IISc Certification | 10 Months | Interactive Live Online Programme Next Selection Review on 26th Feb

Next Selection Review on 26th Feb

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6 Ways This Deep Learning Course Gives You An Edge


  • Get Certified by Center for Continuing Education at IISc

  • Learn from an interdisciplinary
    team of leading IISc faculty

  • Get mentored by researchers
    and practitioners

  • Work on curated
    industry Capstone Projects

  • Establish a compelling portfolio of project work that demonstrates your expertise

  • Build your deep learning foundations and learn effective applications

Hear from our program alumni

Every Industry wants Intelligence

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Deep Learning Engineer among top paid Artificial Intelligence roles in India

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Top Deep Learning Career Opportunities

  • Deep Learning Engineer
  • Deep Learning R&D Engineer
  • Computer Vision and Deep Learning Engineer
  • Deep Learning Research Intern
  • Jr. Data Scientist
  • Deep Learning Developer
  • And more

Deep Learning Course Overview

The PG Level Advanced Certification Course in Deep Learning is offered by the Center of Continuing Education at IISc in collaboration with TalentSprint is a 10-month weekend program that enables both aspiring and practicing AI/ML professionals to build expertise in Deep Learning. The program covers the essential theoretical foundations of deep learning and teaches students how to apply them in the real world effectively. The course is best suited for individuals with programming knowledge who want to create a practical understanding of how machine learning algorithms can be developed and optimized for hardware.

The program is delivered through a unique 5-step learning process that includes LIVE online interactive sessions by IISc and TalentSprint faculty, capstone projects, mentorship, case studies, and campus visits. This fast-track learning process ensures that students gain hands-on experience in applying deep learning techniques to real-world scenarios. Additionally, the program connects students to its Deep Tech alumni network, providing them with lifelong career benefits.

As a deep learning certification course, this program focuses on developing a practical understanding of optimizing machine learning algorithms for hardware to create edge computing systems. The interactive sessions cover the fundamentals of deep learning and its applications, including speech, text, image, and video processing. With its comprehensive curriculum, experienced faculty members, and unique learning process, this program offers a valuable opportunity for individuals who want to specialize in deep learning and advance their careers in the field of AI/ML.


About IISC Bangalore Deep Learning Course



IISc (Indian Institute of Science) tops among the oldest and the finest higher education institutes in the world. 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 https://www.iisc.ac.in.

The Center of Continuing Education at IISc offers the Advanced Certification Programme in Deep Learning program in collaboration with TalentSprint. CCE delivers courses suitably designed to meet the requirements of various target groups, e.g. aspiring research scientists, graduate engineers, young professionals, to enable them to grow into competent managers of technology-intensive and data-driven organizations. For more information visit http://cce.iisc.ac.in.

Learn from Leaders

IISc faculty members are an impressive group bearing academic accreditation from premier institutions around the world

Prof. Chiranjib Bhattacharyya
Unsupervised Learning, Optimization, Autonomous Systems

Ph.D., Computer Science and Automation, IISc, India
Programme Coordinator

Professor and Chairperson of the Dept. of Computer Science and Automation, IISc. He is a fellow of the Indian Academy of Engineering. His research areas include Unsupervised Learning, Optimization, Autonomous Systems.

Prof. Chandramani Singh
Communication Network, Federated Learning, Stochastic Systems

Ph.D., Electrical Communication Engineering, IISc, India

Assistant Professor in the Dept. of Electronic Systems Engineering, IISc. Previously a Postdoctoral Research Associate at University of Illinois at Urbana-Champaign. Recipient of Microsoft Research India Rising Star Award for the academic year 2010-2011. His research focuses on Communication Networks, Stochastic Systems, Federated Learning, Optimization and Game Theory.

