Generative AI 101
Description
This introductory course explores the fundamentals of Generative AI, focusing on Neural Networks and Generative Adversarial Networks (GANs). Participants will gain hands-on experience training models with Keras and understand the theory behind generative architectures.
Indicative Duration: 8 training hours
*Duration is adjusted based on the final scope and the target audience.
Scope
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1. Neural Networks
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2. Generative Adversarial Networks
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Learning Objectives
Upon completion of the course participants will be able to:
- Understand the foundational architecture and training principles of Neural Networks.
- Train and evaluate a basic Neural Network using Keras.
- Explain the core concepts behind Generative Adversarial Networks (GANs).
- Implement and experiment with a simple GAN using Keras.
Target Audience
- Roles: Junior to Mid-level Data Scientists, AI Enthusiasts, ML Engineers, Developers exploring AI
- Seniority Levels: Beginner to Intermediate professionals with some ML background
Prerequisite Knowledge
- Basic understanding of machine learning concepts
- Familiarity with Python programming
- Introductory knowledge of neural networks
- Experience with Jupyter notebooks or similar environments
Delivery Method
Sessions can be delivered via the following formats:
- Live Online – Interactive virtual sessions via video conferencing
- On-Site – At your organization’s premises
- In-Person – At Code.Hub’s training center
- Hybrid – A combination of online and in-person sessions
The training methodology combines presentations, live demonstrations, hands-on exercises and interactive discussions to ensure participants actively practice AI in realistic work scenarios.
