Indian Cyber Security Solutions | A unit of Green Fellow IT Security Solutions Pvt Ltd | Member of NASSCOM, DSCI, ICC | ATC of EC- Council

Toll-Free - 1800-123-500014  

Call Us at: +91 8972107846 | 6291980077

Diploma in Machine Learning and AI in India D|ML & AI Course

Diploma in Machine Learning and AI in India from Indian Cyber Security Solutions is the most demanded training in India as well as across globe. Machine Learning is a very important and inevitable part of knowledge in today’s World. Diploma in Machine Learning by ICSS will help you to lead the AI-driven technological revolution.



Objective of Machine learning training in India course is to impart in depth knowledge in Machine Learning & Artificial Intelligence and its applications using tools. Get trained by industry experts of data science. More than 200+ students got placed in a different place from ICSS. By leveraging Diploma in Machine Learning and AI for Industry you will be exposed to numerous high-paying job opportunities. Indian Cyber Security Solutions as a renowned industry in the country is thus providing the best Diploma in machine learning online Training.

Diploma in Machine Learning and AI in India

Machine learning, reorganized as a separate field, started to flourish in the 1990s. The field changed its goal from achieving artificial intelligence to tackling solvable problems of a practical nature. It shifted focus away from the symbolic approaches it had inherited from AI, and toward methods and models borrowed from statistics and probability theory. As of 2019, many sources continue to assert that machine learning remains a subfield of Artificial Intelligence.

Rating

4.8 ( 21,123 ratings )

1,09,233 Students Enrolled

D|ML & AI – Diploma in Machine Learning and AI

Machine learning is closely related to computational statistics. Its applications across business problems, machine learning is also referred to as predictive analytics. As a scientific endeavor, machine learning grew out of the quest for artificial intelligence. The job market for machine learning specialists is expected to grow 56% over the next few years, with a significant concentration of the jobs found in the Greater Toronto Area. This is the right time to grow your knowledge in the field of Machine Learning & Artificial Intelligence. Join Indian Cyber Security Solutions for Diploma in Machine Learning and AI in India course and get deep knowledge from professional Data Scientist. You can work with both structured and unstructured data with various supervised, unsupervised and reinforcement learning algorithms after completion of the course. Our Diploma in Machine Learning and AI in India course will help to reach your career goals.

Class Room Training on Diploma in Machine Learning and AI in India

Diploma in Machine Learning and AI in India with hands-on training in the lab from the professional Data Scientist. Data Science & Machine Learning training is in huge demand as organizations are going online with more than 170 Billion Doller investment in the Machine Learning & Artificial Intelligence domain worldwide. At Indian Cyber Security Solutions, you will learn in-depth on Machine Learning & Data Science & learn to create AI tool by using machine learning from our experts. Machine Learning training is designed is such a way that you get the maximum practical knowledge. At our training center, we bring in guest faculties from the industry so they can share their practical experience with you. At the end of the course, we aim to make your placement ready.

Online LIVE Training on PG Diploma in Machine Learning and AI in India

Indian Cyber Security Solutions have 130+ trainers who are professional Data Scientist working in different MNCs like Infosys, Cognizant, Wipro, ATOS, Intel and are also members of our research & development team. All the trainers are geographically located in different areas provide online training on Machine Learning. All the machine learning training classes are held through an application where the faculty and the students are LIVE interacting with each other over the internet. We provide online Live Training on Machine Learning. Most importantly, all the classes are recorded and uploaded in our online portal where all students have lifetime access. We guarantee your satisfaction or we pay back your course fee. There will be 3 instructors dedicated for individual batch which will carry on for 3 months.

Eligibility Criteria to become a Professional Data Scientist & Machine Learning Engineer

The prime objective of this course is to make you ready for the industry where you can use your skills. After completion of this course, you will be able to successfully create AI tools by using machine learning. Any graduate with knowledge of basic programming languages can apply for this course.

Technical Educational Background

You need to be from engineering / science/ Maths / Stats background to understand the theory and the techniques used in machine learning. Prior programming experience would be very useful. Machine Learning is all about Stats and Probability. So, having a prior knowledge in that area would come very handy. it will be necessary for you to learn how to program in a programming language such as Python. You will get python programming course in this course bundle.