Prof. Prasanta Kumar Ghosh
Speech and Audio Signal Processing, Speech Production

Ph.D., Electrical Engineering, University of Southern California, USA

Associate Professor at the Dept. of Department of Electrical Engineering, IISc. Before joining IISc, he was a faculty fellow in the department of EE under the INSPIRE faculty fellowship programme. His research interests include Non-Linear Signal Processing Methods for Speech and Audio, Speech Production and its relation to Speech Perception, and Automatic Speech Recognition inspired by the Speech Production and Perception Link.

Prof. Shirish Shevade
Machine Learning, Applications of Deep Learning

Ph.D., IISc, India

Professor at the Dept. of Computer Science and Automation, IISc. He is a Senior Member of Institute of Electrical and Electronics Engineers (IEEE). His research interests include Machine Learning and applications of Deep Learning.

Prof. Venkatesh Babu. R
Signal Processing, Machine Vision, Image/Video Processing, Pattern Recognition

Ph.D., Electrical Engineering, IISc, India

Associate Professor at the Dept. of Computational and Data Sciences, IISc. He has held postdoctoral positions at Universities across Europe and worked in industry before taking active interest in academics. His research interests include: Signal Processing, Compression, Machine Vision, Image/Video Processing, Pattern Recognition and Multimedia.

Prof. Prathosh A P
Deep Representation Learning, Deep Learning, Machine Learning, Digital Healthcare

Ph.D., Signal Processing & Machine Learning, IISc, India
Co-founder/Chief of Engineering, CogniAble Tech

Assistant Professor at the Department of Electrical Communication Engineering, IISc. Before joining IISc, he worked for four years as an Assistant Professor in the Computer Technology Group of Electrical Engineering at IIT Delhi. Before switching to academics, he worked in corporate research labs including Xerox Research India, Philips Research, and a Californian-based startup in the USA. His industry career mainly spanned focussing on healthcare analytics. He has 15 (US) patents to his credit, of which 10 are granted and 6 are commercialized. He co-founded CogniAble Tech which builds learning algorithms for behavioural healthcare (Winner of AI start-up challenge by GoI), and actively engaged with several corporate industries, start-ups, and medical centres (like AIIMS) in solving interesting technical problems. His research interests include guided Deep-Representational Learning, Cross-Domain Generalization, Machine Learning, and Signal Processing ( in healthcare).

Prof. Ambedkar Dukkipati
Statistics, Machine Learning

Ph.D., IISc, India

Associate Professor at the Dept. of Computer Science and Automation, IISc. His research interests include Statistical Network Analysis, Network Representation Learning, Spectral Graph Methods, Machine Learning in Low Data Regime, Sequential Decision-Making under Uncertainty and Deep Reinforcement Learning.

Prof. Chetan Singh Thakur
Neuromorphic Computing, Machine Learning for Edge Computing, Machine Learning Hardware, Analog/Digital ASIC design

Ph.D., Neuromorphic Engineering, MARCS Research Institute, Western Sydney University, Australia

Assistant Professor at the Dept. of Electronic Systems Engineering, IISc. Before joining IISc, he worked as a Research Fellow at Johns Hopkins University. In addition, he worked with Texas Instruments, Singapore as a Sr. Integrated Circuit Design Engineer, designing IPs for mobile processors.His research areas include Neuromorphic Computing, Mixed Signal VLSI Systems, Analog/Digital ASIC design, and Machine Learning for Edge Computing.

Prof. Rajiv Soundararajan
Image and Video Signal Processing, Computer Vision, Machine Learning, Information Theory

Ph.D., Electrical and Computer Engineering, University of Texas at Austin, USA

Assistant Professor in the Dept. of Electrical Communication Engineering, IISc. Previously he worked with Qualcomm Research India, Bangalore. His research interests are broadly in Image and Video Signal Processing, Computer Vision, Machine Learning, and Information Theory.

