Application for qualifier exam to Foundational Level Open (This is not the form for Direct Entry to Diploma)   

Application for qualifier exam to Foundational Level Open (This is not the form for Direct Entry to Diploma)   

Degree Level Course

Deep Learning in Practice

by Pratyush Kumar

Course ID: BSCCS3052

Course Credits: TBD

Course Type: Elective

Prerequisites: TBD

What you’ll learn

Recognise the full stack of deep learning - datasets, frameworks, hardware for training, deployment across devices, interpretability, and security
Use tools to improve deep learning practice throughout the entire stack
Apply best practices in training and deployment, even under constraints of data and hardware
Build confidence of training models of real-world scale
Identify problems of social relevance that are solvable with deep learning

Course structure & Assessments

12 weeks of coursework, weekly online assignments, 3 in-person invigilated quizzes, 1 in-person invigilated end term exam. For details of standard course structure and assessments, visit Academics page.

WEEK 1 Datasets
WEEK 2 Deep Learning Frameworks
WEEK 3 Model training
WEEK 4 Hardware for DL
WEEK 5 Training with data constraints
WEEK 6 Training with hardware constraints
WEEK 7 Training models that are efficient for inference
WEEK 8 Interpreting models
WEEK 9 Security and privacy
WEEK 10 Deploying models
WEEK 11 Applications of DL
+ Show all 12 weeks

About the Instructors

Pratyush Kumar
Assistant Professor, Department of Computer Science, IIT Madras

Pratyush Kumar is an Assistant Professor at the Department of Computer Science and Engineering at IIT Madras. His research interests are in the areas of systems engineering for deep learning and applications of AI for social good. He holds a PhD from ETH Zurich and a BTech degree from IIT Bombay. He holds over 25 US patents and has co-founded One FourthLabs.

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