IBM RAG and Agentic AI

Overview

Enhance your career in the high-growth field of artificial intelligence with advanced skills in generative AI. This program is designed to equip you with advanced techniques and tools such as prompt engineering, Agentic, and multimodal AI integration, enabling you to create sophisticated & context-aware AI applications.

This program will teach you advanced AI skills including developing efficient Retrieval-Augmented Generation (RAG) pipelines, integrating multimodal AI for text, image, and audio processing, as well as designing autonomous multiagent systems. The program will not only help you advance your career in AI but also provides a strong foundation for future career development in areas such as advanced data science, deep learning, and AI-driven automation.

You’ll also utilize the latest tools used by AI experts, including integrating external tools and APIs with AI agents, orchestrating complex workflows using LangChain and LangGraph, and frameworks like CrewAI, AG2, BeeAI, and Model Context Protocol (MCP). When you complete the full program, you’ll have a portfolio of projects and a Professional Certificate from IBM to showcase your expertise.

This program is ideal for software developers, machine learning engineers, data scientists, and anyone with Python programming experience who wants to level up their AI engineering game. Enroll today and master the latest generative AI technologies at the forefront of innovation!

Syllabus

• Introduction to RAG and Agentic AI
Overview of the Course
The Importance of Generative AI in the Current Landscape
Introduction to Key Concepts: RAG, Agentic AI, Multimodal AI
• Prompt Engineering
Basic and Advanced Techniques
Contextual Design and Optimization
Examples and Hands-on Exercises
• Retrieval-Augmented Generation (RAG) Pipelines
Understanding RAG
Designing Effective RAG Pipelines
Use Cases and Implementation Strategies
• Multimodal AI Integration
Introduction to Multimodal AI
Text, Image, and Audio Processing
Integrating Multiple Data Modalities in Applications
• Designing Autonomous Multiagent Systems
Fundamentals of Agentic AI
Creating and Managing Multiagent Workflows
Autonomy and Coordination in Agent Systems
• Tools and Frameworks
Overview of AI Development Tools
Utilizing LangChain and LangGraph for Workflow Orchestration
Introduction to CrewAI, AG2, BeeAI, and Model Context Protocol (MCP)
• Integrating External Tools and APIs with AI Agents
API Integration Techniques
Building API-Driven AI Solutions
Hands-on API Integration Exercises
• Orchestrating Complex Workflows
Workflow Design with LangChain and LangGraph
Advanced Application Scenarios
Case Studies and Real-world Applications
• Capstone Projects
Developing a Portfolio of AI Projects
Implementing Learned Skills in Real-World Scenarios
Presentation and Feedback Sessions
• Career Advancement in AI
Pathways to Entering Advanced Data Science and AI-Driven Automation
Building a Professional Network
Showcasing Your IBM Professional Certificate
• Conclusion and Future Directions in AI
Summary of Key Learning Points
Emerging Trends and Future Technologies in AI
Continued Learning and Professional Growth Opportunities

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Taught by

, Hailey Quach, IBM Skills Network Team, Rachael and Wojciech 'Victor' Fulmyk

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Subjects

Computer Science