3 Reasons why Professionals Prefer this Program

Top Faculty

  • trangleTaught by Top Research Professors at IIIT Hyderabad,
    Asia’s Top Ranked Research Institution in AI and Robotics
  • quotes-iconThe faculty helped me understand the subtle nuances of working with AI.
    Jaya Srivastava
    Research PM, Microsoft

Outstanding Peer-group

  • trangle7 Year Avg. Experience
  • trangle40% Leaders and Managers 60% Developers, Analysts
  • trangle30% from Startups and Mid size companies
  • quotes-iconIt is about the peer collaboration & networking that this Program brings to the table.
    Krishna Chilamkurthy

High Impact Format

  • trangleCohort Based
  • trangleLive Interactive Lectures
  • trangleMentored Labs
  • trangleProjects, Hackathons
  • trangleCampus Visit *
  • quotes-iconThe Program is structured in a way that even a beginner can easily understand complex AI concepts.
    Kandula Andula Lakshmi Chaya

Outstanding Peer Group
You learn with Outstanding Professionals

Working with Global Organizations

Participant organisation Participant organisation

Brand logos of organizations of program participants. All logos belong to the respective brand owners.

Career Transformation Stories
Invest in yourself. Expand your knowledge. Build a stronger career.


High Impact Format
Program Designed and Perfected for Working Professionals

Creating Phenomenal Journeys

Kumar Paritosh
Vasanth Raj

Top Faculty
Meet the Faculty, Redefining AI Research in India

C. V. Jawahar

C. V. Jawahar
Professor, IIIT Hyderabad

C. V. Jawahar received his Ph.D. from Indian Institute of Technology Kharagpur. He is the Machine Learning Lab Head, Dean (RnD) and Amazon Chair Professor at IIIT Hyderabad. He is a renowned expert in Machine Learning and Optimization, Document Image Analysis, and Computer Vision.

Anoop Namboodiri

Anoop Namboodiri
Associate Professor, IIIT Hyderabad

Anoop Namboodiri received his Ph.D. in Computer Science from Michigan State University, USA. He is associated with the Centre for Visual Information Technology. His research interests include Pattern Recognition, Biometrics, Document Understanding, and Computer Vision

Ravi Kiran

Ravi Kiran
Assistant Professor, IIIT Hyderabad

Ravi Kiran received his Ph.D. from the Department of Computational and Data Sciences, Indian Institute of Science, Bangalore. His research areas include Computer Vision, Machine Learning, Virtual Reality, Robotics, Affective Computing, Document Analysis and Multimedia.

Vineet Gandhi

Vineet Gandhi
Assistant Professor, IIIT Hyderabad

Vineet Gandhi received his Ph.D. in Applied Mathematics and Computer Science from INRIA Rhone Alpes/University of Grenoble. His research areas include Computer vision and multimedia, human detection and tracking, computational photography and cinematography, depth reconstruction and applications.


Asokan Pichai
Chief Learning Officer, TalentSprint

Asokan holds a PG Diploma in Computer Programming. He is an Industry Instructor, Instructional Designer, and Programming Guru, with a software development experience of over 35 years. His subject-matter expertise includes Programming languages - COBOL, Clipper, C, C++, Python, Haskell, Elixir, Clojure, Java and Ruby.

Mohammed Habeebvulla

Dr. Mohammed Habeebvulla
Director of Delivery - Executive Programs at TalentSprint

Dr. Habeebvulla received his Ph.D. in Computer Science from Calorx University. Habeebvulla has worked in diverse roles in the software development cycle as Developer and Technical Lead. His areas of expertise include AI/ML, Data Science, OCR, Computer Vision and Design Patterns.

Manish Gupta

Manish Gupta
Principal Applied Scientist at Microsoft Adjunct Faculty, IIIT Hyderabad

Manish received his Ph.D. from the University of Illinois. His area of interest includes Big Data Analytics, Algorithms, Deep Learning, Data Mining, Information Retrieval and Web Mining, Databases, Text Mining, Machine Learning, Time Series Analysis, Graph Mining, Natural Language Processing, Optimization.

Manish Shrivastava

Manish Shrivastava
Assistant Professor, IIIT Hyderabad

Manish received his Ph.D. from IIT, Bombay. His areas of interest include Natural Language Processing, ML, Machine Translation, NLP for Indian Languages. His publications include ‘Experiences in Constructing a POS Tagger for Hindi’, ‘Hierarchical Phrase Based Machine Translation Systems for Five Indian Languages’ and more.

Anil Vuppala

Anil Vuppala
Associate Professor, IIIT Hyderabad

Anil received his Ph.D. from IIT, Kharagpur. His areas of interest include Speech Recognition, Speaker Recognition, Language Identification, Speech Processing in Emotional Conditions, Pathological Speech Processing and Speech to Speech Machine Translation.

