
Personal Effectiveness: Time Management, Goals, Efficiency

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This beginner course is aimed at developers, DevOps engineers, technical writers and anyone who writes notes or documentation. Its premise is that Markdown now matters well beyond README files, because AI chat tools answer in it and coding agents read their instructions from it.
The course begins with everyday syntax: headings, emphasis, lists, tables, code, links and images. It then moves into VS Code as a Markdown workbench, covering GitHub Flavored Markdown extras, Mermaid diagrams, KaTeX maths and YAML front matter. The AI section looks at structuring prompts, writing agent instruction files, and cleaning up output with markdownlint. The final part applies Markdown to Obsidian, Hugo and Ghost.
A single small Python notes project runs through the new sections, so each lecture builds on the one before. Downloadable handouts summarise each lecture.
Useful for writers who want Markdown to serve notes, documentation and AI work alike.
Markdown is the language of technical writing today. README files, documentation sites, note-taking apps, static site generators and blogs all use it. And now AI tools do too: every chat assistant answers in Markdown, and AI coding agents read their instructions from Markdown files.
Whether you are a developer, a DevOps engineer, a technical writer, or anyone who writes notes and docs, this course was created specifically for you.
The course is divided into four parts:
1. Markdown basics. Headings, bold and italics, lists, tables, code, links and images: the syntax you will use every day.
2. Beyond the basics, in VS Code. We set up VS Code as a Markdown workbench with a live preview and the Outline view. Then we use GitHub Flavored Markdown (task lists, aligned tables, autolinks, footnotes and alerts), draw diagrams with Mermaid, write math with KaTeX, and add YAML front matter, the metadata that Hugo, Obsidian and documentation sites read.
3. Markdown and AI. Why AI assistants answer in Markdown, how to structure your prompts with it, how to write the instruction files (AGENTS and CLAUDE files) that tell AI coding agents how to work on your project, and how to clean up AI-written Markdown with markdownlint.
4. Markdown at work. Three of the best-known applications built on Markdown: Obsidian for notes, Hugo for blazingly fast static websites, and Ghost for blogs.
One running example, a small Python notes project, carries through the new sections, so every lecture builds on the last one. Every new lecture comes with a downloadable handout that summarizes it.
The course stays practical and to the point. I know how precious your time is, so I only give you what you need to master the skill.
Feel free to watch the free preview lectures. If you like what you see, hit the Enroll button. You have nothing to lose: Udemy gives you a 30-day money-back guarantee. I'll be waiting for you in lecture one.
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Tracking since 15 Nov — not enough history yet to tell you whether today's price is any good. Watch the course and we'll tell you when it drops.
This is what we recorded in US pricing — not every price this course has ever had, and prices differ by country.
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