Master the basics of ML and Python. Join now to learn under a Python and ML expert.
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Corporate Served- Machine Learning is considered as one of the most crucial skills today and its demand is surely going to increase in the future too tremendously. According to experts, Machine Learning will stay relevant for at least next 20 years. The Machine Learning Training in Delhi helps to acquire all the required skills and makes you proficient as an ML engineer.
- The Machine Learning certification course will help you to master various machine learning fundamental skills too that involve supervised learning, unsupervised learning, machine learning algorithms, vector machines, etc. You will get a chance to master all these concepts practically by working on various case-studies or assignments.
- The right training not only helps you to shape your career but leverages demand for skilled professionals too. The Machine learning placement course has been designed keeping latest industry trends in mind and certification structure to make you more relevant in the field.
- With the top Machine learning institute in Delhi, you can learn all the concepts step-by-step and make a strong foundation in the AI domain. It does not matter where you stand in your career currently, we can help you at all levels with course customization features.
- The Machine learning training in Delhi is designed with the core objective to define all the machine learning concepts in-depth and helps you to understand the roles and responsibilities in machine learning space.
- As the best Machine learning training in Delhi, we help you to master each of the concepts wisely and learn to apply them to the workplace too.
You may know about ML algorithms in detail including designing, development, and their implementation in the workplace.
You will get hands-on training in component analysis to design detailed data models using the best ML practices.
Know about different types of learning in ML and how it can be supported using vector algorithms.
With the comprehensive machine learning course, know about various machine learning concepts including linear regression, data modelling types, component analysis, vector machines, and more.
Know how to design an artificial neutral network and logical classification of data using R programming language.
- You must be wondering how much can you get as an expert ML professional Well, you are eligible to get $74K to $140K as a certified ML engineer at the fresher level. Moving ahead, variation can be seen in salaries in terms of location, Company, skillset, experience, etc. further, you have different job profiles that also affects the salary range. With Machine Learning placement course in Delhi, you become eligible to apply for jobs and bag attractive salaries even at the fresher level.
- It is true that Machine Learning domain is growing through leaps and bounds and it will stay relevant for many years to come. Companies are moving towards AI and robotics solutions slowly. They required people who can implement AI or machine learning concepts wisely. With the eminent Machine Learning training institute in Delhi, you can quickly implement all these skills and make yourself eligible for top industries too.
- At Croma Campus, we strongly believe that you should always start your training from basics. Even if you are an experienced user, brush up your skills first to make a strong foundation in the machine learning space. Once you have gained all the required skills, you must be excited to know about the career growth after the machine learning certification course.
- Gradually with our machine learning training course in Delhi, you can learn technical things like ML machines, supervised or unsupervised learning, ML algorithms, use-cases, projects, etc. Also, you will understand what are your roles and responsibilities in Machine Learning.
As soon as you become stronger in the Machine Learning domain, we help you to attempt the certification exam further.
As an expert ML engineer, you can design or implement ML algorithms successfully and showcase the same at your workplace too.
Get hired by top industries around the world and BAG huge salary packages that you ever dreamt of.
In a span of 2-3 years, see yourself more established when compared to your colleagues working at the same level.
- As the name suggests, Machine learning is a popular AI concept that helps machines to learn from patterns, examples, or past experiences. The best thing is that developers dont have to program much to achieve the excellence through machine learning. Instead of writing the code, you have to develop machine learning algorithms and the machine can build the logic by analyzing the existing data.
- Let us see some of the most important facts what makes the Machine Learning certification course more popular for aspirants.
- With the Machine Learning training in Delhi, we make you proficient in using different Machine learning tools or techniques. Also, work on multiple projects, assignments, and case studies as the part of training.
- With the leading Machine Learning training institute in Delhi, prepare yourself of certifications, top industries, and BAG good salaries too. Soon, when everything will be powered by AI soon, it is just the right time to start a career in Machine Learning with promising growth and job options ahead.
It is #1 IT skill in the AI space.
The average salary taken by machine learning experts lie between $70K to $140K per annum.
You have the flexibility to work on various profiles and earn accordingly.
The machine learning market is growing exponentially worldwide.
Almost every IT industry believe that Ai can make their lives easy.
