Applied Edge AI: Deep Learning Outside of the Cloud

Target Groups:

everyone

Professional Requirements:

- High school math is required (pre-course) - Basics in Machine Learning and Deep Learning - Python as programming language

Technical Requirements:

Keine besonderen Anforderungen.

Classification of the Federal Employment Agency:

• C 1410-20-10 Internetnutzung - allgemein

Contents

Compared to Cloud Computing, which is centralized in computing and data storage, Edge Computing brings computation and data storage closer to data sources.

Edge AI combines edge computing and AI technology and has become a rapidly developing field in the past few years. Edge AI enables AI computing directly on the edge or client device, enhancing power efficiency, supporting low latency, and solving data privacy problems.

Therefore, what improvements need to be made to traditional deep learning algorithms in Edge AI scenarios? This course teaches you about deep model compression and optimization techniques, decentralized and collaborative deep learning approaches and algorithms, software, and hardware for Edge AI.

What will you learn?
- Summary of deep learning basics relevant for this course
- Deep model compression and optimization techniques
- Decentralized and collaborative deep learning
- Algorithms, software and hardware for Edge AI