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Artificial Intelligence Course in Chennai

82,124 Ratings

Become a certified AI engineer with Artificial Intelligence Course in Chennai in 7 months

  • Artificial Intelligence Training in Chennai by IITM Pravartak ( An Innovation Hub of IIT Madras)
  • Learn AI Course in Chennai from eminent IIT Madras Faculty and Industry Experts
  • Master CNN, Neural Networks, Machine Learning, perceptron, TensorFlow, etc. via hands-on projects and case studies.
  • 2 Days Campus Immersion at IIT Madras Research Park
  • 3 Guaranteed Interviews upon movement to the Placement Pool

Ranked #1 Artificial Intelligence Course by India TV

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Key Highlights

50+ Live sessions across 7 months
218 Hrs Self-paced Videos
200 Hrs Project & Exercises
Learn from IIT Madras Faculty and Industry Practitioners
1:1 with Industry Mentors
Resume Preparation and LinkedIn Profile Review
24*7 Support
No-cost EMI Option
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Artificial Intelligence Training Overview

What is the learning outcome of this artificial intelligence training in Chennai?

In this artificial intelligence certification course in Chennai, you will learn about the following:

  • Data analysis, project life cycle, and Data Science in the real world
  • Python with Data Science.
  • Data Science projects, analytics, and recommender systems.
  • Natural Language Processing (NLP) and its applications.
  • Techniques of evaluation, experimentation, and project deployment.
  • Data visualization with Tableau.
  • Deploying machine learning models on clouds ( MLOps).
  • Git, Storytelling.
  • Data Science at scale with PySpark, AI with TensorFlow.
  • Machine learning algorithms.
  • Analysis segmentation using clustering and the technique of prediction.
  • Microsoft Excel for data analysis and data transformation.

The following professionals can join this artificial intelligence course in Chennai:

  • Software engineers working on AI projects
  • Computer science engineers looking for a career transition
  • Professionals working as data analysts, data scientists, and ML engineers
  • Freshers looking for a lucrative artificial intelligence career

This best artificial intelligence course in Chennai can be taken up by everyone who is looking for opportunities in the field of artificial intelligence.

According to various job posting websites such as Naukri.com, Indeed, Freshersworld, and LinkedIn, there are 1,500+ jobs vacant for artificial intelligence Engineers in Madras. This shows the wide scope of opportunities in artificial intelligence in this city. Also, the salary provided to AI professionals is higher than the salary offered to other job profiles in the industry. According to Forbes, the average salary of an AI Engineer in the United States is US$135,250 and, in India, it is ₹925,500. This makes it one of the best career choices. Thus, pursuing an artificial intelligence online course will help you excel in your career.

There is a huge market for artificial intelligence all over the world. According to Fortune Business Insights, by 2026, the market for artificial intelligence will reach US$202.57 billion with a compound annual growth rate of 33.1 percent. This will result in the creation of numerous jobs with high packages in the field of artificial intelligence. Those who are AI professionals will get a great benefit. Therefore, enroll in artificial intelligence courses in Chennai to get a head start in AI to land your first job as an AI Engineer.

Among the latest technological advancements, artificial intelligence stands foremost. Deep learning and machine learning startups are blooming and their valuations are increasing more than ever due to increased demand for their solutions. Intellipaat is well familiar with this trend and is poised to teach popular courses with live online videos on the importance of such technologies to young budding professionals looking to enhance their careers.
Further, the following are a few reasons why you must take up the AI course in Chennai:

  • LinkedIn has over 6,000 job opportunities available for you in the field of AI in India
  • The average salary of AI professionals in India is about ₹1,500,641 per annum – PayScale
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Artificial Intelligence would be the ultimate version of Google - Larry Page
The global Artificial Intelligence market size is expected to grow at a compound annual growth rate (CAGR) of 42.2% from 2020 to 2027 - Grand View Research

Career Transition

57% Average Salary Hike

$1,14,000 Highest Salary

12000+ Career Transitions

300+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Meet the Artificial Intelligence Mentors

