VTU Online Class - Course Details

Applied Accelerated Artificial Intelligence

Satyadhyan Chickerur

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What you will learn

Computer Science and Engineering

This course will cover the fundamentals of the compute capabilities and the system software required for implementing artificial intelligence (AI) based solutions on industrial use cases such as the ones in the domains of healthcare and Smart City. The course will discuss end to end deployments of two industrial use cases with demonstration, and hence will help participants use state-of-the-art AI SDKs effectively to solve complex problems.

Introduction to AI Systems Hardware part 1

Introduction to AI Systems Hardware - part 2

Introduction to AI Accelerators,GPUs

Introduction to Operating Systems, Virtualization, Cloud - part 1

Introduction to Operating Systems, Virtualization, Cloud part 2

Introduction to Containers and IDE Dockers part1

Introduction to Containers and IDE Dockers part 2

Scheduling and Resource Management part 1

Scheduling and Resource Management part 2

"DeepOps: Deep Dive into Kubernetes with deployment of various AI based Services." Part 1

"DeepOps: Deep Dive into Kubernetes with deployment of various AI based Services." Part 2

"DeepOps: Deep Dive into Kubernetes with deployment of various AI based Services Session II part1"

"DeepOps: Deep Dive into Kubernetes with deployment of various AI based Services Session II part 2"

Design principles for Building High Performance Clusters part 1

Design principles for Building High Performance Clusters part 2

Design principles for Building High Performance Clusters part 3

Design principles for Building High Performance Clusters part 4

Introduction to Pytorch part 1

Introduction to Pytorch part 2

Introduction to Pytorch part 3

Introduction to Pytorch part 4

Profiling with DLProf Pytorch Catalyst part 1

Profiling with DLProf Pytorch Catalyst part 2

Introduction to TensorFlow part 1

Introduction to TensorFlow part 2

Accelerated TensorFlow Part 1

Accelerated TensorFlow Part 2

Accelerated TensorFlow - XLA Approach Part 1

Accelerated TensorFlow - XLA Approach part 2

Optimizing Deep learning Training: Automatic Mixed Precision part 1

Optimizing Deep learning Training: Automatic Mixed Precision part 2

Optimizing Deep learning Training: Transfer Learning part 1

Optimizing Deep learning Training: Transfer Learning part 2

Fundamentals of Distributed AI Computing Session 1 Part 1

Fundamentals of Distributed AI Computing Session 1 Part 2

Fundamentals of Distributed AI Computing Session 2 Part 1

Fundamentals of Distributed AI Computing Session 2 Part 2

Distributed Deep Learning using Tensorflow and Horovod

Challenges with Distributed Deep Learning Training Convergence

Fundamentals of Accelerating Deployment part 1

Fundamentals of Accelerating Deployment part 2

Accelerating neural network inference in PyTorch and TensorFlow part 1

Accelerating neural network inference in PyTorch and TensorFlow part 2

Accelerated Data Analytics part 1

Accelerated Data Analytics part 2

Accelerated Data Analytics part 3

Accelerated Data Analytics part 4

Accelerated Machine Learning

Scale Out with DASK

Web visualizations to GPU accelerated crossfiltering part 1

Web visualizations to GPU accelerated crossfiltering part 2

Accelerated ETL Pipeline with SPARK part 1

Accelerated ETL Pipeline with SPARK part 2

Applied AI: Smart City ( Intelligent Video Analytics) Session 1 part 1

Applied AI: Smart City ( Intelligent Video Analytics) Session 1 part 2

Applied AI: Smart City ( Intelligent Video Analytics) Session 2 Deepstream part 1

Applied AI: Smart City ( Intelligent Video Analytics) Session 2 Deepstream part 2

Applied AI: Smart City ( Intelligent Video Analytics) Session 2 Deepstream part 2

Applied AI : Health care Session I part 1

Applied AI : Health care Session I part 2

Applied AI : Health care Session II part 1

Applied AI : Health care Session II part 2

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Meet Your Instructor

video

Free

Course Duration

29 h 23 m 41 s
Course Level

Intermediate
Student Enrolled

104
Language

English

This Course Includes

29 h 23 m 41 s Video Lectures
0 Quizzes
0 Assignments
0 Downloadable Resources
Full Lifetime Access
Certificate of Completion