Fundamentals of AI, Machine Learning, and Python Programming

Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Embark on a transformative learning experience designed to equip you with a robust understanding of AI, machine learning, and Python programming. This course begins with a thorough introduction to artificial intelligence and machine learning, demystifying the core concepts and exploring how algorithms and data-driven techniques empower computers to learn and adapt. As you progress, you'll delve into the architecture of deep learning and neural networks, grasping how these advanced structures mimic human cognition to process complex data and make accurate predictions. Transitioning from theory to practical application, the course guides you through setting up your development environment with Anaconda, laying the groundwork for efficient coding and package management. You'll then immerse yourself in Python programming, mastering flow control mechanisms, data structures, and functions. The journey continues with an exploration of essential Python libraries such as NumPy, Matplotlib, and Pandas, providing you with the tools to handle data manipulation and visualization effectively. The latter part of the course focuses on advanced AI topics, including the installation and application of deep learning libraries like TensorFlow and PyTorch. You'll learn about the fundamental structures of artificial neurons and neural networks, and the crucial roles of activation functions, loss functions, and optimizers in training models. Through hands-on projects, such as building regression models for house price prediction and binary classification models for heart disease prediction, you'll apply your knowledge to real-world scenarios, reinforcing your learning and enhancing your practical skills. This course is designed for as