Generative AI and Agentic AI

What you'll learn

• Explain the evolution of AI and core concepts behind generative and agentic systems
• Differentiate major generative models (GANs, VAEs, autoregressive, diffusion) and their use cases
• Design and train basic generative models and evaluate their outputs
• Build and configure autonomous agents that perceive, plan, and act in dynamic environments
• Apply reinforcement learning algorithms to train agent behaviors
• Integrate generative models into content-creation pipelines
• Assess ethical, safety, and societal implications of generative and agentic AI
• Complete hands-on projects deploying generative models and agents
• Plan for future trends and research directions in generative and agentic AI

Prerequisites

Basic Python programming and foundational machine learning knowledge (neural networks, probability); familiarity with calculus and linear algebra is helpful.

Skills you'll gain

• Generative model design
• Deep learning
• Reinforcement learning
• Prompt engineering
• Agent architecture and planning
• Model evaluation and validation
• Ethical AI reasoning
• Data preprocessing and augmentation
• Experimentation and hyperparameter tuning
• Prototype deployment