Deep Learning Engineer among top paid Artificial Intelligence roles in India
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
About the Programme
The PG Level Advanced Certification Programme in Deep Learning (Foundations and Applications) enables professionals to build expertise in Deep Learning, starting from essential theoretical foundations to learning how to apply them in the real world effectively. The 10-month weekend programme is best suited for aspiring and practising AI and Machine Learning professionals with programming knowledge.
The programme creates a practical understanding of how Machine Learning algorithms can be developed and optimized for hardware. Such systems can be used in edge computing where power and performance are the major constraints. The interactive sessions will cover fundamentals of deep learning and its applications including speech, text, image, and video processing.
It is delivered in a unique 5-step learning process of LIVE online interactive sessions by IISc and TalentSprint faculty, capstone projects which start in the middle of the programme and continue till the end, mentorship, case studies, and campus visits to ensure fast-track learning.
IISc, with its expertise in multi-disciplinary sciences, is best positioned to offer this programme. Delivered in association with TalentSprint, the programme also connects you to its Deep Tech alumni network so that you can reap life-long career benefits.
About Indian Institute of Science
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 Advanced Certification Programme in Deep Learning will be delivered by IISc’s Centre for Continuing Education (CCE). 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.
*Based on metric of Citations per Faculty
Learn from Leaders
IISc faculty members are an impressive group bearing academic accreditation from premier institutions around the world
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.
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.
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.
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.
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.
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).
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.
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.
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.
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.
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.
Module 0: Programming and Basic Math (Preparatory Module)
Module 1: Mathematical Preliminaries and Data Visualization
Probability and Statistics
Numerical Optimization for ML
Module 2: Introduction to Machine learning
Module 3: Deep Learning Architectures
Neural Networks - CNN, RNN, LSTM
Backpropagation, Deep networks
Regularization, Dropout, Batch Normalization
Module 4: Deep Learning for Natural Language Processing
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
End-to-end deep networks
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)
Choose From Curated Capstone Projects
Deep Learning Portfolio
Showcase your Deep Learning journey in the programme through various experiments and projects in a compelling manner.
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 Programme?
LearnLearn from Leading IISc Faculty
ReinforceReinforce Learning by Applying Concepts
NetworkNetwork with Experts at the forefront of Deep Learning Practises
EarnIISc Certification that will boost your resume
TalentSprint Career Accelerator Program
Supports certified learners looking for a new career
Resume Building and LinkedIn Profile Makeover
Interview Practice Sessions
Dedicated Portfolio Page to showcase project and program accomplishments
Network with Peers and Alumni
Knowledge exchange sessions with business/tech leaders
Lifetime membership to TalentSprint Alumni Network
Access to incubators for promising startup ideas
Access to Career Opportunities*
6 months membership of Hirist
Annual Career Fair and career opportunities from 500+ hiring partners
Exclusive Job Alerts through TalentSprint Alumni Network
*Terms & Conditions apply
Education: Graduation (four years or equivalent)
Experience: Working professionals with active hands-on coding experience aspiring to build expertise in Deep Learning
Coding Experience: Programming experience is mandatory to join this 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.
64%5+ Years of Exp.
From Top Organizations
Bank of America
McKinsey & Company
From Indian and Global Locations
Find out why professionals want to join the programme
"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.
Campus visit fee will be based on actuals and to be borne by the participants.
Fee paid is non-refundable and non-transferable.
10 Years of
85 Net Promoter
Established in 2010, TalentSprint is a part of NSE group and a global edtech company that brings transformational high-end and deep-tech learning programs to young and experienced professionals. The company’s digital learning platform ipearl.ai offers a hybrid onsite/online experience to seekers of deep technology expertise. TalentSprint partners with top academic institutions and global corporations to create and deliver world class programs, certifications, and outcomes.Its programs have consistently seen a high engagement rate and customer delight. It is a leading Innovation Partner for the National Skill Development Corporation, an arm of the Ministry of Skill Development and Entrepreneurship, Government of India. A recipient of various prestigious accolades, TalentSprint was recently honored with the Indian Achievers Award 2022, for its excellence in building deeptech talent in India. For more information about TalentSprint, visit TalentSprint website
Computers have gone much beyond mere computing numbers at a superhuman level. With Deep Learning, it seems computers might finally meet human-level performance or even surpass them in intuitive tasks like understanding spoken words, recognizing objects in an image, etc. Deep Learning has led to many technological breakthroughs. It is being used in investment modeling, fraud detection, autonomous cars, virtual assistants, super-computing, customer relationship management (CRM) systems, and facial recognition systems. Further, a lot of research is going on across the world to unleash its unfathomable potential. With such developments, Deep Learning is creating massive opportunities for professionals with the right skills.
Deep Learning is penetrating the industry at an unprecedented pace. In a way, almost every sector of the industry – healthcare, software, retail, manufacturing, and others is leveraging Deep Learning applications. As the adoption of these intelligent technologies increases, so is the demand for professionals with relevant Deep Learning capabilities. This demand will only escalate higher.
Here are the most promising Deep Learning career paths that you can aspire for:
IISc is India’s premier institution for advanced scientific and technological research and education. It is one of the first three publicly funded institutes to be awarded the Institute of Eminence status.
The institution’s reputation and pre-eminence consistently feature it in global university rankings. The institution has been home to distinguished alumni who have had noteworthy academic and industry positions around the globe.
TalentSprint, an National Stock Exchange (NSE) Group Company, brings high-end and deep-tech education to aspiring and experienced professionals in partnership with top academic institutions and global corporations. Its patent-pending, AI-powered, digital learning platform enables a perfect blend of high-end academics and industry-leading practitioner experience.
Given its in-depth understanding of the deep technologies, access to industry experts, and a state of art technology platform, IISc has chosen TalentSprint as its partner for executive education programmes in disruptive and emerging technologies. For more information, visit www.talentsprint.com.