100 topics · 5 tracks

AI Trainings Map

A topic map organized by training direction. Think of each track as a compass — it points you to what to look for, not a fixed list of courses.

Generative AI & everyday productivity

Easy-to-apply skills for any profession.

  1. 01Effective prompt writing (Prompt Engineering) for beginners
  2. 02Applying ChatGPT / Google Gemini / Claude to daily tasks
  3. 03AI tools for writing, editing, and content creation (Copywriting)
  4. 04Integrating AI assistants into office suites (Microsoft Copilot, Google Workspace)
  5. 05Image generation for business and creativity (Midjourney, DALL-E, Stable Diffusion)

AI for business, marketing & sales

For executives, marketers, and growth teams.

  1. 21Generating social media content plans and posts with AI
  2. 22Using AI in SEO (search engine optimisation) strategies
  3. 23Optimising digital ad campaigns (Facebook, Google Ads) with AI
  4. 24Automated video content creation and editing (Sora, Runway, HeyGen)
  5. 25Creating and using virtual AI influencers (Avatars)

AI in education, science & specialised industries

For teachers, lecturers, students, and sector specialists.

  1. 46AI tools for teachers: lesson plans and quiz creation (MagicSchool, Brisk)
  2. 47Personalised learning: AI as an individual tutor (Khanmigo)
  3. 48Academic writing ethics and how AI detectors work
  4. 49Accelerating research: literature review with Elicit or Consensus
  5. 50AI in medicine: diagnostic assistants and medical image analysis

Technical AI training & programming

For developers, data scientists, and IT specialists.

  1. 71Programming with AI assistants (GitHub Copilot, Cursor, Replit)
  2. 72Introduction to data science and Python programming
  3. 73Machine learning for beginners
  4. 74Deep learning and neural networks
  5. 75Integrating Large Language Model (LLM) APIs into your apps

Advanced future engineering & philosophy

Top-level concepts, innovation, and the future of AI.

  1. 91Designing autonomous AI agent systems
  2. 92Managing multimodal models (text + image + audio + code)
  3. 93AI model interpretability and transparency (Explainable AI - XAI)
  4. 94Quantum machine learning
  5. 95Robotics: programming AI-driven physical robots