# Courses & Training

## 🧪 Beginner-Friendly Tutorials & Courses

| Source                 | Type            | Description / Link                                                                                        |
| ---------------------- | --------------- | --------------------------------------------------------------------------------------------------------- |
| 🔵 3Blue1Brown         | YouTube         | Visual math & neural network intuition – [*Neural Networks*](https://www.youtube.com/watch?v=aircAruvnKk) |
| 🎥 StatQuest           | YouTube         | Step-by-step explanations of ML/statistics with analogies                                                 |
| 📘 Machine Learnia     | YouTube (FR/EN) | French & English intros to ML, DL, and projects                                                           |
| 🧠 freeCodeCamp        | Full Course     | [*6h crash course*](https://www.youtube.com/watch?v=c36lUUr864M) on PyTorch & Deep Learning               |
| 💻 Google Crash Course | Website         | [*Google ML Crash Course*](https://developers.google.com/machine-learning/crash-course) – hands-on        |

***

## ⚙️ Intermediate Level Resources (for those with basics)

| Source             | Type       | Description / Link                                                                                      |
| ------------------ | ---------- | ------------------------------------------------------------------------------------------------------- |
| 🎥 StatQuest       | YouTube    | Advanced algorithms explained clearly                                                                   |
| 📘 DeepLearning.AI | Coursera   | [*Neural Networks Specialization*](https://www.coursera.org/specializations/deep-learning) by Andrew Ng |
| 📗 Hugging Face    | Web Course | [*Transformers Course*](https://huggingface.co/learn/nlp-course/) – Colab-based NLP                     |
| 🧪 PyTorch Blitz   | Tutorial   | [*60-Min Blitz*](https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html)                 |
| 🧠 FastAI          | Web Course | [*Practical Deep Learning*](https://course.fast.ai/) – code-first, project-based                        |

***

## 🧠 Expert-Level Learning

| Source              | Type      | Description / Link                                                                                 |
| ------------------- | --------- | -------------------------------------------------------------------------------------------------- |
| 🧠 Steve Brunton    | YouTube   | Applied math for ML/AI – SVD, Koopman theory, control theory                                       |
| 🧪 Formation Fiddle | GitHub/YT | Deep math experiments, model introspection                                                         |
| 📘 Full Stack DL    | Bootcamp  | [*Full Stack Deep Learning*](https://fullstackdeeplearning.com/) – real-world training, deployment |
| 🧬 Deep RL Bootcamp | Stanford  | [*Course Materials*](https://deep-rl.net/) – advanced RL lectures, code                            |

***


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://doc.guidry-cloud.com/02-training-resources.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.