The course begins with Python Programming Basics for Artificial Intelligence, focusing on essential programming concepts like loops, functions, and data structures. You'll write clean Python code, preparing you to develop practical AI applications. The journey continues with data science essentials, where you'll explore tools such as Pandas, NumPy, and Matplotlib for data manipulation, cleaning, and visualization, critical skills for any AI engineer. Next, the course delves into the mathematics that underpin machine learning and AI, breaking down linear algebra, calculus, probability, and statistics in an intuitive and practical manner. You'll apply these mathematical concepts to build stronger analytical skills, enabling you to better understand and create AI models. The final phase introduces machine learning, where you will learn algorithms like linear regression, logistic regression, and k-NN using Scikit-learn. You'll gain hands-on experience building and evaluating models. Throughout the course, you’ll work on projects and exercises that reinforce the concepts you learn, preparing you for a successful career in AI. Whether you're looking to become a machine learning engineer, data scientist, or AI developer, this course will equip you with the skills to advance in the field of artificial intelligence.