4.7/5 
4.7/5
12 Sessions
Introduction to AI
- What is Artificial Intelligence?
- The Evolution of AI: From Logic to Learning
- Overview of AI Applications in Daily Life
Foundations of AI
- Understanding Machine Learning
- Introduction to Neural Networks and Deep Learning
- Key Concepts: Supervised vs. Unsupervised Learning, Reinforcement Learning
Generative AI Fundamentals
- What is Generative AI?
- Generative AI vs. Traditional AI
- Popular Generative AI Technologies: GANs, VAEs, Transformers
Large Language Models
- Introduction to large language models (LLMs)
- Understanding how LLMs are trained
- Exercise: Compare the output of different LLM sizes for the same prompt.
Responsible AI
- Ethics and biases in AI
- Principles of responsible AI development
- Exercise: Analyze biases in each set of AI-generated texts.
Prompt Engineering
- Introduction to Prompt Engineering
- Understanding Model Architecture (Transformers, GPT, BERT, etc.)
- Basic Prompt Mechanics and Syntax
- Techniques for Clear and Concise Prompts
- The Art of Question Framing
- Handling Ambiguity and Complexity in Prompts
Advanced Prompt Engineering Strategies
- Zero-shot, Few-shot, and Chain-of-thought Prompting
- Conditional Logic in Prompts
- Personalization and Contextualization Techniques
- Prompt Engineering for Specific Use Cases
Ethical AI Frameworks and Principles
- Principles of Responsible AI
- The Importance of Security and Ethics in AI
- Overview of AI Security Threats
- Ethical Considerations in AI Development
AI Security Challenges
- Understanding AI Vulnerabilities
- Data Privacy and Security in AI Systems
- Secure AI Architectures and Deployment Models
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