Skills Covered

Python

Data Science

Data Analysis

AI

Git

MLOps

Data Wrangling

SQL

Storytelling

Machine Learning

Prediction Algorithms

NLP

PySpark

Model

Data Visualization

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Tools Covered

pyspark python jupyter Scipy numpy pandas matplotlib tensorflow SQL tableau excel git SparkSQL
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AI Course Fees in Chennai

Online Classroom Preferred

  • Everything in Self-Paced Learning, plus
  • 50+ Live sessions across 7 months of Instructor-led Training
  • One to one doubt resolution sessions
  • Attend as many batches as you want for Lifetime
  • Job Assistance
30 Mar

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

20 Apr

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

18 May

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

$1,229 10% OFF Expires in

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  • Enterprise grade learning management system (LMS)
  • 24x7 Support
  • Enterprise grade reporting

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Artificial Intelligence Course Curriculum

Live Course Industry Expert Academic Faculty

Module 1 – Preparatory Session - Linux and Python

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Python 

  • Introduction to Python and IDEs – The basics of the Python programming language, how you can use various IDEs for python development like Jupyter, Pycharm, etc. 
  • Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, file handling, exception handling, etc.
  • Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  • Hands-on Sessions And Assignments for Practice – The culmination of all the above concepts with real-world problem statements for better understanding. 

Linux

  • Introduction to Linux  – Establishing the fundamental knowledge of how Linux works and how you can begin with Linux OS. 
  • Linux Basics – File Handling, data extraction, etc.
  • Hands-on Sessions And Assignments for Practice – Strategically curated problem statements for you to start with Linux. 
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Module 2 – Data Wrangling with SQL

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SQL Basics – 

  • Fundamentals of Structured Query Language
  • SQL Tables, Joins, Variables 

Advanced SQL –  

  • SQL Functions, Subqueries, Rules, Views
  • Nested Queries, string functions, pattern matching
  • Mathematical functions, Date-time functions, etc. 

Deep Dive into User Defined Functions

  • Types of UDFs, Inline table value, multi-statement table. 
  • Stored procedures, rank function, SQL ROLLUP, etc.

SQL Optimization and Performance

  • Record grouping, searching, sorting, etc. 
  • Clustered indexes, common table expressions.

Hands-on exercise: 

Writing comparison data between the past year and the present year with respect to top products, ignoring the redundant/junk data, identifying the meaningful data,  and identifying the demand in the future(using complex subqueries, functions, pattern matching concepts).

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Extract Transform Load

  • Web Scraping, Interacting with APIs

Data Handling with NumPy

  • NumPy Arrays, CRUD Operations, etc.
  • Linear Algebra – Matrix multiplication, CRUD operations, Inverse, Transpose, Rank, Determinant of a matrix, Scalars, Vectors, Matrices.

Data Manipulation Using Pandas

  • Loading the data, data frames, series, CRUD operations, splitting the data, etc.

Data Preprocessing

  • Exploratory Data Analysis, Feature engineering, Feature scaling, Normalization, standardization, etc.
  • Null Value Imputations, Outliers Analysis and Handling, VIF, Bias-variance trade-off, cross-validation techniques, train-test split, etc.

Data Visualization

  • Bar charts, scatter plots, count plots, line plots, pie charts, donut charts, etc. with Python matplotlib.
  • Regression plots, categorical plots, area plots, etc, with Python seaborn.
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Descriptive Statistics – 

  • Measure of central tendency, the measure of spread, five points summary, etc. 

Probability 

  • Probability Distributions, Bayes’ theorem, central limit theorem. 

Inferential Statistics –  

  • Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.
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Introduction to Machine Learning 

  • Supervised, Unsupervised Learning.
  • Introduction to scikit-learn, Keras, etc.

Regression 

  • Introduction classification problems, Identification of a regression problem, dependent and independent variables.
  • How to train the model in a regression problem.
  • How to evaluate the model for a regression problem.
  • How to optimize the efficiency of the regression model.

