1. Understand AI Concepts and History

• Define AI and differentiate between narrow AI, general AI, and superintelligent AI.
• Trace the historical evolution of AI and key milestones.
• Explain the Turing Test and other benchmarks for AI intelligence.

2. Explore Core AI Techniques

• Describe machine learning (ML) vs. rule-based systems.
• Compare supervised, unsupervised, and reinforcement learning.
• Understand search algorithms (e.g., A*, minimax) in problem-solving.

3. Learn Machine Learning Fundamentals

4. Introduction to Neural Networks & Deep Learning

5. AI in Real-World Applications

• Analyze AI use cases in industries (healthcare, finance, autonomous vehicles).
• Discuss AI-powered tools (ChatGPT, recommendation systems, facial recognition).
• Explore AI ethics, bias, and fairness in algorithmic decision-making.

6. Natural Language Processing (NLP) Basics

7. AI Ethics and Societal Impact

• Debate job displacement, privacy concerns, and AI regulation (e.g., GDPR, AI Act).
• Identify bias in datasets and mitigation strategies.

1. Understand AI Concepts and History

• Define AI and differentiate between narrow AI, general AI, and superintelligent AI.
• Trace the historical evolution of AI and key milestones.
• Explain the Turing Test and other benchmarks for AI intelligence.

2. Explore Core AI Techniques

• Describe machine learning (ML) vs. rule-based systems.
• Compare supervised, unsupervised, and reinforcement learning.
• Understand search algorithms (e.g., A*, minimax) in problem-solving.

3. Learn Machine Learning Fundamentals

4. Introduction to Neural Networks & Deep Learning

5. AI in Real-World Applications

• Analyze AI use cases in industries (healthcare, finance, autonomous vehicles).
• Discuss AI-powered tools (ChatGPT, recommendation systems, facial recognition).
• Explore AI ethics, bias, and fairness in algorithmic decision-making.

6. Natural Language Processing (NLP) Basics

7. AI Ethics and Societal Impact

• Debate job displacement, privacy concerns, and AI regulation (e.g., GDPR, AI Act).
• Identify bias in datasets and mitigation strategies.

Why Take This Course?

• Gain a strong foundation in AI before diving into advanced topics.
• Learn practical skills with industry-relevant tools.
• Understand AI’s societal impact and ethical considerations.