Artificial Intelligence Learning Roadmap

Introduction

• Roadmap to learn AI from scratch
• Presenter: 10 years of experience in AI, data science, and freelancing
• YouTube Channel: Over 25,000 subscribers
• Free resource available at the end of the video

AI Market Context

• AI market expected to grow significantly by 2030
• Introduction of pre-trained models by OpenAI makes entry easier
• Differentiates between using no-code tools vs. learning deep AI principles
• AI is a broad term encompassing machine learning, deep learning, data science

Learning Path (7 Steps)

1. Set Up Work Environment

• Python is the primary language for AI and data science
• Importance of setting up a local environment on your computer
• Recommended tools: VS Code for code editing

2. Learn Python Basics

• Focus on programming fundamentals first, then transition to Python
• Key Python libraries for AI and data science:
  • Numpy
  • Pandas
  • Matplotlib
• Skills in data manipulation and visualization are crucial

3. Understand Git and GitHub

• Importance of version control from the beginning
• Familiarize with basic GitHub functionalities like cloning
• Many learning resources and code examples shared via GitHub

4. Work on Projects and Build Portfolio

• Use Git and GitHub for downloading and reverse-engineering projects
• Explore different fields within AI to identify personal interest areas
• Suggested platforms: Kaggle for machine learning competitions, GitHub repositories

5. Pick Specialization and Share Knowledge

• Choose a specific focus area within AI or data science
• Start sharing your knowledge through blogs, articles (Medium, Towards Data Science), or YouTube
• Helps in reinforcing your own learning by teaching others

6. Continuous Learning and Upskilling

• Focus on areas identified as gaps in your knowledge
• Suggested areas of study:
  • Math and statistics for machine learning and data science
  • Software engineering for working with APIs and building applications
• Learning paths are unique and should be tailored to individual goals

7. Monetize Your Skills

• Options: job, freelancing, or building a product
• Real learning is in applying your skills under pressure
• Essential to push yourself by working on real-world challenges

Bonus Tips

Surround Yourself with Like-minded Individuals

• Join communities and groups to share ideas and tips
• Announcement: Free group called Data Alchemy
• Benefits: Complete roadmap, additional courses, resources, and networking opportunities