Roadmap to Learning Artificial Intelligence

Introduction

• Context & Background: Started AI journey in 2013, 10 years of experience, freelance data scientist, YouTuber with 25,000+ subscribers.
• Importance of AI: Expected market growth to nearly $2 trillion by 2030.
• Resource Promise: Free roadmap with training videos and instructions will be provided at the end.

AI Learning Path Considerations

• AI Hype: Many new entrants due to market growth and pre-trained models from OpenAI.
• Common Misunderstandings: AI encompasses more than just chatbots or automation tools.
• AI Subfields: Machine Learning, Deep Learning, Data Science.
• No-Code vs. Code: Evaluate if you want to delve into coding or use no-code tools. No wrong choice but be aware of pros and cons.

Step-by-Step AI Learning Roadmap

Step 1: Set Up Work Environment

• Language: Python
• Tools: VS Code recommended
• Goal: Comfortable setup on your computer for running Python code.

Step 2: Learn Python

• Focus: Basics of programming transitioning quickly to Python specifics.
• Libraries: Numpy, Pandas, Matplotlib – essential for data manipulation, cleaning, visualization.

Step 3: Basics of Git and GitHub

• Importance: Helpful for accessing and collaborating on code, especially from tutorials and projects.

Step 4: Work on Projects & Build Portfolio

• Learning by Doing: Reverse engineering, exploring projects to identify interests (Computer Vision, NLP, etc.).
• Resources: Kaggle for competitions, GitHub repositories for example projects, Project Pro for end-to-end project solutions.

Step 5: Specialization & Sharing

• Goal: Choose a focus area within AI, Data Science, or ML.
• Knowledge Sharing: Blogs, articles on Medium/Towards Data Science, YouTube videos to strengthen understanding.

Step 6: Continue Learning & Upskilling

• Identify Gaps: Based on specialization, focus on math/statistics for ML/Data Science, or software engineering skills for LLMs.

Step 7: Monetize Your Skills

• Pathways: Jobs, freelancing, or building products.
• Real-World Pressure: Pushes for deeper learning and innovation.

Additional Tips

• Community: Surround yourself with like-minded individuals, join groups like 'Data Alchemy' for sharing news, tips, and resources.
• Free Resource: Complete roadmap and additional resources available through the 'Data Alchemy' group.