What You Will Learn

Generative AI has moved beyond the experimental phase and is actively reshaping core industries, from day-to-day business operations to software engineering, research, and automation systems. This intensive hands-on workshop bridges fundamental machine learning principles with production-ready deployments. Participants will master foundational neural network and transformer architectures before advancing to the modern LLM landscape, API integration rules, and high-performance prompt optimization strategies. Designed around actual enterprise constraints, this course focuses heavily on mitigation of hallucinations, Model Context Protocol (MCP) ecosystems, and secure multi-agent orchestration for real-world business deployment.

Course Objectives

• Explain core AI paradigms including machine learning, deep learning frameworks, neural networks, and transformer architectures.
• Compare the performance, latency, token limits, and economic trade-offs of major proprietary versus open-source LLMs.
• Integrate large language models into enterprise architectures via APIs while managing rate limits, streaming, and security.
• Design and refine high-quality prompts using advanced techniques like few-shot learning, chain-of-thought, and role prompting.
• Build resilient prompt pipelines structured to actively reduce hallucinations, systemic bias, and data exposure vulnerabilities.
• Understand the architecture of agentic workflows, Large Action Models (LAMs), and multi-agent cooperative systems.
• Implement rigorous operational guardrails, including the Model Context Protocol (MCP), human-in-the-loop validation, and trace logging.

Methodology

This program will be conducted via highly interactive conceptual lectures, practical prompt engineering laboratories, performance testing evaluations, step-by-step API integration reviews, and end-to-end enterprise deployment scenario walkthroughs.

Course Contents

• Module 1: AI Foundations
• Module 2: Modern LLM Landscape
• Module 3: Comparative Dimensions
• Module 4: Deployment & API Integration
• Module 5: Prompt Engineering Fundamentals
• Module 6: Prompt Engineering in Practice
• Module 7: Agentic AI and Multi-Agent Systems
• Module 8: Ethics, Governance & Risk Mitigation
• Module 9: Real-World Scenarios & Deployment Use Cases