Non-Technical Educational Background

You can get into data science & machine learning from a non-technical background. Machine learning makes use of a lot of programming and mathematics. However, even if you are not a technical person, it will be possible for you to learn machine learning if you follow the right path.

UNIVERSITY TRAINING PARTNER'S

UNIVERSITY TRAINING PARTNER'S

thin

Learn from Industry Experts & Get Real Hands-On Experience and get job ready

100% Placement Support After completion of the Diploma in Machine Learning and AI

Practice on Real Time Projects which can be showcased to future recruiters

Learn from industry experts who have over 12+ Years Industry Experience

Average Salary is $120,000 in the field of Machine Learning & AI

Demand for Machine Learning & AI will increase to 80% by 2022

Top Companies Hiring: Google, Facebook, Amazon, Apple, Uber & Many More.

Become a Master in Machine Learning & AI

Diploma in Machine Learning and AI Curriculum

1500+ Professionals Trained with 4.8/5 Rating

Get Started with FREE Demo Class:

* We don’t share your personal info with anyone.  Check out our Privacy Policy for more info.

Why You Should Choose ICSS ?

Industry professions from Amazon, Cognizant & Intel will share their practical experience in the class

100% practical and lab-based classes (available online & offline)

25% Scholarship program for merited students with a minimum of 90% marks in their board exams

LIFETIME access to video tutorials, case studies

EMI option is available if you go for 2 or more courses.

Get educational loan @  O% interest

TRAINING METHODOLOGY of ICSS

THEORY

PRACTICALS

ASSIGNMENT

CERTIFICATION

RESUME PREPARATION

ATTEND INTERVIEW

With our full Training Methodology you will get job

JOB ORIENTED ETHICAL HACKING COURSE DETAILS

100% Job Placement Assistance

  • Career Guide: Job Opportunities will be shared with you
  • Be JOB Ready Resume prepared by Experts
  • Questions & Answers provided for interviews
  • Mock Exams you will write to test your skills
  • Mock Interviews to boost your confidence
  • Pre-Requisite: Any one can learn Ethical Hacking and Get Job
  • Projects: Work on Real Life Case Studies

Course Duration

We Provide:

  • 9 Months Classes
  • Fast Track Classes
  • Weekdays & Weekend Classes
  • Projects to do assignments
  • Location: Courses are run in our Kolkata training center (Salt Lake, Sector 5) & Bangalore (Indiranagar)
  • Corporate Training for your Employees
  • Online Ethical Hacking Courses - Live Instructor LED Classes
  • Pay only after attending FREE DEMO CLASS

True Reviews by Real Students

4.8/5 Ratings

FEW STUDENT'S REVIEWS

C|PP - CERTIFIED PYTHON PROGRAMMER (Basic)