Classification 

  • Introduction to classification problems, Identification of a classification problem, and dependent and independent variables.
  • How to train the model in a classification problem.
  • How to evaluate the model for a classification problem.
  • How to optimize the efficiency of the classification model.

Clustering 

  • Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables.
  • How to train the model in a clustering problem.
  • How to evaluate the model for a clustering problem.
  • How to optimize the efficiency of the clustering model.
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Supervised Learning 

  • Linear Regression – Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.
  • Logistic Regression – Creating logistic regression models for classification problems – such as if a person is diabetic or not, if there will be rain or not, etc.
  • Decision Tree – Creating decision tree models on classification problems in a tree like format with optimal solutions.
  • Random Forest – Creating random forest models for classification problems in a supervised learning approach.
  • Support Vector Machine – SVM or support vector machines for regression and classification problems.
  • Gradient Descent – Gradient descent algorithm that is an iterative optimization approach to finding the local minimum and maximum of a given function.
  • K-Nearest Neighbors – A simple algorithm that can be used for classification problems.
  • Time Series Forecasting – Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting.

Unsupervised Learning 

  • K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach.
  • Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.
  • Linear Discriminant Analysis –  LDA or linear discriminant analysis to reduce or optimize the dimensions in the multidimensional data.
  • Principal Component Analysis – PCA follows the same approach in handling the multidimensional data.
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  • Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
  • Confusion matrix – To evaluate the true positive/negative, and false positive/negative outcomes in the model.
  • r2, adjusted r2, mean squared error, etc.
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Artificial Intelligence Basics 

  • Introduction to keras API and TensorFlow

Neural Networks

  • Neural networks
  • Multi-layered Neural Networks
  • Artificial Neural Networks 

Deep Learning

  • Introduction to Deep Learning (by Academic Faculty)
  • Deep neural networks
  • Convolutional Neural Networks 
  • Recurrent Neural Networks
  • GPU in deep learning
  • Autoencoders, restricted boltzmann machine 
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The Data Science capstone project focuses on establishing a stronghold of analyzing a problem and coming up with solutions based on insights from the data analysis perspective. The capstone project will help you master the following verticals:

  • Extracting, loading and transforming data into usable format to gather insights.
  • Data manipulation and handling to pre-process the data.
  • Feature engineering and scaling the data for various problem statements.
  • Model selection and model building on various classification, and regression problems using supervised/unsupervised machine learning algorithms.
  • Assessment and monitoring of the model created using the machine learning models.
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Electives:

Power BI Basics

  • Introduction to PowerBI, Use cases and BI Tools, Data Warehousing, Power BI components, Power BI Desktop, workflows and reports, Data Extraction with Power BI.
  • SaaS Connectors, Working with Azure SQL database, Python and R with Power BI
  • Power Query Editor, Advance Editor, Query Dependency Editor, Data Transformations, Shaping and Combining Data,M Query and Hierarchies in Power BI.

DAX 

  • Data Modeling and DAX, Time Intelligence Functions, DAX Advanced Features

Data Visualization with Analytics  

  • Slicers, filters, Drill Down Reports
  • Power BI Query, Q & A and Data Insights
  • Power BI Settings, Administration and Direct Connectivity
  • Embedded Power BI API and Power BI Mobile
  • Power BI Advance and Power BI Premium

Hands-on Exercise:

Creating a dashboard to depict actionable insights in sales data.

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  • Job Search Strategy
  • Resume Building
  • Linkedin Profile Creation
  • Interview Preparation Sessions by Industry Experts
  • Mock Interviews
  • Placement opportunities with 400+ hiring partners upon clearing the Placement Readiness Test.
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Artificial Intelligence Projects and Assignments

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends — the possibilities are endless and our community has something for everyone!

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Hackathons
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collaborative-learning

Career Services

Career Services

Career Oriented Sessions

Throughout the course

Over 10+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions that will help you stay on track with your upskilling.

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & Linkedin Profile from our career services team and learn how to grab the attention of the hiring manager at the profile shortlisting stage

Mock Interview Preparation

After 80% of the course completion.

