This repository provides a comprehensive, free guide for individuals with no prior background in programming, math, or machine learning to start and advance their skills in AI and ML. It curates a structured learning path using a wide array of free online resources, including YouTube videos, courses, articles, and podcasts, with optional paid resources for deeper understanding.

How It Works

The guide follows a top-to-bottom, self-paced learning approach, emphasizing practical application and continuous learning. It breaks down complex topics like neural networks, transformers, and LLMs into digestible segments, recommending specific free video series and courses from reputable sources like 3Blue1Brown, Welch Labs, Stanford, and MIT. The curated list also includes resources for building foundational math and coding skills in Python, essential for ML practitioners.

Quick Start & Requirements

• Install/Run: No specific installation is required as it's a curated list of learning resources.
• Prerequisites: Basic computer literacy. Access to the internet is essential. Optional: Python environment for coding practice.
• Resources: Links to free YouTube videos, courses, articles, podcasts, communities, and cheat sheets are provided. Optional paid courses and books are also listed.
• Setup Time: Minimal, primarily involves browsing and selecting resources.
• Links: YouTube video overview, GitHub Repository

Highlighted Details

• Extensive coverage of Large Language Models (LLMs), including training, fine-tuning, and building applications with tools like LangChain and vector databases.
• Dedicated sections for individuals without math or coding backgrounds, offering tailored learning paths.
• Emphasis on practical learning through Kaggle competitions, project-based courses, and community engagement.
• Inclusion of AI ethics and career advice, such as job interview preparation.

Maintenance & Community

• Maintained by louisfb01, who is active on YouTube and podcasts.
• Open to resource suggestions via email and social media tags.
• The repository is regularly updated.
• Links to Discord servers and Reddit communities for AI enthusiasts are provided.

Licensing & Compatibility

• The repository itself is not software; it's a curated list of links. The licensing of the linked resources varies, with most being free to access.

Limitations & Caveats

• While the guide emphasizes free resources, some recommended courses and books are paid, and affiliate links are used.
• The effectiveness of the self-paced learning path depends heavily on individual motivation and discipline.