TechMinds Tutorials — Curated Open-Source Learning
This page is the index for our curated learning resources. We collect GitHub repositories that we have personally used to learn, ship real projects, or teach others, and we add a short TechMinds note explaining what each one is good for and where it falls short.
We do not list tutorials we have not personally worked through. Every entry below has been opened, read, and (in most cases) built from. The list is updated when we find a repository that genuinely improves on an existing pick.
How we curate
A repository earns a place on this page by meeting three criteria:
- **We have used it.** Not "looked at the README" — actually worked through examples or shipped something with it.
- **It teaches a real skill.** Reference docs are great; we link to those separately in our [Recommends](/recommends/) page. This page is for *learning resources* — repositories you work through to acquire a skill.
- **It is actively maintained.** We remove repositories that have not seen a meaningful commit in 18 months unless they are reference-grade (for example, algorithm textbooks).
AI and machine learning
Anthropic Claude Cookbooks — LLM application patterns
Anthropic's official cookbook repository. Best for: developers building production LLM applications who want working examples of RAG, agent orchestration, prompt evaluation, and tool use patterns. The code is production-quality and uses the official SDK. Our team uses this as the first reference for any new Claude integration.
Where it falls short: Anthropic-specific. Most patterns transfer to other LLMs but the examples are Claude-only.
Difficulty: Intermediate to advanced. Assumes Python comfort.
Shubhamsaboo/awesome-llm-apps — Survey of LLM applications
A curated collection of LLM application examples covering chatbots, RAG systems, agent workflows, and multi-modal applications. Best for: surveying what is possible and finding inspiration for a new project. The 100+ examples span beginner to production-grade.
Where it falls short: Quality varies across the listed applications. Some are demo-grade only.
Difficulty: Beginner-friendly examples mixed with advanced.
Algorithms and data structures
krahets/hello-algo — Algorithm textbook with animations
The best Chinese-language algorithm learning resource currently available, with English translation in progress. Each algorithm is presented with a clear explanation, animated visualization, and runnable code in Python, Java, C++, Go, and several other languages. Best for: anyone learning algorithms from scratch, or anyone who wants a more visual learning experience than CLRS.
Where it falls short: Coverage is narrower than CLRS. Advanced topics (advanced graph algorithms, approximation algorithms) are not here.
Difficulty: Beginner-friendly.
jwasham/coding-interview-university — Interview prep study plan
A multi-month study plan for software engineering interviews. Best for: experienced engineers preparing for FAANG-style interviews who want a structured curriculum. The book list and timing recommendations are the most useful parts.
Where it falls short: Time commitment is significant. Plan for 3-6 months if you are starting from scratch.
Difficulty: Advanced.
Systems and infrastructure
donnemartin/system-design-primer — System design interview prep
A learning resource for system design interviews covering caching, load balancing, databases, message queues, and the architecture of well-known products. Best for: engineers preparing for senior or staff-level interviews, or anyone who wants to understand how large systems are built.
Where it falls short: Resource is several years old. Some recommendations (specific databases or tools) are dated.
Difficulty: Intermediate to advanced.
redis/redis source code — Production Redis source
The actual Redis source code with extensive comments. Best for: engineers who want to understand how a high-performance in-memory data store is implemented. The code is exceptionally well-written and commented.
Where it falls short: This is real production code, not a tutorial. Expect to spend weeks working through it.
Difficulty: Advanced. Requires solid C and systems knowledge.
jlevy/the-art-of-command-line — Command line fluency reference
A reference for command-line productivity on Linux and macOS. Best for: developers who want to be faster at the terminal. The section on text processing pipelines is worth the time alone.
Where it falls short: Not a tutorial — it is a reference you work through section by section as needed.
Difficulty: Beginner to intermediate.
Curated resource lists
MunGell/awesome-for-beginners — Beginner-friendly open source projects
A curated list of GitHub projects that are good first contributions for new open-source developers. Best for: developers making their first open-source pull requests. The projects listed have maintainers who are known to mentor first-time contributors.
Where it falls short: The list itself is maintained periodically. Some projects on it may be inactive by now.
Difficulty: Beginner-friendly.
aalhour/awesome-c-cn — C language resource list
A comprehensive list of C language resources, libraries, and frameworks. Best for: C developers looking for libraries or learning paths.
Where it falls short: Mostly Chinese-language resources. Less useful if you only read English.
Difficulty: All levels.
New entries in progress
We are currently testing the following and will add them when the team finishes working through them:
- A new LLM fine-tuning tutorial repository (under evaluation)
- A systems programming textbook with Rust examples (under evaluation)
- A performance engineering course repository (under evaluation)
Suggest a resource
If you maintain an open-source repository that meets the curation criteria above, see our Contact page for the submission process. We respond to genuine suggestions within 2 weeks. We do not accept payment for inclusion on this page.