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Our Python Online Course is devised for students, freshers, and working professionals wanting to gain comprehensive programming skills and apply Python programming concept in practical work situations. We begin our Python Course with Placement with basic Python concept.
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- Python is not only utilized to write simple codes but today is applied extensively in web programming, automation, data analysis, testing, AI development, scripting, and other activities. Python codes are easy to read due to a simple syntax but real-life Python Programming Online Course involves mastering such topics as functions, modules, errors handling, files, databases, and project programming.
- Python Course with Placement will help you to understand the process taking place in Python and not just learn new commands but rather teach you how to solve the problem, write functions, handle errors, and make reusable code.
- The significance of Python Online Classes also lies in the availability of the large standard library and different third-party packages. Official documentation on Python describes modules, packages, file I/O, exceptions, classes, iterators, and generators.
- Python Online Course with Placement at Croma Campus includes constant programming. Students can begin with writing small pieces of code and then move to more complicated projects. The point is not in memorizing codes but rather in understanding the reasons for using certain code and results of its execution.
- The evidence for the usefulness of Python Training in india lies in today's developer statistics. For instance, the 2025 Stack Overflow Developer Survey stated a 7 percent increase in Python usage in 2025 compared to 2024 and pointed out its involvement in such domains as AI, data science, and back-end development.
- Learning through taking a Python Online Training can be useful for college students, freshers, testers, developers and other working professionals. In this Python Course, one can move from learning the basics of syntax to becoming an expert in such areas as object-oriented programming, using APIs, databases and finishing projects.
- One more factor which is worth considering is debugging. It is possible to write code which looks perfect but has errors. Thus, the ability to analyze errors, find a place where they occurred and fix the code instead of rewriting it is practiced by students.
Python Online Course
- In this Python Online Classes, learners will study:
Python syntax and program structure
Variables and different data types
Conditions and loops
Strings, lists, tuples, sets and dictionaries
Functions and arguments
Modules and packages
File handling
Exception handling
Object-oriented programming
Iterators and generators
Working with JSON data
Regular expressions
Database connectivity
API basics
Debugging and testing
Automation scripts
Real project examples
The Python Online Course gives more focus to practice, so learners can see what happens when code is actually executed.
- There are no strict requirements for joining the Python Programming Online Course.
- However, Python Training In India things can help:
Basic computer knowledge
Ability to use files and folders
Basic maths understanding
Logical thinking
Interest in programming
Willingness to practise code
You do not need to be an expert in another programming language. Beginners can start from the first step and learn slowly.
- The following candidates can join the Python Course with Placement:
College students
Fresh graduates
Beginners in programming
Software developers
Web developers
Testing professionals
Data professionals
Automation engineers
IT support professionals
Working IT professionals
Anyone interested in learning Python
The Python Course are useful for learners who want to study from home while still getting regular practice and trainer support.
- Python Course in India Basics:
- Logic Building In Python Course:
- Data Handling:
- Functions and Modules In Python Training:
- Files and Error Handling:
- Object-Oriented Python Training:
- Advanced Python Training Concepts:
- Database and API Work:
- Debugging and Testing:
- Real Project Scenarios:
Writing the first Python program
Understanding variables
Using numbers and strings
Taking input from users
Printing useful output
Using operators correctly
Using if and else
Writing loops
Working with nested conditions
Solving small coding problems
Breaking large problems into smaller steps
Working with lists
Using tuples
Understanding sets
Creating dictionaries
Sorting and searching data
Using list and dictionary comprehensions
Creating reusable functions
Passing arguments
Returning values
Using default arguments
Importing modules
Creating your own modules
Understanding packages
Reading text files
Writing data into files
Working with CSV and JSON
Using try and except
Creating useful error messages
Understanding common Python errors
Python officially supports exception handling and also allows developers to create user-defined exceptions. This is useful when a program needs to deal with problems in a controlled way.
Creating classes
Creating objects
Using methods
Understanding constructors
Working with inheritance
Using class and instance variables
Understanding simple object-based design
Python Course supports common object-oriented programming features such as inheritance and methods.
Iterators
Generators
Decorators
Lambda functions
Scope and namespaces
Regular expressions
Context managers
Virtual environments
Package management
Generators are useful when data needs to be produced step by step instead of keeping everything in memory at once. The official Python tutorial includes iterators, generators and generator expressions as part of the language.