Praveen Paruchuri

Praveen Paruchuri
Associate Professor, IIIT Hyderabad

Praveen received his Ph.D. from the University of Southern California. His areas of interest include Artificial Intelligence, Multi-agent Systems, and Game Theory, Linear/Integer Programming and Applied Machine Learning.

A Glimpse of the Research Impact of IIITH Faculty

  • AI Chatbot
  • AI Powered Biometrics
  • compurt-vision

Curriculum for Practitioners

  • Basics of Python
  • Data Types and Data Structures
  • Defining and Calling Functions
  • Python Library Packages

  • Vectors
  • Norms
  • Matrices
  • Matrix Operations
  • Linear Dependence and Independence
  • Linear Transformations
  • Least Square Error
  • Derivatives
  • Chain Rule
  • Integration
  • Gradients

  • Continuous and Discrete Random Variables
  • Mutually Exclusive/Non-exclusive Events
  • Independent and Dependent Events
  • Probability Distribution Functions
  • Cumulative Distribution Functions
  • Measures of Centre and Spread
  • Normalization and Standardization

  • Basic understanding of Algorithm Design Paradigms, Python Classes, Objects, Methods

  • Numpy
  • Scipy
  • Pandas
  • Matplotlib

  • Demystifying ML
  • Modern AI

  • Supervised vs Unsupervised Learning
  • Classification vs Regression
  • Training and Testing Methods
  • ML Pipeline

  • Data Munging
  • Outlier Detection
  • Hands-on Data Visualization

  • Feature Selection Methods
  • Feature Extraction Methods

  • k-NN Classification
  • Decision Tree
  • Linear Classifier

  • Linear Regression
  • Polynomial Regression
  • Logistic Regression

  • Basic Mathematics and Hands-on Analysis

  • Understanding standard NLP Libraries
  • Exploring Different Representations Methods

  • Bootstrapping
  • Bagging

  • Literacy Rate Prediction
  • Aptitude Questions Classification

  • NLP Problem Formulation and Fundamental Solutions

  • Exploring Word Embeddings

  • Methods to Measure the Efficacy of the ML models

  • Single Layer Perceptron
  • Basic Mathematics
  • Practical Tricks and Tips

  • Activation Functions
  • MLP Architecture

  • PCA Algorithm
  • Underlying Mathematics
  • Applications of PCA

  • SVM Formulation
  • Non-linear Mapping
  • Popular Kernels

  • Non-Linear Dimensionality Reduction for visualization
  • Hierarchical Agglomerative Clustering
  • K-means clustering

  • Classical and Modern Feature Representation for Visual Data
  • Classical and Modern Feature Representation for Audio/Speech

  • Author Identification
  • Customer Segmentation

  • Deep Learning Framework
  • Neural Network Module
  • Training a Neural Network

  • Basics of Pytorch
  • Pytorch Packages
  • Computation on GPU
  • Model Building
  • Model Training and Evaluation

  • Convolutional Layers and Backpropagation
  • Building Blocks for Convolutional Networks
  • Applications of CNN - Audio, Text and Image

  • Intro to Autoencoders
  • Deep Autoencoder
  • De-noising Autoencoder

  • Recurrent Neural Network Architecture
  • Machine Learning with Sequential Data
  • Neural Network Language Models

  • Intro to Keras and Keras Basics
  • Keras Models
    - Sequential Model
    - The Functional API
    - Model Subclassing
  • Sequential ,odel Steps and it's Parameters and Adding Layers
  • Building a Network in Keras
  • Loading and Save the Models with Example and Measuring the Performance

  • ETL
  • Dimensional Data Modelling
  • Big Data Query

  • Memorization and Generalization
  • Occam’s Razor
  • Ways to Prevent/Reduce Overfitting

  • Classical Models (AR, MA, ARMA & ARIMA)
  • Neural Networks for Time Series Forecasting

  • Random Forest
  • Boosting and Adaboost

  • Different Roles for Human in the Loop
  • Users in the ML Systems
  • Relevance Feedback
  • Active Learning

  • Image Classification
  • Identification of plant disease from leaf images

  • Visualizing CNNs
  • Improving CNNs
  • Popular CNN Architectures

  • Vanishing Gradients
  • Understanding Recurrent Architectures

  • Introduction to Recommendation Systems
  • Social Recommender Systems
  • Collaborative Filtering
  • Hybrid Recommendation Models

  • Adapting Pre-trained Models for Desired Applications

Machine Learning Deployment using

  • Docker
  • HTML
  • Java Script
  • Joblib and Pickle

  • Technical and Non-technical Pratical Issues in ML

  • Model Compression
  • Pruning
  • Quantization
  • Student-teacher Network

  • Reinforcement Learning Framework
  • Single and Multi agent RL
  • Q-Learning
  • Deep RL
  • RL Applications

