[NEW] AI Foundations for Technical Professionals

Course Overview

This course provides a comprehensive understanding of modern generative AI technologies including large language models (LLMs), tokens, retrieval-augmented generation (RAG), AI agents, the Model Context Protocol (MCP), and AI security. It is designed for technical professionals who need to explain, evaluate, and implement AI systems without requiring coding skills.

Through focused lectures, lightboard explanations, and live demos, learners will build a complete picture of the AI stack, from how models work internally to deploying and securing AI agents in real-world environments.

Key Takeaways

• Understand how generative AI and LLMs operate, including tokens, parameters, context windows, and reasons for hallucinations.
• Estimate AI workload costs and select appropriate models and deployment methods (hosted API vs self-hosted).
• Develop advanced prompt engineering skills and apply retrieval-augmented generation techniques.
• Learn the architecture and operation of AI agents, including loops, tool calling, subagents, orchestrators, and human-in-the-loop controls.
• Gain practical knowledge of the Model Context Protocol (MCP) and orchestration frameworks like LangChain and LangGraph.
• Identify and mitigate key AI security risks such as prompt injection and over-privileged agents.

Prerequisites

• No prior AI experience required; familiarity with ChatGPT or Claude is helpful but not necessary.
• No coding or math required; concepts are explained with plain-language analogies.
• General technical literacy is needed; understanding what an API is suffices.
• A computer and web browser are required to complete exercises.

Target Learners

• Solution engineers, sales engineers, and technical account managers involved in AI demos and customer discussions.
• DevOps, platform, and cloud engineers integrating AI features and agents.
• IT professionals, sysadmins, and support leads evaluating or supporting AI tools.
• Developers and architects seeking a big-picture understanding of AI without extensive coding.
• Technical product and engineering managers needing fluency in AI concepts for planning and reviews.