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1. Robolution is the future

According to PwC, AI, robotics, automation, and autonomous machines will drive 70% of GDP growth between now and 2030 globally.

  • "The need for skilled engineers who can build, run, and maintain AI systems to go up by 20-50 million globally by 2030." 1
  • "50% of Indian firms to deploy intelligent automation by 2024." 2
  • "The autonomous navigation market to reach $13.5 Bn by 2030." 3

2. High Impact Format

  • Live Interactive Sessions With expert faculty from IISc
  • Experiential Learning Supported by use-cases and capstone projects
  • Hi-Tech Hi-Touch Learning with iPearl.ai Access best-in-class digital content for 24x7 learning
  • Experience IISc campus 2 campus visits, one each at the start and end of the cohort

3. IISc Advantage
World’s #1* Research University

IISc IISc

IISc (Indian Institute of Science) is the oldest and the finest higher education institute of its kind in India. It pursues excellence in research and education in several fields of Science and Engineering and is one of the first three publicly funded institutes to be awarded the Institute of Eminence status. The alumni of IISc hold significant academic and industry positions around the globe. For more information visit www.iisc.ac.in

The PG Level Advanced Certification Programme on Machine Learning and AI for Autonomous Systems will be delivered by IISc’s Centre for Continuing Education (CCE). CCE delivers courses suitably designed to meet the requirements of various target groups - research & development (R&D) laboratories and industries, research scientists, and engineers, and enable them to grow into competent managers of technology-intensive and data-driven organizations. For more information, visit cce.iisc.ac.in

AI ML course for Autonomous Systems Overview

Join the 9-month AI ML course for Autonomous Systems PG Level Certification by IISc Bangalore, designed for tech professionals. The course covers the state-of-the-art curriculum and insights into AI implementation in autonomous systems. It includes campus visits and online live interactive sessions, allowing candidates to apply their learnings to real-world tasks.

To be eligible for the course, candidates must possess a B.Tech (BE) degree in any engineering discipline with a minimum of 50% marks or at least 4 years of job experience in the related field. Coding experience is required, preferably in Python, and exposure to Engineering Mathematics is considered an added advantage.

Get certified and unlock your potential in AI and Machine Learning for Autonomous Systems with IISc Bangalore.

Expert Faculty

Taught by eminent IISc Faculty Group


Programme Coordinator Prof. Ambedkar Dukkipati
Professor, Department of Computer Science and Automation, IISc

Research Expertise: Statistical Machine Learning, Reinforcement Learning, and Deep Learning in Low data Regimes.

  • Heads the Statistics and Machine Learning Group, CSA Department, IISc.
  • Worked as a postdoctoral researcher with EURANDOM, The Netherlands.
  • Published various research articles on Deep Learning, Algorithmic Algebra, and Stochastic Optimization topics.
  • An IIT Madras and IISc alumnus, he also teaches a few other programs offered by the Centre for Continuing Education (CCE) at IISc.

Prof. Shalabh Bhatnagar
Professor, Department of Computer Science and Automation and Associate Faculty, Robert Bosch Centre for Cyber-Physical Systems, IISc

Research Expertise: Stochastic Approximation Algorithms, Stochastic Control, Reinforcement Learning, Simulation Optimization, Autonomous Systems, Vehicular Traffic Control, Smart Grids, Communication/Wireless Networks

  • Head of Stochastic Systems Laboratory at IISc.
  • Authored research papers and a book titled ‘Stochastic Recursive Algorithms for Optimization: Simultaneous Perturbation Methods.’
  • Worked as a Principal Investigator for sponsored projects of organisations like DRDO, Xerox, DST - GoI, and Texas Instruments (India).
  • Winner of Prof. Satish Dhawan Young Engineer Award (2013), Rajib Goyal Young Scientist Prize (2012,13,15), and more such honors.
  • Besides IISc, worked as a Visiting Faculty for leading institutions like IIT Delhi, INRIA - France, TU Delft, Netherlands, and NUS - Singapore.

Prof. Shishir Kolathya
Assistant Professor, Robert Bosch Center for Cyber-Physical Systems and Department of Computer Science and Automation, IISc

Research Expertise: Hybrid robotic Systems, Safety Critical Control, Application of Learning Theory to Legged Locomotion

  • Principal Investigator for IISc’s Stochastic Robotics Lab, where novel learning-based controllers for quadrupeds are developed.
  • Started career as an R & D Engineer with Tejas Networks, Bangalore.
  • Worked as a Postdoctoral Fellow for California Institute of Technology (Caltech), USA.
  • His work is majorly focused on robotics, especially in the domain of legged robots.
  • His research and conference publications are mostly centered around Bipedal Robotic Locomotion.

Curriculum

With the state-of-the-art curriculum, designed by IISc Faculty, gain an insight into AI implementation in the modern context of autonomous systems with the possibility to apply the learnings to real-world tasks.