  • Module 1: Introduction of Python
  • Module 2: Installation of Python
  • Module 3: Basics of Python
  • Module 4: Python Strings
  • Module 5: Python Lists
  • Module 6: Python Tuples
  • Module 7: Python Dictionary
  • Module 8: Python Set
  • Module 9: Python Control Statement
  • Module 10: Python Functions
  • Module 11: Python Files I / O
  • Module 12: File Handling
  • Module 13: Python OOPS Concept
  • Module 14: Python Modules 
  • Module 15: Python Exceptions
  • Module 16: Python Date
  • Module 17: Python Network Programming
Module 1: Introduction of Python
  • What is Python
  • Python History
  • Python 2.x vs 3.x
  • Features of Python
  • About Python Versions
  • Applications of Python
Module 2: Installation of Python
  • How to install python
  • Python Script Mode
  • Python GUI Mode
  • Python Interactive Mode
  • Python in Linux
  • Linux Script Mode
  • Linux GUI Mode
  • How to install IDLE in Linux
  • How to set path
Module 3: Basics of Python
  • Python “Hello World”
  • How to Execute Python
  • Variables in python
  • Keywords in python
  • Identifiers in python
  • Literals in python
  • Operators in python
  • Comments in python
Module 4: Python Strings
  • Accessing Strings
  • Strings Operators
  • Basic Operators
  • Membership Operators
  • Relational Operators
  • Slice Notation
  • String Functions and Methods
Module 5: Python Lists
  • How to define list
  • Accessing list
  • Elements in a Lists
  • List Operations
  • Adding Lists
  • List slicing
  • Updating elements in a List
  • Appending elements to a List
  • Deleting Elements from a List
  • Functions and Methods of Lists
Module 6: Python Tuples
  • How to define a tuple
  • Accessing tuple
  • Elements in a tuple
  • Tuple Operations
  • Tuple slicing
  • Deleting tuple
  • Functions and Methods of tuple
Module 7: Python Dictionary
  • How to define dictionary
  • Accessing Dictionary
  • Updation
  • Deletion
  • Functions and Methods
Module 8: Python Set
  • How to define Set
  • Accessing Set
  • Set Built-in Functions
  • Set Operations
Module 9: Python Control Statement
  • “If” in python
  • “If else” in python
  • “else if” in python
  • “nested if” in python
  • “for loop” in python
  • “while loop” in python
  • “break” in python
  • “continue” in python
  • “pass” in python
Module 10: Python Functions
  • Defining a Function
  • Invoking a Function
  • return Statement
  • 66 Argument and Parameter
  • Passing Parameters
  • Default Arguments
  • Keyword Arguments
  • Anonymous Function
  • Difference between Normal Functions and Anonymous Function
  • Scope of Variable
Module 11: Python Files I / O
  • “print” statement
  • Input from Keyboard
Module 12: File Handling
  • Operations on Files
  • Opening file
  • closing file
  • reading file
  • writing file
  • Modes of files
  • Methods in files
Module 13: Python OOPS Concept
  • Python OOPs Concepts
  • Python Object Class
  • Python Constructors
  • Python Inheritance
  • Multilevel Inheritance
  • Multiple Inheritance
Module 14: Python Modules 
  • Importing a Module
  • Example of importing multiple modules
  • How to use “from” import statement
  • import whole module
  • Built-in Modules in Python
  • Package
Module 15: Python Exceptions
  • What is Exception handling
  • Declaring Multiple Exception
  • Finally Block
  • Raise an Exception
  • Custom Exception
Module 16: Python Date
  • Retrieve Time
  • Formatted Time
  • time module
  • Calendar
  • Calendar module
Module 17: Python Network Programming
  • Basics of networking
  • What is the socket?
  • How to make socket?
  • socket methods
  • creating server
  • creating client
  • creating echo server
  • Python Internet modules
  • Port scanner in python
  • Creating Web server

C|MLP - Course Module


  • Module 1: Features of Python
  • Module 2: Data Structures
  • Module 3: Concept of Modules
  • Module 4: OOPS Concept
  • Module 5:
  • Exam on Python
  • Module 6: Numpy
  • Module 7: Basic of Pandas
  • Module 8: Data Visualization with Matplotlib & Seaborn
  • Module 9: Supervised Learning 1
  • Module 10: Machine Learning vs Statistical Modelling
  • Module 11: Unsupervised Learning
  • Module 12: Logistic Regression Algorithm
  • Module 13: Practice Linear & Logistic Regression with Different Dataset
  • Module 14: K Means & Hierarchical Clustering Algorithm 
  • Module 15: PCA & Decision Tree Algorithm
  • Module 16: Random Forest Algorithm
  • Module 17: K-Nearest Neighbor Algorithm
  • Module 18: Support Vector Machine & Natural Language Processing with Naive Bayes
  • Doubt Clear Session
  • Final Project with Documentation
Module 1: Features of Python

Using the Python Interpreter

  • Invoking the Interpreter
  • The Interpreter and Its Environment

Introduction to Anaconda

  • Anaconda Navigator
  • Anaconda Prompt
  • Python Console
  • Jupyter qt-console
  • Jupyter Notebook
  • Spyder

An Informal Introduction to Python

  • Using Python as a Calculator
  • First Steps Towards Programming

Installation to Anaconda and Control Flow Tools

  • if Statements
  • for Statements
  • The range() Function
  • break and continue Statements, and else Clauses on Loops
  • pass Statements
  • Defining Functions
  • More on Defining Function
  • Function special attributes
  • Coding Style
Module 2: Data Structures
  • Lists
  • The del statement
  • Tuples and Sequences
  • Sets
  • Dictionaries
  • Looping Techniques
  • More on Conditions
Module 3: Concept of Modules
  • Standard Modules
  • The dir() Function
  • Packages Input and Output Reading and Writing Files
Module 4: OOPS Concept
  • Object: properties and operations
  • Class as a blueprint for objects
  • Fields: Python convention for defining private fields
  • Constructors: overloading and chaining
  • Designing static properties, operations, and blocks in Python
  • Special method names in a class and their uses (e.g. __new__, __del__, __str__ etc.)
  • Single and multiple inheritances
  • Method overriding and polymorphism
  • Iterators
  • Errors and Exceptions
  • Syntax Errors
  • Exceptions
  • Handling Exceptions
  • Raising Exceptions

