Overview

The Applied Generative AI Specialization program is designed to prepare you for modern, in-demand roles across industries. Build expertise in generative AI, from foundational concepts to advanced LLM applications, Agentic AI, and MCP.

Syllabus

UCSB PaCE-AGS: Program Induction
Begin your learning journey with an online induction. Understand how this Applied Generative AI course provides comprehensive knowledge and elevates your career. Learn about all essential concepts in the generative AI domain that the program will cover.
UCSB PaCE-AGS: AI Literacy
Build a strong foundation in machine learning and generative AI by exploring key algorithms, including neural networks, GANs, and transformers. Learn how large language models support chatbots and discover image and video generation techniques. Under expert guidance, you will also practice with tools like ChatGPT and Stable Diffusion.
UCSB PaCE-AGS: Advanced Generative AI - Models and Architecture
Get introduced to generative models and understand how modern AI systems create content. Explore the architecture of large language models, learn how variational autoencoders work, and examine adversarial networks. You will also learn about attention mechanisms and transformers that power many advanced generative AI applications
UCSB PaCE-AGS: Advanced Generative AI - Building LLM Applications
Learn how to design LLM workflows using LangChain and use advanced prompt engineering techniques. Explore how to build LLM applications, work with retrieval-augmented generation, and fine-tune and customize large language models for specific use cases.
UCSB PaCE-AGS: Agentic AI Frameworks with Model Context and Tooling Protocols
Learn the basics of agentic AI. Design LLM agents with perception layers and cognitive engines, build workflows using LangGraph, and develop multi-agent systems with AutoGen. You will also learn how to create agent teams with CrewAI and implement the Model Context Protocol for unified integration and communication across different AI systems.
UCSB PaCE-AGS: Advanced Generative AI - Image Generation Capabilities
Understand how denoising enables high-quality image generation. Learn the role of autoencoders in generative AI, study contrastive learning techniques, and how shared embedding spaces help models understand relationships between text, images, and other data.
UCSB PaCE-AGS: Generative AI Governance
Understand why governance is critical in AI and explore the challenges companies face in responsibly managing AI systems. Learn key ethical principles, governance structures, risk management strategies for AI projects, and how governance is integrated into the AI lifecycle.
UCSB PaCE-AGS Capstone Project
Complete the Applied Generative AI course online Specialization program with a portfolio-worthy capstone project in which you will apply your newly acquired skills to work on an industry problem.

Electives

UCSB PaCE-AGS: Microsoft Azure AI Fundamentals - Generative AI
Understand the foundational role of large language models in generative AI and how Azure OpenAI Service provides access to advanced generative AI technologies. Learn how applications such as Copilot improve productivity, practice refining prompts and responses, and explore how Microsoft’s responsible AI principles support ethical and responsible AI development.
UCSB PaCE-AGS: Microsoft Copilot Foundations
Learn to build develop copilots using Microsoft Copilot Studio and understand how to publish bots and analyze their performance. Explore Azure AI Studio, build a copilot solution using retrieval-augmented generation, learn how to ground language models with relevant data, and create copilots using prompt flow.
UCSB PaCE-AGS: Industry Masterclass
Attend an online interactive masterclass led by industry experts and get insights about advancements in generative AI technologies and techniques.