Organized by DotPy, this session builds a strong conceptual foundation in Artificial Intelligence and Machine Learning. It aims to demystify AI concepts, clarify the differences between AI, Machine Learning, and Deep Learning, and help participants understand how modern AI systems work.

The session begins with an introduction to Artificial Intelligence, followed by a clear comparison between AI, Machine Learning, and Deep Learning. Participants will explore the different types of AI by capability, including Narrow AI, General AI (conceptual), and Super AI (future vision).

It then dives into Machine Learning fundamentals, covering supervised, unsupervised, semi-supervised, and reinforcement learning, supported by real-world examples. Common Machine Learning algorithms—such as Linear Regression, Logistic Regression, K-Means, and Decision Trees—are introduced at a high level, alongside an intuitive explanation of how models learn from data.

The session concludes by positioning Generative AI within the broader AI and Machine Learning landscape.

🎯 Outcome:
Participants will gain a clear understanding of AI fundamentals and Machine Learning concepts, preparing them for more advanced AI topics and applications.