Build Your AI Foundation with Python, Data Science, Math & Machine Learning Basics
Sub Category
- Data Science
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Objectives
- Write clean Python code for AI applications using variables, loops, functions, and OOP
- Analyze and manipulate data with Pandas and NumPy
- Visualize datasets using Matplotlib and Seaborn
- Understand core math concepts like linear algebra and calculus for AI
- Apply probability theory and statistics to AI problem-solving
- Explain how machine learning models work and are trained
- Build and evaluate basic ML models using Scikit-learn
- Develop a solid foundation to pursue advanced AI and ML topics
Pre Requisites
- No prior programming or AI experience is required — this course is beginner-friendly
- A computer (Windows, macOS, or Linux) with internet access
- Willingness to learn and experiment with new concepts
- Basic familiarity with high school math (algebra and arithmetic is helpful but not mandatory)
- Ability to install software like Python, Jupyter Notebook, and required libraries (we’ll guide you step-by-step)
- Curiosity about how AI works and a passion for problem-solving
- A commitment to completing lessons and hands-on exercises
- Optional: A notebook or digital note-taking tool to jot down key ideas and formulas
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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