Prof. Sriram Ganapathy
Machine Learning, Deep Learning, Speaker and Language Recognition

Ph.D., Johns Hopkins University Baltimore, USA

Assistant Professor in the Dept. of Electrical Engineering, IISc. Previously he worked as Research Staff Member at the IBM T.J. Watson Research Center in Yorktown Heights, NY, USA. His research areas include Machine Learning, Deep Learning, Auditory Neuroscience, Speaker and Language Recognition, Speech Enhancement and Recognition.

Prof. Vijay Natarajan
Scientific Visualization, Computational Geometry, Computational Topology

Ph.D., Computer Science, Duke University, USA.

Mindtree Chair Professor in the Dept. of Computer Science and Automation, IISc. He also heads Visualization and Graphics Lab. Prior to joining IISc, he was a postdoctoral researcher in the Institute for Data Analysis and Visualization at University of California, Davis. His research areas include Scientific Visualization, Computational Geometry, and Computational Topology.

Deep Learning Course Curriculum

Module 0: Programming and Basic Math (Preparatory Module)

Module 1: Mathematical Preliminaries and Data Visualization

  • Linear Algebra
  • Probability and Statistics
  • Numerical Optimization for ML
  • Data Visualization

Module 2: Introduction to Machine learning

  • Supervised Learning
  • Unsupervised Learning

Module 3: Deep Learning Architectures

  • Logistic regression
  • Neural Networks - CNN, RNN, LSTM
  • Backpropagation, Deep networks
  • Regularization, Dropout, Batch Normalization

Module 4: Deep Learning for Natural Language Processing

  • Introduction
  • Distributed word representations
  • Language Modeling, Convolutional neural networks for Text
  • GRUs, LSTMs for Language Modeling, Attention and Applications, GPT, BERTs and Variants
  • Recurrent Neural Networks (Unidirectional and Bidirectional), Machine Translation, POS, Sentence Classification, Text Generation
  • Graph Neural Networks

Module 5: Deep Learning for Speech and Audio Processing

  • Audio representations for deep learning
  • Speech Recognition
  • End-to-end deep networks
  • Detection Models

Module 6: Deep Learning for Computer Vision

  • Popular CNN architectures
  • Transfer learning, autoencoders
  • Object detection,image segmentation
  • RNN and LSTM for image captioning/video

Module 7: Deep Reinforcement Learning

  • Introduction to sequential decision making under uncertainty
  • Implementing RL algorithms with deep neural networks.
  • Value functions, Finite and infinite Problems

Module 8: Deep Learning for IoT/Edge Devices

  • Overview of various ML hardware for IoT/Edge devices
  • Energy Efficiency, IoT/Edge Devices
  • Optimization techniques * ML Model for Edge Devices

Module 9: Representation Learning

  • Deep Generative Models I
  • Deep Generative Models II
  • Semi and Self-supervised Learning I
  • Semi and Self-supervised Learning II

Showcase your capabilities with real-world projects

Bring Your Own Project
(Learn to solve a problem which you / your organization is facing using Deep Learning)

or

Choose From Curated Capstone Projects

  • Brain Tumor
    Detection
  • Fraud
    Detection
  • Expression
    Identification
  • And
    more

Deep Learning Portfolio

Showcase your Deep Learning journey in the programme through various experiments and projects in a compelling manner.


Detailed Curriculum

Schedule

onlineInteractive Online Classes

  • Faculty-led Interactive Sessions
  • Convenient Schedule
  • Direct to Device

View Details

Campus Visit of 2 Days
Dates will be decided keeping the safety of participants in mind. Fees will be based on actuals.


What should you expect from this Deep Learning Certification Course?