Module 0: Bridge Module

  • Basics of Probability
  • Basics of Linear Algebra

Module 2: Introduction to Sequential Decision Making and Reinforcement Learning

  • Introduction and Real world examples
  • Sequential Decision Making under Uncertainty: Multi-armed Bandits
  • Markov Decision Process, Value & Q-functions, Finite and Infinite Horizon Problems
  • Value and Policy iteration, Dynamic ProgramingMarkov Decision Process, Value & Q-functions, Finite and Infinite Horizon Problems
  • Policy evaluation with Monte-Carlo and Stochastic approximation

Module 3: Data-driven Optimization

  • Basics of Optimization
  • Deterministic Algorithms for Local Search-Gradient/Newton/Jacobi Schemes
  • Data-driven Gradient Search Algorithms for Optimization – Kiefer-Wolfowitz Algorithm, Random Perturbation Methods, Smoothed Functional Schemes
  • Data-driven Newton-based Random Perturbation Algorithms for Multi-Dimensional, Parameter Optimization
  • Data-driven Algorithms for Discrete Parameter Optimization with Noisy/Uncertain Objectives
  • Data-driven Algorithms for Optimization under Constraints
  • Case studies in Dynamic Pricing and Resource Allocation, Vehicular Traffic Control, Wireless Networks

Module 4: Reinforcement Learning Algorithms

  • Model-free Algorithms for Policy Evaluation – Incremental Update Temporal Difference Learning, N-step Temporal Difference Learning
  • Model-free Least Squares Temporal Difference Learning, Least Squares Policy Evaluation, Incremental Least Squares Temporal Difference Learning
  • Model-free Value-based Algorithms for Control – SARSA, Q-learning, Expected SARSA, Double Q-learning
  • Algorithms for On-policy Prediction with Value Function Approximation – Linear Approximation Architectures (Fourier/Polynomial bases, Tile Coding, Radial basis Functions), Non-Linear Approximation Architectures (Artificial Neural Networks)
  • Off-policy Value-based Algorithms with Approximation – Semi-Gradient Methods, Gradient descent in Bellman error, Gradient Temporal Difference Learning, Temporal Difference with Correction
  • Policy Gradient Algorithms – Policy Parameterization, REINFORCE: Monte-Carlo Policy Gradient, REINFORCE with Baseline, Actor-Critic Algorithms
  • Recent Algorithms - Deep Q-network, Trust Region Policy Optimization, Proximal Policy Optimization, A2C, A3C

Module 5: RL Applications to Autonomous Systems

  • Deep RL Demonstrations on Simulated Environments
  • Introduction to Robotics


Detailed Curriculum

Participant Profile

From Top Organizations

Amazon Web Services
Arctictern Solutions
AT&T
Cetazean
Cientra Techsolutions
Citicorp
ELGI Equipments
Google
HCL
Iqvia
Jay Switches
John Deere
Junglee Games
Maleotech Solutions
MBRDI
Motorola
Netgear
Nobis Labs
RafterOne
Slice
TCS
Tata Motors
Tech Mahindra
Tata Strategic Management Group
USFB
Volvo
Wipro

From Across Indian Cities and International Locations

Bagalkot
Bengaluru
Chennai
Gurgaon
Hyderabad
Mumbai
New Delhi
Noida
Pune
Eindhoven

Is this programme for me?

  • Yes, if you are a tech professionals involved in the design and validation of autonomous systems across industries.

Eligibility


  • Qualification: B.Tech (BE) degree in any engineering discipline with min. 50% marks or at least 4 years of job experience in the related field.
  • Coding Experience: Required, preferably in Python
  • Good to have: Exposure to Engineering Mathematics

How can I enrol in this programme?

RM
  • Application

    Apply for the
    Programme

  • Upload Document

    Submit
    Documents**

  • Selection

    Selection by
    IISc Committee*

  • Enrollment

    Join the
    Programme

*Selection for the programme will be done by IISc and is strictly based on the education, work experience, and motivation of the participants.

**Scanned copies to be submitted within 7 days 1. Education Certificate 2. Experience Letter/Latest Pay Slip

What is the return on my investment?

By successfully completing the programme, you will be able to shift to new roles that require expertise in autonomous systems powered by AI and become adept at managing and scaling intelligent automation initiatives in your organisation.


  • $9.32 Bn would be the global autonomous navigation market by 2028 4
  • 97 Mn new roles will be created by 2025 as humans, machines and algorithms increasingly work together 5
  • 90% of organisations expect AI to increase their workforce capacity 6
  • 90% of enterprises will have an automation architect by 2025 7
  • $3 Tn would be the worldwide economic impact of converged AI-powered automation by the end of 2022 8
  • $15.7 Tn would be the potential contribution to the global economy by 2030 from AI 9

AI and Machine Learning for Autonomous Systems Course Fee

Details 9 Months Programme
Programme Fee* ₹2,80,000/-

12-Month 0% EMI available Nominate your employees to avail special benefits *GST as applicable

(i) Application Fee of ₹2,000, and
(ii) Campus visit fee will be based on actuals and to be borne by the participants
(iii) Fees paid are non-refundable and non-transferable.


Frequently Asked Questions

Who should attend this programme?

The programme is useful for tech professionals interested in learning AI/ML and reinforcement learning to design and build autonomous systems for applications across industries.

Who will teach this programme?

You will learn from eminent IISc faculty who hold academic and research credentials from the world’s best institutions. Meet your faculty here.

View all

About TalentSprint

  • 10 Years of
    Excellence
  • 200K Empowered
    Professionals
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    Rate
  • 85 Net Promoter
    Score

Established in 2010, TalentSprint (a part of the NSE group) is a global EdTech company offering cutting-edge, deeptech, management programs for early career and experienced professionals, with top institutions/organizations. It creates a highly-skilled niche talent pool to meet new-age industry demands. The company’s digital learning platform ipearl.ai offers a hybrid onsite/online experience to seekers of deep technology expertise. TalentSprint is a leading Innovation Partner for the National Skill Development Corporation, an arm of the Ministry of Skill Development and Entrepreneurship, Government of India. It is also a recipient of various prestigious accolades. Some of the recent ones are:

Education Excellence Award 2022

EdTech Leader of The Year 2023

Best Edtech Company of The Year 2023

Digital Learning Company of The Year 2023

Best Edtech Solution of The Year 2023

Most Breakthrough Product of the Year 2023

References

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