  • Siamese Architecture
  • Generative Adversarial Networks

  • Introduction to Computer Vision
  • Camera Model and Geometry
  • Problems in Computer Vision
  • Applications and Use Cases


  • Sequence Generation and Information Extraction
  • Latest Text Embedding Models
  • Neural Machine Translation
  • Attention Mechanism for DL

ML in Speech

  • DNN based Speech Applications
  • DNN with Attention
  • Sequential Network
  • Encoder Decoder Models for Speech Recognition
  • Automatic Speech Recognition

  • Talks from different domain experienced people

  • Retail sales forecasting
  • Image processing and Transfer Learning

  • AI Chatbot


  • Voice-based Product

    Voice-based Product
    Ordering System

  • Anti Face

    Anti Face

  • Fraud Detection


Languages and Tools


Hands-on Projects - 3 Months

Required to complete PG Certification - 9 Months. Option to opt out of Hands-on Projects with Advanced Certification.
  • Automatic Image
  • Classifying Multi-page
  • Text Classification using
    Enron Email Dataset
  • Image Tagging and Road
    Object Detection

Industry Data Sets

  • Monie.io
  • Twenty Newsgroups
  • Clara
  • GloVe
  • Credit Card
  • Movie Rating
  • Wisconsin Breast Cancer
  • Cifar
  • Swiss Roll
  • Aptitude Classification
  • Human Brain Weight and Head Size
  • Bank Notes
  • Alphabet Recognition
  • Air Passengers
  • PM2.5 Data
  • Cats and Dogs
  • Expressions
  • Face Recognition
  • Ants and Bees
  • Fingerprint

Immersive Learning for Experienced Professionals

  • 120 Hours of
    LIVE Classes
  • 250 Hours of
    Lab Sessions
  • 144 Hours of
    Hands-on Projects
  • 2 Hours / Day*
    Expected Commitment
  • Weekend
  • 2 Campus
  • 4 Hackathons
  • 40+ Tools
  • 35+ Data Sets

*Campus visit dates will be decided keeping the safety of participants in mind.

Find out more

IIIT-H Campus
program ideal

Who is the Program ideal for?

Professionals keen to develop AI expertise, with the objective of

  • Enhancing effectiveness in their current role
  • Transitioning to AI roles in their organization
  • Seeking to advance their career in the industry
  • Giving shape to entrepreneurial aspirations


Tech Professionals with at least 1 year work experience
and coding background


Fee with Flexible Payment Options

PG Certification Program in AI/ML With Hands-on Projects

Advanced Certification Program in AI/ML Without Hands-on Projects

Application fee of ₹2,000 + GST
Fees paid are non-refundable and non-transferable.

Nominate your Employee to Avail Special Benefits

Top AI-based Tech Roles

AI AI Skill

Exclusive Interaction with Industry
Leaders in DeepTech

DeepTalk is an interactive series by TalentSprint on DeepTech, hosted by Dr. Santanu Paul, where leaders share their unique perspectives with our community of professionals.

In this DeepTalk event, Dr. Manish Gupta, a Google AI veteran throws light on how and why some basic frontiers in India can be augmented with technology, covering exciting aspects about leveraging AI’s power in real-life applications.

AI for India

Your AIML Journey

  • PG Certification Program in AI/ML AIML certificate
  • Advanced Certification Program in AI/ML AIML certificate

Offered in collaboration with India's #1 AI Research Center and ML Lab

  • First IIIT
    in India

  • #1 in AI Research
    in India

  • Largest CS Research
    Group in India

  • #1 in Robotics
    Research in Asia

Kohli Center on Intelligent Systems (KCIS) at IIIT Hyderabad was established in 2015 to give a flip to research, teaching and entrepreneurship in the Broad Intelligent Systems Area. It has the #1 rated Machine Learning Lab in India and acts as an umbrella organization at the institute to both strengthen the existing groups and facilitate new activities in related areas. It also acts as a force multiplier in attracting projects and funding from the government and industry sectors, coordinating research in related domains across different IIIT Hyderabad centers, as well as in the institute's research collaboration with other academic institutions in the country. For more information please visit www.iiit.ac.in

Application Process Application Process

Apply for the Program

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For any queries that you may have, call @ +91-9989182726.


Frequently Asked Questions

There are 5 reasons why serious professionals prefer the IIIT Hyderabad AIML Program.

  • Program specifically designed for working professionals (Starts with problem definition, solution and the theory and concepts behind the solution)
  • Delivered in interactive digital format, retaining effectiveness while maintaining safety (Uniquely combines the benefit of the in-class program with the flexibility and safety of online delivery)
  • Hands-on program with ideal mix of theory and practice (over 60% of program is dedicated for lab experiments and individual and group work and hackathons with continuous mentor support)
  • Lectures by both Academic Professors and Industry Practitioners (a pracademic approach combining strong academic rigor coupled with practitioner perspectives)
  • Outstanding peer group with extensive group work (learn along with peers from wide range of industries, roles and positions)

Industry is clearly looking for professionals who can build AI/ML applications. Professionals with hands-on experience will be preferred by the industry.

