> ## Documentation Index
> Fetch the complete documentation index at: https://stem-docs.intellectualpoint.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Resources and what's next
> Free courses, hands-on platforms, newsletters, open-source tools, and career paths to continue your AI and robotics journey.
## How to keep learning
**Time**: 11:40 AM to 12:15 PM
This week gave you a foundation. Here is how to keep building on it — all free or low-cost.
***
### Free courses
| Course | What you learn | Link |
| -------------------------------------- | ------------------------------------------------------------------------------- | ---------------------------------------------------------------- |
| **fast.ai** | Practical deep learning — build real models from day one, no math prerequisites | [course.fast.ai](https://course.fast.ai) |
| **Hugging Face NLP Course** | Transformers from scratch, tokenization, fine-tuning | [huggingface.co/learn](https://huggingface.co/learn) |
| **DeepLearning.AI Short Courses** | Focused topics: tool use, RAG, agents, fine-tuning | [deeplearning.ai](https://www.deeplearning.ai/short-courses/) |
| **Andrej Karpathy — GPT from scratch** | Builds a GPT model from zero in 2 hours (YouTube) | [youtube.com/@karpathy](https://www.youtube.com/@AndrejKarpathy) |
| **MIT OpenCourseWare 6.S191** | Introduction to deep learning (free university lectures) | [introtodeeplearning.com](http://introtodeeplearning.com/) |
Start with **fast.ai** if you want to build things immediately, or **Karpathy's YouTube** if you want to understand the math behind GPT.
***
### Hands-on practice
| Platform | What it offers | Cost |
| ----------------------- | ---------------------------------------------------------- | ------------------------------- |
| **Kaggle** | Free compute, datasets, competitions, community notebooks | Free |
| **Google Colab** | Free GPU for training small models, runs Jupyter notebooks | Free (paid GPU tiers available) |
| **Hugging Face Spaces** | Free GPU inference, host demos, share models | Free |
| **Replit** | Online IDE with AI features, deploy web apps | Free tier |
| **GitHub Codespaces** | Cloud development environments, 60 hours/month free | Free tier |
***
### Stay current
The AI field moves faster than any other area of technology. These sources will keep you up to date:
| Source | Format | Why it is useful |
| -------------------------- | ---------------------- | ---------------------------------------------------- |
| **Simon Willison's blog** | Long-form articles | Practical, skeptical analysis of new AI tools |
| **The Batch** by Andrew Ng | Weekly newsletter | Concise AI news digest every Wednesday |
| **Hacker News** | Community links | Real-time discussion of AI papers and products |
| **Papers With Code** | Research papers + code | Find state-of-the-art results with reproducible code |
| **r/LocalLLaMA** | Reddit community | Running models locally, hardware optimization |
***
### Open-source ecosystem
You can run models on your own hardware — no API key required:
| Tool | What it does |
| -------------------- | ------------------------------------------------------------ |
| **Ollama** | Run LLMs locally with one command (`ollama run llama3`) |
| **Hugging Face Hub** | Thousands of free, downloadable models |
| **LangChain** | Framework for building LLM applications with tool calling |
| **LlamaIndex** | Framework for connecting LLMs to your own data |
| **vLLM** | High-performance inference server for production deployments |
| **Whisper** | OpenAI's open-source speech-to-text (much better than Vosk) |
Most of these require more powerful hardware than a Pi Zero. A laptop with 16GB RAM can run small models. A desktop with a GPU can run larger ones. Cloud GPUs (Colab, Lambda, Vast.ai) work for everything.
***
### Robotics resources
| Resource | What it covers |
| ---------------------------------- | ---------------------------------------------------- |
| **Raspberry Pi Foundation** | Projects, learning paths, community |
| **ROS 2** (Robot Operating System) | The industry standard for advanced robotics software |
| **Arduino** | Microcontroller projects, sensors, actuators |
| **Adafruit Learning System** | Electronics tutorials with great documentation |
| **Boston Dynamics blog** | Advanced robotics research and demos |
***
### Career paths
These fields all use what you learned this week:
Build and deploy machine learning models and AI systems. Companies: OpenAI, Google, Meta, Anthropic, and thousands of startups.
Design and program robots for manufacturing, healthcare, space exploration, and defense. Companies: Boston Dynamics, iRobot, NASA JPL.
Study how to make AI systems safe, aligned, and trustworthy. Growing field at Anthropic, DeepMind, MIRI, and universities.
Build secure AI and robotics systems for national security. Companies: Anduril, Palantir, Shield AI, and government labs.
Analyze data, build models, and extract insights. Used in every industry from finance to healthcare to sports.
Create technology that makes the world more accessible for people with disabilities. Vision AI, speech interfaces, and assistive robotics.
***
### What to do this week
Your Raspberry Pi and robot kit are yours to keep experimenting with. Try modifying the programs from this week.
Do not try to learn everything at once. Pick **one** course from the list above and commit to finishing it.
The best way to learn is to build something you care about. A chatbot for your homework? A camera that identifies plants? A voice-controlled lamp? Pick something small and finish it.
Find a Discord server, subreddit, or local meetup. Learning with other people is faster and more fun than learning alone.