AI for IT & Data Professionals
Generative AI is changing IT and data roles, and develop practical skills to use AI for coding, data work, automation and enterprise use cases.
About this course
Course overview: Learn how Generative AI is changing IT and data roles, and develop practical skills to use AI for coding, data work, automation and enterprise use cases. Module 1 — AI & Generative AI Foundations Understand AI, Machine Learning, Generative AI and Large Language Models. Learn how LLMs process prompts, context and generate responses. Explore where GenAI fits into modern IT and data workflows. Module 2 — Prompt Engineering for Professionals Learn practical prompting techniques for technical and business tasks. Use context, examples, constraints and structured outputs effectively. Build reusable prompts for everyday professional workflows. Module 3 — AI for Developers & IT Professionals Use AI for coding, debugging, testing and code explanation. Generate technical documentation, requirements and solution ideas. Learn where AI coding assistants help—and where human validation matters. Module 4 — AI for Data Professionals Use AI to write, understand and optimize SQL. Accelerate Python, data analysis and Data Engineering tasks. Use AI to understand schemas, transformations and data-quality issues. Module 5 — RAG & Enterprise AI Fundamentals Understand embeddings, vector databases and semantic search. Learn how Retrieval-Augmented Generation connects LLMs with enterprise knowledge. Explore document assistants and enterprise search use cases. Module 6 — Building AI-Powered Solutions Understand models, APIs, prompts, data and tools in an AI application. Learn the basic architecture of enterprise AI solutions. Build a simple AI-powered application or workflow. Module 7 — Responsible AI & Enterprise Adoption Understand privacy, security, hallucinations and data leakage risks. Learn the basics of AI governance and responsible AI. Explore practical considerations for adopting AI inside organizations. Module 8 — Hands-on AI Project Identify a real IT or data problem that can benefit from AI. Design and build a working AI-powered solution. Present the architecture, workflow and business value of the solution.