Learn AI

Learning AI skills simplifies many work-related tasks and opens up new career opportunities – across almost all professional fields. Key competencies include:

  • Knowing the right AI tools
  • Using AI effectively and purposefully (prompting)
  • Basic knowledge of ethics and data protection
  • The ability to apply AI solutions meaningfully in one’s own daily work

Top articles:

Learn to program LLMs and chatbots – The best online courses

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Developers who can code with large language models (LLMs) and AI are in high demand on the job market. And it’s not hard to get started, because there are numerous courses that can help you expand your skills. Here’s an always up-to-date overview of the most important online courses on LLMs, AI, chatbots, Python and more.

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Flowise & Langflow – create generative AI tools yourself without programming knowledge

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📖 This article is part of our AI Agents guide. Read the full guide →

With Flowise and Langflow, you can create generative AI applications via drag & drop without the need for developer skills. This helps with quick prototyping and easy testing. We present the most popular free AI prototyping tools.

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PyData Global – These are the most important data and AI topics

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PyData Global will take place on December 6-8, 2023. Here, the most important data and AI topics will be taught practically with Python and many other open source technologies. We provide a practical overview. PyData Global brings together data engineers, scientists and practitioners Key Insights / TL;DR What: PyData Global is a conference on the … Read more

Prompt Engineering: The Complete Guide to Writing Better AI Prompts (2026)

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TL;DR

Prompt engineering is the skill of writing structured instructions that get AI models to deliver accurate, useful results. In 2026, the discipline has evolved from simple “tricks” to a core professional skill used across industries.

  • Core principle: Structure beats length. A clear 3-line prompt outperforms a vague 30-line one
  • 5-step framework: Role, Task, Context, Format, Example — works across all major models
  • Key shift in 2026: The focus has moved from “prompt engineering” to “context engineering” as models got better at reading intent
  • Model differences matter: Claude responds best to XML tags, GPT-5 to conversational style, Gemini to direct, short instructions

📖 This article is part of our comprehensive ChatGPT guide. Read the full guide →

Bottom Line: You don’t need to be a developer. Anyone who works with AI benefits from learning these techniques. The difference between a mediocre and a great prompt is usually 30 seconds of additional thought.

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