- Machine learning has various roles and job profiles to obey on the completion of the ML certification course. Let us see a few common job duties that usually remains the same for all profiles.
- Being the trailblazing Machine Learning Training Institute in Delhi, we prepare you to manage all these roles and responsibilities in Machine Learning with the utmost care and confidence.
You should know about all the machine learning concepts in-depth and helps you to understand the roles and responsibilities in machine learning space.
You must know about ML algorithms in detail including designing, development, and their implementation in the workplace.
You must have hands-on expertise in component analysis to design detailed data models using the best ML practices.
You should know about different types of learning in ML and how it can be supported using vector algorithms.
You should know about various machine learning concepts including linear regression, data modelling types, component analysis, vector machines, and more.
You must know how to design an artificial neutral network and logical classification of data using R programming language.
- IBM, Accenture, Deloitte, Facebook, Google, Microsoft, American Express, User, Oracle, etc.
- These are a few top hiring industries in machine learning and you may also get a chance to work with them if you are skilled enough to clear their interviews in the first attempt. The Machine Learning Training in Delhi gives you just the right skills to start your career in one of the top IT industries and bag BIG salary packages too.
- With the most prominent Machine Learning Training Institute in Delhi, you not only become industry-ready but prepare yourself for global certification exam too. Also, work on real-time projects, case studies, or assignment to make yourself highly relevant in the corporate world.
- To get a training certification on the completion of machine learning certification course in Delhi, you need to complete your training successful and submit one project work to the trainer.
- Related Courses to Machine Learning Training in Delhi
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Plenary for Machine Learning with Python Training
| Track | Week Days | Weekends | Fast Track |
|---|---|---|---|
| Course Duration | 40-45 Days | 7 Weekends | 8 Days |
| Hours | 1 Hrs. Per Day | 2 Hrs. Per Day | 6+ Hrs. Per Day |
| Training Mode | Classroom/Online | Classroom/Online | Classroom/Online |
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CURRICULUM & PROJECTS
Machine Learning with Python Training
- 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
- 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
- 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)
- 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.
- 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
- 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
- Techniques of Machine Learning
Supervised Learning
Unsupervised Learning
Semi-supervised and Reinforcement Learning
Bias and variance Trade-off
Representation Learning
- Regression
Regression and its Types
Logistic Regression
Linear Regression
Polynomial Regression
- Classication
Meaning and Types of Classication
Nearest Neighbor Classiers
K-nearest Neighbors
Probability and Bayes Theorem
Support Vector Machines
Naive Bayes
Decision Tree Classier
Random Forest Classier
- Unsupervised Learning: Clustering
About Clustering
Clustering Algorithms
K-means Clustering
Hierarchical Clustering
Distribution Clustering
- Model optimization and Boosting
Ensemble approach
K-fold cross validation
Grid search cross validation
Ada boost and XG Boost
+ More Lessons
Mock Interviews
Projects
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FAQ's
Python brings an exceptional amount of power and versatility to machine-learning environments. The language's simple syntax simplifies data validation and streamlines the scraping, processing, refining, cleaning, arranging and analyzing processes, thereby making collaboration with other programmers less of an obstacle.
Machine Learning is a field of artificial intelligence (AI) that focuses on developing algorithms and models that enable computers to learn from data and make predictions or decisions without being explicitly programmed. Python has gained immense popularity in the machine learning community because of its simplicity, versatility, and rich ecosystem of libraries and tools like TensorFlow, sci-kit-learn, and PyTorch. Python's ease of use, extensive documentation, and active community support make it an ideal programming language.
No, it's not a very complex course as it seems. For candidates belonging to a technical educational background, it will become quite easier for them to learn this combination advancement in fewer days. But for a complete beginner, it might take time, but with adequate guidance, you will end up knowing every detail.
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1. In recent times Python learning is hugely in demand. And I was looking for an institution to get myself enrolled in this course to become a Data Scientist. They have the best trainers and an affordable fee structure. It's been month
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Enrolling yourself in the Deep learning certification program of Croma Campus is the best way to master all the concepts of data science and deep learning. My experience with these people has been very amazing and positive. The support
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Hello, I have joined Croma Campus for a few months in the course helped in acquiring good knowledge. Also, there are many extra classes held by the trainer. There are many mock sessions given after the post completing the course. The s
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