Connecting Python with databases
Running basic queries
Reading database results
Understanding REST APIs
Sending requests
Reading JSON responses
Using API data inside Python programs
Reading traceback messages
Finding the source of an error
Using debugging methods
Testing functions
Checking expected output
Fixing logic mistakes
Writing cleaner code
File automation project
Student record system
Expense tracker
API data project
Database-based application
Web scraping practice
Simple automation tool
Python data processing project
- The tools covered in the Python Online Course with Placement are:
- Python:
- Python Standard Library:
- NumPy
- Pandas:
- Flask / FastAPI Concepts:
- SQL and Database Connectivity
- Git and GitHub:
Python programming
Functions and modules
Object-oriented programming
File and data handling
OS and file operations
JSON handling
Date and time
Regular expressions
Collections
Testing utilities
Python comes with a large standard library, which means many common programming jobs can be done without installing a separate package for every task.
Working with arrays
Numerical calculations
Data operations
Basic scientific computing
Reading data files
Working with tables
Cleaning data
Filtering and grouping records
Creating simple APIs
Handling requests
Returning responses
Building small backend services
Connecting applications with databases
Running SQL queries
Reading records
Updating data
Saving code versions
Working with repositories
Tracking changes
Sharing project code
- Following are some roles that professionals can take up after completing Python Training in india.
- Python Developer:
- Backend Developer
- Automation Developer
- Test Automation Engineer
- Data Analyst
- Junior Data / AI Developer
Write Python applications
Build reusable functions
Fix programming errors
Maintain project code
Create server-side programs
Build APIs
Connect applications with databases
Handle application logic
Create scripts for repeated tasks
Automate file operations
Automate reports
Reduce manual work
Write automated test scripts
Check application behaviour
Find software issues
Maintain test code
Clean data using Python
Work with tables
Create useful data reports
Perform basic data analysis
Prepare data
Use Python libraries
Build small machine learning projects
Support data and AI tasks
- After Completing Python Course in India Salary depends on experience, company, location, skills and the type of work handled. A learner should not treat one fixed salary number as guaranteed.
- Python Freshers (0-2 Years of Experience):
- Typical work includes:
- Python Mid-Level Professionals (3-6 Years of Experience)
- Typical work includes:
- Experienced Python Professionals (7+ Years of Experience)
- Typical work includes:
Writing small Python programs
Fixing simple bugs
Supporting development teams
Working with files, APIs or databases
Building application features
Creating APIs
Working with databases
Reviewing and improving code
Handling project requirements
Designing application systems
Reviewing technical solutions
Guiding development teams
Handling client requirements
Making decisions about project architecture
- After Completing Python Programming Online Course, Professionals with Python skills can work in many areas.
- Banking and Finance:
- E-commerce:
- Healthcare:
- Education:
- Testing and Quality Assurance:
- Data and AI:
Backend applications
Automation
Software development
Data processing
Report automation
Internal applications
Backend systems
Data processing
Business automation
Data handling
Internal software
Automation
Learning applications
Data processing
Student systems
Test automation
API testing
Regression testing
Data cleaning
Data analysis
Machine learning projects
- Module 1: Python Foundations:
- Module 2: Control Flow In Python Course:
- Module 3: Python Data Structures:
- Module 4: Functions and Modules:
- Module 5: Files and Exceptions:
- Module 6: Object-Oriented Programming:
- Module 7: APIs, Database and Automation:
- Module 8: Projects and Debugging:
Python setup
Syntax
Variables
Data types
Operators
Input and output
Conditions
For loops
While loops
Break and continue
Nested logic
Lists
Tuples
Sets
Dictionaries
Comprehensions
String handling
Functions
Arguments
Return values
Lambda functions
Modules
Packages
Reading files
Writing files
CSV
JSON
Exception handling
Custom exceptions
Classes
Objects
Methods
Constructors
Inheritance
Encapsulation basics
API basics
JSON responses
Database connection
SQL queries
Automation scripts
Project planning
Debugging
Testing
Git basics
Code improvement
End-to-end project work
- The Python Online Course with Placement helps learners develop programming skills which can be
- utilized in various technical fields. Python is applied in such fields as AI, data science,
- backend, automation, and testing. Pythons popularity was increasing among programmers
- according to the Stack Overflow survey in 2025.
- After learning Python Online Training, you can:
Understand how real programs are written.
Build small applications on your own.
Work with files, APIs and databases.
Create automation scripts.
Move towards data or AI learning.
Prepare for developer and testing roles.
Build projects for your portfolio.
Improve your problem-solving skills.
Why should you learn Python Online Course?
Not just learning
we train you to get hired.
Not just learning
we train you to get hired.
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Python Training Program
Python Training Program
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
- Installation and Working with Python
- Understanding Python variables
- Python basic Operators
- Understanding the Python blocks.
Get full course syllabus in your inbox
- Python Comments, Multiline Comments.
- Python Indentation
- Understating the concepts of Operators
Arithmetic
Relational
Logical
Assignment
Membership
Identity
Get full course syllabus in your inbox
- 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
Get full course syllabus in your inbox
- 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
Get full course syllabus in your inbox
- 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.
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)
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- 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.
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- 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
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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
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- 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
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- 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
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