This program is designed to reach higher levels of learning as per Bloom's Taxonomy. The program will not only help you Understand, but also enable you to Apply, Analyse and Evaluate which are far higher levels of expertise.

A participant will do 40+ individual lab experiments and 8 mini-hackathons. In addition they will also be participating in 4 hackathons, which includes select kaggle experiments. This will help the participant not only learn and implement AI/ML but also showcase your expertise for the industry to recognize.

Industry needs professionals with technical expertise and domain expertise to work together to solve today's challenges. Generally, domain expertise comes with experience, and tech expertise comes with young professionals.

As AI/ML has recently entered into the main-stage for companies and professionals, and the education system has very limited capacity for producing fresh graduates with AI/ML expertise, the industry is facing severe shortage. NASSCOM predicts that there are 140,000 vacancies while not even 30% of these seats are being fulfilled.

This has opened up great opportunities for working professionals. Those who are developing AI/ML expertise now are in great demand by the industry.

This demand will continue till the education system churns out enough good quality graduates with AI/ML expertise. The fact that the education system right from school is focusing on building AI/ML learning from a young age, and that many engineering institutions have launched focused programs like BTech in AI/ML, the supply will catch up with industry demand over the next 3-5 years.

This opens up a good window of opportunity for working professionals. If someone enters this area in the next 6 months to 1 year, they will have more than 2 year window to showcase their expertise and become the lead for the new generation that would come in.

Professionals are presented with a unique window of opportunity with AI/ML expertise. In the 1990s a large number of science graduates shifted to technology, and they are now defining the Technology sector. Similarly, those who enter the AI/ML area now will have a distinct advantage in the future of the industry.

Here's why this is the right time to invest in building your expertise:

  • Industry needs more deep-tech (AI/ML) professionals and less gen-tech (Java, testing, project manager) professionals
  • Growth opportunity is available for deep-tech and risk is higher for gen-tech professionals in the current economic scenario
  • Professionals today have more time in hand to 'sharpen the saw' than ever before thanks to working from home and avoiding hours and hours of travel to office and back in traffic

Based on the data since lockdown, we find that serious professionals are using this time to get ready for the future.

Two things are happening as you wait and watch. 1) Younger and more dynamic professionals are going to enter with knowledge, 2) the experience premium will continue to drop thereby making senior professionals less attractive to companies. Hence, earlier one moves into sunrise areas will be better.

The LinkedIn Emerging Jobs Report lists AI as the #1 in the emerging jobs list for 2020. The average package for AI professionals is approx 15 lakhs across all experience levels and skill sets.

The Program will be delivered in interactive digital format, retaining effectiveness while maintaining safety. The format uniquely combines the benefits of an in-class program with the flexibility and safety of online delivery.

Benefits of In-Class Delivery Flexibility and additional value of online
Synchronous program delivery by expert faculty Re-attend classes through recorded archives
Interact and get your doubts answered by faculty Access videos easily with searchable and indexed video archives
Work in group with other participants Learn from the comfort and safety of your home
Get support from mentor for labs and experiments Office hours with one-on-one mentor support

Program will be delivered on TalentSprint's patent pending iPearl.ai, a leading digital learning platform of choice used for programs delivered by the likes of Google, IIM Calcutta, IIT Hyderabad, IISc, and IIT Kanpur to name a few.

Last 3 cohorts of the AI/ML program has been delivered on this platform and has achieved high completion rate.

Learning effectiveness and experience of the participants on this program has been high with NPS of over 80 (NPS of 50 and above considered excellent while 70 and above is considered "world class")

Participants Feedback

  • Cohort 12 (NPS 85)
  • Cohort 14 (NPS 96)
  • Completion Rate 96%

In the wake of Covid-19, the world is going through an uncertain phase. Working from home, not being able to socialize, and concerns about personal and family safety are taking a toll on all of us. We hope the situation will improve soon.

More than ever before, we now need a balance between safety and flexibility in everything we do. We at IIIT Hyderabad and TalentSprint are fully committed to safety, flexibility, excellence and timeliness with regard to all of our programs.

In line with this, we have introduced the following:

1 2 3 4
Attend live interactive online classes by top professors from the safety of your home Practitioner's curriculum with Industry projects and Hackathons High-quality peer-learning, mentored group labs, and hackathons on digital platform Long term interest-free EMI options

If you choose to enroll for Cohort-15, these measures will give you an opportunity to continue your focus on long term goals and career objectives while retaining maximum flexibility.

You can connect with your Relationship Manager Vinodini +91-9059072509 for more details.