Prompt Engineering & Practical AI Tools Professional Certificate

Generative AI tools such as ChatGPT, Claude, Gemini and Microsoft Copilot are changing how people write, research, analyse data and build software. Used well, they save hours every week; used carelessly, they produce confident errors, leak confidential information and damage trust. This course teaches you to use them professionally.

You will start by understanding how large language models (LLMs) actually work, including tokens, context windows and why they sometimes “hallucinate”. You will then master practical prompting techniques: clear instructions, roles and context, examples (few-shot prompting), step-by-step reasoning, structured outputs and systematic iteration. You will apply AI to everyday professional tasks such as writing reports and emails, analysing spreadsheets, researching with citations and creating images, then go further by building custom assistants, no-code automations and simple Python programs that call AI models through an API.

Throughout the course you will learn to protect data privacy, recognise prompt injection and bias, verify outputs and write an AI use policy. The capstone asks you to build a tested AI productivity toolkit for a South Sudanese NGO’s monitoring and communications team, a portfolio piece you can adapt for your own workplace.

No programming experience is required; the optional coding lessons use free Google Colab. Free versions of the main AI tools are enough to complete the course. How the course works: six modules, 23 lessons with 35 videos from respected sources including Anthropic, IBM Technology, 3Blue1Brown, Andrej Karpathy, GitHub, Microsoft and Leila Gharani, a hands-on activity in every lesson, a quiz after every module, a capstone project and a final certification examination. Most learners finish in 6 to 8 weeks at 4 to 5 hours per week.