  • LearnLearn from Leading IISc Faculty
  • ReinforceReinforce Learning by Applying Concepts
  • NetworkNetwork with Experts at the forefront of Deep Learning Practises
  • EarnCertification by Center for Continuing Education at IISc that will boost your resume
certificate

Eligibility

Education:  Graduation (BE, Btech, BSc, MSc etc) or Masters in Science | Engineering | Management (relevant)

Experience: Working professionals (with minimum 1 year of work experience) with active hands-on coding experience aspiring to build expertise in Deep Learning

Enrolment Process

  • Application

    Apply for
    Programme

  • Block Your Seat

    Submit
    Details

  • Enrollment

    Await
    Selection

  • Enrollment

    Join
    Programme

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

Participant Profile

From Top Organizations

Birlasoft
Walmart
Bank of America
Wipro
Fidelity Investments
Standard Chartered
Tech Mahindra
GE
Accenture
Samsung
DXC Technology
Synopsys
Intel
Reliance
McKinsey & Company
Aashaya Designs
ABB
Aditya Birla Group
Amazon
ANZ Group Holdings Ltd
Blowhorn
Bosch
Byjus
Cognizant
Collins Aerospace
DataStax
Dell
Devoteam
Dimagi
Genpact
GlobalLogic
HDFC
HelloAR
HP
HSBC
IBM
Infosys
Iras
IRRI
JP Morgan
Khatabook
KloudKraft
Legato
Lowe's
Magna electronics
Moschip Technologies
Mu sigma business solutions
Novartis
Optum
Oracle
Panasonic
PayPal
PwC
Qualcomm
Salesforce
Shell
SLB
SLK
Solvendo
Soroco
Splashdata
TCS
The Math Company
Thoucentric
TVS Credit
Velospear
Visa
Vmware
Wells Fargo
WorkLLama

From Indian and Global Locations

Pune
Noida
Chennai
Gurgaon
Allahabad
Mumbai
Lucknow
Bangalore
Kolkata
Delhi
Hyderabad
Gurugram
Andhra Pradesh
Belgaum
Bihar
Coimbatore
Gujarat
Haryana
Karnataka
Madhya Pradesh
Maharashtra
Mysore
Odisha
Tamilnadu
Telangana
Uttar Pradesh
West Bengal
Edison
Missouri
California

Find out why professionals want to join the Deep Learning course

"After decades of experience in the software industry, solving technical and business problems using traditional methods, I felt it's time to hone my skills in Deep Learning and be industry-relevant."
- Malay Sankar Barik, IT & Software

"I have previously worked on projects based on traditional machine learning algorithms and methods. Deep learning is where the new frontiers lie for me as a professional. I consider it as a necessary skill set to be able to relate with futuristic technologies that will define the profession of data science."
- Roopak Prajapat, FMCG

"My goal is to build deep knowledge in Deep Learning to handcraft AI applications in the following areas - Customer Acquisition, Manufacturing, R&D, and HR. The program complements my current skill set and will help me build a solid foundation in Deep Learning."
- Ruchi, IT & Software

"Deep Learning expertise will make my job easy, help enhance other Cloud Services and monitor them. I am also looking forward to finding new avenues with Deep Learning on Cloud."
- Alex, IT & Software

"I am looking forward to gaining an in-depth understanding of deep learning, AI, and reinforcement learning and use the same to lead data science projects in the organization."
- Arushi Rai, IT Solutions

"My company works on 5G and AI accelerator SoCs. I believe this programme will equip me with knowledge of the applications and internal workings of AI hardware. This will eventually help me work towards designing better accelerators."
- Harshita Prabha, Telecommunication

"I am looking forward to understanding Deep Learning in depth - its basics, concepts, and work on projects. I wish to explore career opportunities in this domain in the future."
- Vathsala, IT & Software

"I want to understand the importance of ML systems more mathematically and logically, which would improve the way I look at data. Hence I have enrolled for this programme."
- Navneeth, IT & Software

Note: These are edited versions based on the details submitted by various programme applicants.

PG level Deep Learning Certification Course: Fee

Details Domestic Participants International Participants
Programme Fee
With Scholarship		 ₹3,60,000
₹2,70,000		 $4,500
$3,375
GST as applicable

12-Month 0% EMI available Nominate your Employee to Avail Special Benefits

Campus visit fee will be based on actuals and to be borne by the participants.
Fee paid is non-refundable and non-transferable.

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