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Course Description
Artificial intelligence has become an extremely important area for IT professionals and engineers in the past 10-20 years with the scientific breakthroughs and practical applications of deep learning and more recently of generative AI systems, especially with its Large Language Model (LLM) variant such as OpenAI’s ChatGPT and Google’s Bard. Due to its importance and impact on every aspect of our lives, understanding the concepts, functionalities and practical usage of AI systems is quickly becoming essential for all IT and other technical professionals as well as for managers with technical background.
This training focuses on Generative AI techniques and teaches participants the following topics (preliminary list):
- Introduction to Generative AI
- Variational Autoencoders
- Generative Adversarial Networks (GANs)
- Autoregressive Models
- Diffusion Models
- Transformers and General Pretrained Models (GPT)
- Multimodal Models
Besides gaining a basic understanding of the theory of Generative AI models, students will also make extensive lab exercises using the Python based TensorFlow + Keros framework to see how these models work in practice.
This training is part of the AI portfolio of Component Soft which explores essential AI topics, such as ChatGPT and GPT API Prompt Engineering for Developers, Deep Learning Basics, Large Language Models (LLM) Basics, and Generative AI Basics.
Course Length: 24 training hours
Structure: 50% theory, 50% hands on lab exercises
Target audience: All types of IT, telecom and other technical professionals as well as managers with technical background who want to understand the basic concepts, types and functionalities of Generative AI.
Prerequisites: Basic understanding of AI, Machine Learning and Deep Learning concepts. Basic Python programming skills. Some experience in using TensorFlow and Keros deep-learning frameworks.
Suggested preliminary course: AI-202 Deep Learning Basics