Input & Output

  • Fancier Output Formatting
  • Reading and Writing Files
Module 5:
  • Single and multiple inheritances
  • Method overriding and polymorphism
  • Iterators
  • Generators
  • Generator Expressions
  • Errors and Exceptions
  • Syntax Errors
  • Exceptions
  • Handling Exceptions
  • Raising Exceptions
  • User-defined Exceptions
  • Defining Clean-up Actions
  • Predefined Clean-up Actions
Exam on Python
Module 6: Numpy
  • An example
  • Array Creation
  • Printing Arrays
  • Basic Operations
  • Universal Functions
  • Indexing, Slicing, and Iterating

Shape Manipulation

  • Changing the shape of an array
  • Stacking together different arrays
  • Splitting one array into several smaller ones

Copies and Views

  • No Copy at All
  • View or Shallow Copy
  • Deep Copy
  • Functions and Methods Overview

Broadcasting rules Fancy indexing and index tricks

  • Indexing with Arrays of Indices
  • Indexing with Boolean Arrays
  • The ix_() function
  • Indexing with strings

Linear Algebra

  • Simple Array Operations

Tricks and Tips

  • “Automatic” Reshaping
  • Vector Stacking
  • Histograms
Module 7: Basic of Pandas

Introduction to Pandas Data Structures

  • Series
  • DataFrame
  • Index Objects Reindexing
  • Dropping entries from an axis
  • Indexing, selection, and filtering
  • Arithmetic and data alignment
  • Function application and mapping
  • Sorting and ranking
  • Axis indexes and duplicate values Filtering out missing Data
  • Filling out missing Data

Essential Functionality

  • Reindexing
  • Dropping entries from an axis
  • Indexing, selection and filtering
  • Arithmetic and data alignment
  • Function application and mapping
  • Sorting and rankin
  • Axis indexes and duplicate values

Summarizing and Computing descriptive statistics

  • Correlation and Covariance
  • Unique values, Value Counts and Membership

Handling missing data

  • Filtering out missing Data
  • Filling out missing Data

Hierarchical Indexing

  • Reordering and sorting levels
  • Summary statistics by level
  • Using a data frame's column

Other Pandas topics

  • Integer indexing
  • Panel Data
Module 8: Data Visualization with Matplotlib & Seaborn
Module 9: Supervised Learning 1
  • K-Nearest Neighbours
  • Decision Trees
  • Random Forests
  • Reliability of Random Forests
  • Advantages & Disadvantages of Decision Trees
  • Project-1 on data analysis with documentation
Module 10: Machine Learning vs Statistical Modelling
  • Machine Learning Languages, Types, and Examples
  • Machine Learning vs Statistical Modelling
  • Supervised vs Unsupervised Learning
  • Supervised Learning Classification
  • Unsupervised Learning

Supervised Learning II

  • Regression Algorithm (Linear, Multiple, Polynomial)
  • Model Evaluation
  • Model Evaluation: Overfitting & Underfitting
  • Understanding Different Evaluation Models
Module 11: Unsupervised Learning
  • K-Means Clustering plus Advantages & Disadvantages
Module 12: Logistic Regression Algorithm
Module 13: Practice Linear & Logistic Regression with Different Dataset
Module 14: K Means & Hierarchical Clustering Algorithm 
Module 15: PCA & Decision Tree Algorithm
Module 16: Random Forest Algorithm
Module 17: K-Nearest Neighbor Algorithm
Module 18: Support Vector Machine & Natural Language Processing with Naive Bayes
Doubt Clear Session
Final Project with Documentation

Class Room Training

Students Enrolled83%

Course Fee

INR 40,000 / – + 18% GST

Course Duration

9 Months

2 Classes Per Week X 2 Hours Each Day

Batch Timing

Week End Classes | Week Days Classes

Online Self Paced LIVE Training

Students Enrolled92%

Course Fee

INR 40,000 / – + 18% GST

Course Duration

9 Months

2 Classes Per Week X 2 Hours Each Day

Batch Timing

Week End Classes | Week Days Classes

Our Hiring Partners for Placements

Still Hunting for a Job? or Want to Make a Career Switch into Machine Learning & AI ?

