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Section 1: Introduction to Generative AI and Large Language Models

What is Generative AI?

Understanding Large Language Models (LLMs)

Section 2: Foundation Models and Their Capabilities

Characteristics of Foundation Models

Common Use Cases for Foundation Models

Section 3: Prompt Engineering Paradigms

Basics of Prompt Engineering

Applying Foundational Prompting Techniques

Section 4: Advanced Concepts Made Simple - RAG and Agentic Systems

Introduction to Retrieval-Augmented Generation (RAG)

Basics of Autonomous Agent Workflows

Course Quizzes

Quiz 1: Fundamentals of Generative AI and LLMs

Quiz 2: Foundation Models and Use Cases

Quiz 3: Prompt Engineering Basics

Quiz 4: Applying Prompting Techniques

Quiz 5: RAG and Agentic Systems

Course Feedback

Post-Course Survey

Welcome to 'Generative AI Fundamentals: LLMs, Prompt Engineering, and Agentic Systems. ' In today's rapidly evolving digital landscape, Generative Artificial Intelligence is no longer just a buzzword—it is a transformative technology reshaping how we work, create, and solve problems.

Welcome to 'Generative AI Fundamentals: LLMs, Prompt Engineering, and Agentic Systems.' In today's rapidly evolving digital landscape, Generative Artificial Intelligence is no longer just a buzzword—it is a transformative technology reshaping how we work, create, and solve problems. This comprehensive, beginner-friendly course is designed to demystify the complex world of AI, breaking down advanced concepts into easily digestible lessons. Whether you are a professional looking to boost your productivity, a business leader exploring AI integration, or simply a curious learner, this course provides the foundational knowledge you need to navigate the AI revolution confidently. 

Throughout this course, you will explore the inner workings of Large Language Models (LLMs) and Foundation Models, understanding how they generate human-like text, images, and code. You will learn the critical skill of Prompt Engineering, mastering techniques like zero-shot and few-shot prompting to communicate effectively with AI and extract high-quality, relevant outputs. Furthermore, we will simplify advanced paradigms such as Retrieval-Augmented Generation (RAG) and Autonomous Agentic Systems, showing you how AI can be connected to external knowledge bases to reduce hallucinations and automate complex, multi-step workflows. By the end of this journey, you will possess a robust understanding of Generative AI capabilities, limitations, and practical applications, empowering you to leverage these cutting-edge tools in your everyday life and career.

Generative AI Fundamentals: LLMs, Prompt Engineering, and Agentic Systems

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            <p>The rapid evolution of artificial intelligence has fundamentally transformed the technological landscape, shifting from traditional analytical systems to highly capable generative models. This course provides a comprehensive exploration of Generative AI, establishing a robust foundation in the mechanics and applications of Large Language Models (LLMs). Participants will examine the core differences between conventional AI and generative systems, exploring how these models predict and generate human-like text, images, and code. Furthermore, the curriculum delves into the architecture of foundation models, elucidating how a single, highly versatile model can be adapted across multiple distinct tasks and industries to drive innovation in content creation, customer support, and data summarization.</p>

<p>Beyond theoretical understanding, this program emphasizes practical application through rigorous instruction in prompt engineering paradigms. Learners will acquire the skills necessary to construct highly effective prompts, utilizing foundational techniques such as zero-shot and few-shot prompting, role-playing, and constraint implementation to optimize AI outputs. As the course progresses, it demystifies advanced concepts, introducing Retrieval-Augmented Generation (RAG) as a critical method for reducing AI hallucinations and connecting models to external, up-to-date knowledge sources. Finally, the curriculum transitions into the mechanics of autonomous agent workflows, distinguishing standard conversational chatbots from sophisticated agentic systems capable of planning and executing complex, multi-step digital tasks. Through structured modules and comprehensive assessments, participants will develop a multifaceted understanding of modern generative AI technologies.</p>
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