AI Shiksha
APPLIED ACCELERATED ARTIFICIAL INTELLIGENCE
Duration:
33 lectures (demos included) of 1 hour
each followed by 30 mins of Q&A
Hours:
Mondays, Wednesdays and Fridays - 5:00 pm to 6:30 pm. Students are expected to
attend all the sessions LIVE.
| Topic | Instructor | Proposed Date | ||
|---|---|---|---|---|
| Session 1: Fundamentals | ||||
| Introduction to AI System Hardware CPU, RAM, GPU, Interconnects, Storage, Network Controller | Dr. Satyajit Das | 31-Jan 2022 | ||
| Introduction to AI Accelerators GPUs (Lecture ) | Prof. Satyadhyan Chickerur | 02-Feb 2022 | ||
| Introduction to System Software Operating System, Virtualization, Cloud; ( Lecture ) | Dr. Satyajit Das | 04-Feb 2022 | ||
| Introduction to Containers and IDE (Jupyter Demo) ( Lecture + Demo ) | Prof. Satyadhyan Chickerur | 07-Feb 2022 | ||
| Scheduling and Resource Management Introduction to schedulers and orchestration tools ( Lecture ) | Mr. Bharat Kumar | 09-Feb 2022 | ||
| DeepOps: Deep-dive into Kubernetes with deployment of various AI-based services (Lecture + Demo) | Prof. Satyadhyan Chickerur | 11-Feb 2022 | ||
| DeepOps (contd) ( Lecture + Demo ) | Prof. Satyadhyan Chickerur | 14-Feb 2022 | ||
| Design principles for building High Performance compute clusters for AI ( Lecture ) | Mr. Bharat Kumar | 16-Feb 2022 | ||
| Implementation details for building High Performance compute clusters for AI (contd) (Lecture) | Mr. Bharat Kumar | 18-Feb 2022 | ||
| Frameworks for Accelerated Deep Learning Workloads - PyTorch ( Lecture ) | Dr. Satyajit Das | 21-Feb 2022 | ||
| Frameworks for Accelerated Deep Learning Workloads - PyTorch (contd) ( Lecture + Demo ) | Dr. Satyajit Das | 23-Feb 2022 | ||
| Accelerated PyTorch ( Lecture + Demo ) | Dr. Satyajit Das | 25-Feb 2022 | ||
| Frameworks for Accelerated Deep Learning Workloads - TensorFlow ( Lecture ) | Dr. Satyajit Das | 28-Feb 2022 | ||
| Frameworks for Accelerated Deep Learning Workloads - TensorFlow (contd) ( Lecture + Demo ) | Dr. Satyajit Das | 02-Mar 2022 | ||
| Accelerated TensorFlow ( Lecture + Demo ) | Dr. Satyajit Das | 04-Mar 2022 | ||
|
Additional Day (Q&A on Session 1) |
07-Mar 2022 | |||
| Exam on Session 1 | 13-Mar 2022 | |||
| Session 2a: End to End Accelerated Data Learning | ||||
| Optimizing Deep Learning Training: Automated Mixed Precision ( Lecture + Demo ) | Mr. Adesuyi Tosin | 14-Mar 2022 | ||
| Optimizing Deep Learning Training: Transfer Learning ( Lecture + Demo ) | Mr. Adesuyi Tosin | 16-Mar 2022 | ||
|
Holi (No session) |
18-Mar 2022 | |||
| Fundamentals of Distributed AI Computing: Multi-GPU and multi-node implementation (MPI, NCCL, RDMA) ( Lecture ) | Mr. Bharat Kumar | 21-Mar 2022 | ||
| Distributed AI Computing: Horovod ( Lecture + Demo ) | Mr. Bharat Kumar | 23-Mar 2022 | ||
| Challenges with Distributed Deep Learning Training Convergence ( Lecture + Demo ) | Mr. Bharat Kumar | 25-Mar 2022 | ||
| Fundamentals of Accelerating Deployment ( Lecture + Demo) | Prof. Satyadhyan Chickerur | 28-Mar 2022 | ||
| Accelerating neural network inference in PyTorch and TensorFlow ( Lecture + Demo ) | Prof. Satyadhyan Chickerur | 30-Mar 2022 | ||
| Session 2b: End to End Accelerated Data Science | ||||
| Accelerated Data Analytics (Lecture + Demo) | Mr. Bharat Kumar | 01-Apr 2022 | ||
| Accelerated Machine Learning (Lecture + Demo) | Mr. Bharat Kumar | 04-Apr 2022 | ||
| Scale Out with DASK | Mr. Bharat Kumar | 06-Apr 2022 | ||
| Web visualizations to GPU accelerated crossfiltering ( Lecture + Demo ) | Mr. Bharat Kumar | 08-Apr 2022 | ||
| Accelerated ETL Pipeline with SPARK | Mr. Bharat Kumar | 11-Apr 2022 | ||
| Session 2c: AI in Industry | ||||
| Applied AI: Smart City ( Intelligent Video Analytics) | Prof Satyadhyan Chickerur | 13-Apr 2022 | ||
| Applied AI: Smart City (Intelligent Video Analytics) (Contd.) | Prof. Satyadhyan Chickerur |
15-Apr 2022 (Good Friday) |
||
| Applied AI: Healthcare (Federated Learning, AI Assisted Annotation) | Prof. Satyadhyan Chickerur | 18-Apr 2022 | ||
| Applied AI: Healthcare (Federated Learning, AI Assisted Annotation) | Prof. Satyadhyan Chickerur | 20-Apr 2022 | ||
|
Additional Day (Q&A on Session 2) |
22-Apr 2022 | |||
| Exam on Session 2 | 01-May 2022 | |||