Recruiters are looking for you!

All you need to Learn Basic to Advance of Machine Learning with ICSS, Become Certified Professional and Get JOB with our Free Placement Assistance Program

Machine learning training in India by ICSS – Get trained from Data Scientist

Machine learning training in India course by ICSS will provide the skills you need to become a Machine Learning Engineer and unlock the power of this emerging field. It involves computers learning from data provided so that they carry out certain tasks. For simple tasks assigned to computers, it is possible to program algorithms telling the machine how to execute all steps required to solve the problem at hand, on the computer’s part, no learning is needed. For more advanced tasks, it can be challenging for a human to manually create the needed algorithms. Machine learning training in India and PG Diploma in Machine Learning and AI in India course can turn out to be more effective to help the machine develop its own algorithm. The Machine Learning market is expected to reach USD $8.81 Billion by 2022, So it’s a great opportunity to grow your career in this field.

Machine learning training in India course is easily approachable by keen students those who have craving for Machine Learning and Artificial Intelligence. This course will equip you with the basic machine learning and AI tools for mining and analyzing datasets, and extracting insights for decision making. You will learn from our data scientist how to identify correlations and patterns in datasets, build predictive models using machine learning and AI software. You will emerge with the hands-on skills you need to apply AI in your enterprise, and enhance your career in the field.

Need to Work on real-time projects and complete assignments to get Professional Certification from Indian Cyber Security Solutions

ICSS provides the course completion certificate once you successfully complete the Certified Ethical Hacking training program Professional Certificate Holders work at 1000s of companies like HP, TCS, Amazon, Accenture and many more.

REGISTRATION DESK

Machine learning training in India

Current Job Openings

Check job profile, salary scale of current jobs available in market

Cyber Security Professional | Cyber Security Engineer | Pen-Tester

Information Security Analyst | Security Consultant


Conducted Machine Learning Training Session

Some Glimpses of our Workshop

Diploma in Machine Learning and AI for Industry and workshops conducted by ICSS Educational Division

Diploma in Machine Learning and AI for Industry will expand your knowledge of neural networks-based Artificial Intelligence & Machine Learning in this course. ICSS had been fortunate enough to have been associated with some of the renounced educational institutions like IIT Kharagpur, NIT Durgapur, Jadavpur University, Lovely Professional University and JIS collage to name a few. Our campus representatives are highly active and conduct interactive sessions. Considering the major approaches in Diploma in Machine Learning and AI for Industry, the country is developing rapidly. Our training module is delicately balanced between practical lab based training and theoretical content. Learn the newest AI & Machine Learning applications and opportunities from top industry experts in the course of PG Diploma in Machine Learning and AI in India. Increasingly challenging exercises will help you to build AI tool that can learn to classify images, perform rudimentary language translation etc.

By studying this degree you will:

Have the option to study one of the specialist pathways in Artificial Intelligence or Financial Technology

Address skills required by data scientists to drive improvements in organisational performance

Have the opportunity to create your own data analysis projects

Diploma in Machine Learning Course in India and workshops conducted by ICSS Educational Division

Diploma in Machine Learning Course in India and workshops are conducted across all collages. ICSS had been fortunate enough to have been associated with some of the renounced educational institutions like IIT Kharagpur, NIT Durgapur, Jadavpur University, Lovely Professional University and JIS collage to name a few. Our campus representatives are highly active and conduct interactive sessions on cyber security. Campus representatives are student’s representatives from different collages those who are responsible for establishing a research lab on cyber security inside the campus of the respective collages. These research facilities & interactive sessions on ethical hacking helps the students to gain latest knowledge in cyber security. Indian Cyber Security Solutions offers Diploma in Machine Learning Course in India for corporate teams and individuals.

Do you want to be a Campus Representative?

If you want to be a CR there is a long list of benefits that you will be entitled too.