
FORWARD_ONLY and LOCAL Cursors
KEYSET Cursors with Complex SPs
- Transactions Management
ACID Properties and Scope
EXPLICIT Transaction types
IMPLICIT Transactions and options
Get full course syllabus in your inbox
- Understanding Concepts of Excel
Creation of Excel Sheet Data
Range Name, Format Painter
Conditional Formatting, Wrap Text, Merge & Centre
Sort, Filter, Advance Filter
Different type of Chart Creations
Auditing, (Trace Precedents, Trace Dependents)Print Area
Data Validations, Consolidate, Subtotal
What if Analysis (Data Table, Goal Seek, Scenario)
Solver, Freeze Panes
Various Simple Functions in Excel(Sum, Average, Max, Min)
Real Life Assignment work
- Ms Excel Advance
- Lookup
- VLookup
- HLookup
- Column Wise
- Row Wise
- Auto Filter
- Advance Filter
- Goal Seek
- Scenario Manager
- Advance use of Data Tables in Excel
- Reporting and Information Representation
- Pivot Chat
- Slicer with Pivot Table & Chart
- Advance Functions of Excel
- Math & Trig Functions
Advance Data Sorting
Multi-level sorting
Restoring data to original order after performing sorting
Sort by icons
Sort by colours
Lookup Functions
Subtotal, Multi-Level Subtotal
Grouping Features
Consolidation With Several Worksheets
Filter
Printing of Raw & Column Heading on Each Page
Workbook Protection and Worksheet Protection
Specified Range Protection in Worksheet
Excel Data Analysis
Data Table
Pivot Table
Generating MIS Report In Excel
Text Functions
Lookup & Reference Function
Logical Functions & Date and Time Functions
Database Functions
Statistical Functions
Financial Functions
Functions for Calculation Depreciation
Get full course syllabus in your inbox
Internet of Things (IoT) Certification Training
40k
LearnersWeekend/WeekdayLive
Class
- 2 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
- In this program you will learn:
Internet of Things (IoT) Introduction
IoT Architecture
Understanding IoT Ecosystems
Raspberry Pi
IoT Gateways
Cloud Platforms for IoT
IoT Implementations [Applications]
Future & Security Concerns
Get full course syllabus in your inbox
- Internet of Things (IoT) Introduction
Background and Development
Three waves of Internet
Why IoT
Market Analysis & Investment In IoT
Industrial & Consumer IoT
M2M communication and automation history
Relation with embedded systems
General introduction to Arduino , Raspberry Pi and SmartWifi boards
Get full course syllabus in your inbox
- IoT Architecture
How IoT Works
High level Data Flow in IoT
Technical Architecture
Description of all layers of IoT Architecture
Technologies for IoT
Get full course syllabus in your inbox
- Understanding IoT Ecosystems
What is IoT application
What are basic elements / building blocks of IoT app
How are these blocks connected together
The systematic method to design IoT application
Architecting our hands-on project
Get full course syllabus in your inbox
- Raspberry Pi
Learning fundamentals of Raspberry Pi
Different types of pi boards.
Installation of OS in Raspberry Pi
Programming Raspberry Pi Using Python
Get full course syllabus in your inbox
Advanced Python Programming Course
30k
LearnersWeekend/WeekdayLive
Class
- 0 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
- What is Data Analytic
- Common Terms in Data Analytics
- What is data
- Classication of data
- Relevance in industry and need of the hour
- Types of problems and business objectives in various industries
- How leading companies are harnessing the power of analytics
- Critical success drivers.
- Overview of Data Analytics tools & their popularity.
- Data Analytics Methodology & problem-solving framework.
- List of steps in Data Analytics projects
Get full course syllabus in your inbox
- Introduction To Python
Installation and Working with Python
Understanding Python variables
Python basic Operators
Understanding the Python blocks.
- Python Keyword and Identiers
- Arithmetic
- Relational
- Logical
- Assignment
- Membership
- Identity
Python Comments, Multiline Comments.
Python Indentation
Understating the concepts of Operators
Get full course syllabus in your inbox
- Introduction to Statistics
Categorical Data
Numerical Data
Mean
Median
Mode
Outliers
Range
Interquartile range
Correlation
Standard Deviation
Variance
Box plot
- Understanding Statistics
Descriptive Statistics
Sample vs Population Statistics
Random variables
Probability distribution functions
Expected value
Normal distribution
Gaussian distribution
Z-score
Spread and Dispersion
Correlation and Co-variance
- Data Pre-Processing & Data Mining
Data Preparation
Feature Engineering
Feature Scaling
Datasets
Dimensionality Reduction
Anomaly Detection
Parameter Estimation
Data and Knowledge
Selected Applications in Data Mining
- EDA (Exploratory Data Analysis)
Need for structured exploratory data
EDA framework for exploring the data and identifying any problems with the data (Data Audit Report)
Identify missing data
Identify outliers’ data
Imbalanced Data Techniques
Get full course syllabus in your inbox
- Data Analysis and Visualization using Pandas.
Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les
How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function
Using the Excel File class to read multiple sheets More Mapping, Filling Nonvalue’s
Exploring the Data Plotting, Correlations, and Histograms
Getting statistical information about the data Analysis Concepts, Handle the None Values
Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc
Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows
Applying formulas on the columns Basic Grouping, Concepts of Aggre gate Function
Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)
Under sting the Properties of Pivot Table in Pandas Advanced Reading CSVs/HTML, Binning, Categorical Data
Exporting the results to Excel Joins
Python | Pandas Data Frame Inner Join
Under sting the properties of Data Frame Left Join (Left Outer Join)
Indexing and Selecting Data with Pandas Right Join (Right Outer Join)
Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)
Pandas | Find Missing Data and Fill and Drop NA Appending Data Frame and Data
Pandas | How to Group Data How to apply Lambda / Function on Data Frame
Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)
- Data Analysis and Visualization using NumPy
Introduction to NumPy Numerical Python
Importing NumPy and Its Properties
NumPy Arrays
Creating an Array from a CSV
Operations an Array from a CSV
Operations with NumPy Arrays
Two-Dimensional Array
Selecting Elements from 1-D Array
Selecting Elements from 2-D Array
Logical Operation with Arrays
Indexing NumPy elements using conditionals
NumPy’s Mean and Axis
NumPy’s Mode, Median and Sum Function
NumPy’s Sort Function and More
- Data Analysis and Visualization using MatPlotLib
Bar Chart using Python MatPlotLib
Column Chart using Python MatPlotLib
Pie Chart using Python MatPlotLib
Area Chart using Python MatPlotLib
Scatter Plot Chart using Python MatPlotLib
Play with Charts Properties Using MatPlotLib
Export the Chart as Image
Understanding plt. subplots () notation
Legend Alignment of Chart using MatPlotLib
Create Charts as Image
Other Useful Properties of Charts.
Complete Understanding of Histograms
Plotting Different Charts, Labels, and Labels Alignment etc.
- Introduction to Data Visualization with Seaborn
- Introduction to relational plots and subplots
- Creating subplots with col and row
- Customizing scatters plots
- Changing the size of scatter plot points
- Changing the style of scatter plot points
- Introduction to line plots
- Interpreting line plots
- Visualizing standard deviation with line plots
- Plotting subgroups in line plots
- Current plots and bar plots
- Count plots
- Bar plot with percentages
- Customizing bar plots
- Box plots
- Create and interpret a box plot
- Omitting outliers
- Adjusting the whisk
- Point plots
- Customizing points plots
- Point plot with subgroups
- Changing plot style and colour
- Changing style and palette
- Changing the scale
- Using a custom palette
- Adding titles and labels Part 1
- Face Grids vs. Axes Subplots
- Adding a title to a face Grid object
- Adding title and labels Part 2
- Adding a title and axis labels
- Rotating x-tics labels
- Putting it all together
- Box plot with subgroups
- Bar plot with subgroups and subplots
- Well done! What’s next
Introduction to Seaborn
Making a scatter plot with lists
Making a count plot with a list
Using Pandas with seaborn
Tidy vs Untidy data
Making a count plot with a Dataframe
Adding a third variable with hue
Hue and scattera plots
Hue and count plots
Visualizing Two Quantitative Variables
Visualizing a Categorical and a Quantitative Variable
Customizing Seaborn Plots
Get full course syllabus in your inbox
Python Django Course
30k
LearnersWeekend/WeekdayLive
Class
- 0 Live Project
- Self-Paced/ Classroom
- Certification Pass Guaranteed
Not just learning –
we train you to get hired.
Phone (For Voice Call):
+91-971 152 6942WhatsApp (For Call & Chat):
+91-971 152 6942Real
Stories
success
inspiration
Abhishek
career upgrad
Upasana Singh
career upgrad
Shashank
career upgrad
Abhishek Rawat
career upgrad
Get exclusive
access to career resources
upon completion
Mock Session
You will get certificate after
completion of program
LMS Learning
You will get certificate after
completion of program
Career Support
You will get certificate after
completion of program
Showcase your Course Completion Certificate to Recruiters
-
Training Certificate is Govern By 12 Global Associations.
-
Training Certificate is Powered by “Wipro DICE ID”
-
Training Certificate is Powered by "Verifiable Skill Credentials"
in Collaboration with
Not Just Studying
We’re Doing Much More!
Empowering Learning Through Real Experiences and Innovation
Mock Interviews
Prepare & Practice for real-life job interviews by joining the Mock Interviews drive at Croma Campus and learn to perform with confidence with our expert team.Not sure of Interview environments? Don’t worry, our team will familiarize you and help you in giving your best shot even under heavy pressures.Our Mock Interviews are conducted by trailblazing industry-experts having years of experience and they will surely help you to improve your chances of getting hired in real.
How Croma Campus Mock Interview Works?
Not just learning –
we train you to get hired.
Phone (For Voice Call):
+91-971 152 6942WhatsApp (For Call & Chat):
+91-971 152 6942Download Curriculum
Get a peek through the entire curriculum designed that ensures Placement Guidance
Course Design By
Request Your Batch Now
Ready to streamline Your Process? Submit Your batch request today!
+91-971 152 6942
+91-971 152 6942 
Interested in Azure Machine Learning Certification Course? 
+16395255419
+91-971 152 6942
Interested in Course?
Master in Cloud Computing Training