Students will go through several mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learner’s educational background, past experience, and future career aspirations.

Placement Assistance

Upon movement to the Placement Pool

Placement opportunities are provided once the learner is moved to the placement pool upon clearing the Placement Readiness Test (PRT)

Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Advance Artificial Intelligence Certification in Chennai

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IITM Pravartak has initiated various programs in partnership with NASSCOM. The courses offered by them aim to upskill millions of students and professionals in trending technologies through a blend of theoretical and hands-on knowledge and are taught by leading academicians.

Upon completion of this course, you will:

  • Receive an Advanced Certification in Data Science and AI from IITM Pravartak.
  • Receive live lectures from IIT Madras faculty & Industry Experts

Key achievements of IIT Madras:

  • NIRF Rank 1 for the last 3 years
  • Ranked 50 in Asia by the QS World University Rankings in 2020
  • Ranked 63 in Emerging Economic University Rankings in 2020

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Artificial Intelligence Course in Chennai FAQs

What is Intellipaat’s artificial intelligence online course like?

Our artificial intelligence online training involves the simultaneous participation of both learners and instructors in an online environment. Being a learner, you can log in to our applied AI course sessions from anywhere and attend the class without having to be physically present. Also, we record the proceedings of all AI classes and equip you with them to further enhance your learning process. Upon the completion of this AI training online, your experience will be equivalent to that of a professional who has worked for 6 months in the industry.

Simply put, artificial intelligence is the intelligence that is demonstrated by machines to perform tasks that are otherwise done by humans. This is achieved through machine learning and deep learning.

Deep learning is essentially a subset of machine learning that involves predictive modeling and statistics. It facilitates predictive analytics. Currently, deep learning is widely used in image recognition, NLP, and speech recognition.

You can become an AI Engineer by acquiring all the essential skills that an AI professional should possess. Intellipaat’s artificial intelligence and machine learning courses can help you do exactly that. Enroll in the online training program for mastering the domain comprehensively. After the completion of the course and all of the projects, you will be ready to attempt the certification exam conducted by Intellipaat.

Yes! Before the exam, Intellipaat provides practice tests for the students to familiarize themselves with the exam format and get an idea of the kinds of questions that may be asked.

We have both instructor-led training and self-paced training. It depends on your preference.

Intellipaat provides other technical certification training courses in Chennai such as Machine Learning course, Python, Data Science, Data Analyst, Business Analyst, Selenium, Salesforce, Power BI, Tableau, SQL, Business Analytics, MSBI, etc.

Intellipaat offers Artificial Intelligence Course in Chennai on different locations mentioned below-

Area Postal Code
Adambakkam 600088
Anna Salai 600002
Ambattur 600053
Ashok Nagar 600083
Aminjikarai 600030
Besant Nagar 600090
Choolaimedu 600094
K.K. Nagar 600078
Kodambakkam 600024
Koyambedu 600107
Ekkattuthangal 600032
Kilpauk 600010
Medavakkam 600100
Nandanam 600035
Nungambakkam 600034
Madipakkam 600091
Teynampet 600018
Nanganallur 600061
Navalur 600130
Mylapore 600004
Pallavaram 600043
Purasaiwakkam 600007
Porur 600116
Pallikaranai 600100
Poonamallee 600056
Saidapet 600015
St.Thomas Mount 600016
Sholinganallur 600119
Triplicane 600014
Thoraipakkam 600096
Vadapalani 600026
Valasaravakkam 600087
Villivakkam 600049
West Mambalam 600033
Velachery 600042
Virugambakkam 600092

Intellipaat is offering 24/7 query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail of email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, 1:1 session support is provided for a period of 6 months from the start date of your course.

Intellipaat provides placement assistance to all learners who have successfully completed the training and moved to the placement pool after clearing the PRT( Placement Readiness Test) More than 500+ top MNC’s and startups hire Intellipaat learners. Our Alumni works with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.

Apparently, no. Our job assistance is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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