Duration of the online course: 12 hours and 40 minutes
4.72
(64)
Artificial intelligence is no longer a distant concept reserved for research labs; it powers recommendations, language tools, image recognition, and decision-making systems used every day. This free online course is designed to help you understand how AI actually works under the hood, connecting core theory with practical thinking you can apply to real problems. If you want to move from curiosity to capability, you will develop a solid foundation in the main approaches that drive modern intelligent systems.
You will start by learning what AI is and how to frame problems in a way machines can solve. From there, you will explore how an agent can search for solutions, represent knowledge about the world, and make decisions when information is incomplete or uncertain. These ideas form the backbone of many real products, where computers must choose actions efficiently, balance trade-offs, and update beliefs based on evidence.
As you progress, the course shifts toward the methods that allow machines to improve with experience. You will grasp the intuition behind optimization and why it is central to training effective models. You will also dive into machine learning, focusing on supervised learning as a practical pathway to building predictive systems. Along the way, you will strengthen your reasoning with targeted exercises that reinforce key concepts in probability, local search behavior, and model evaluation.
You will then step into neural networks and the fundamentals that make them so powerful, including the building blocks used in vision tasks such as convolution. Finally, you will learn how AI approaches language, tackling goals and techniques within natural language processing that aim to help machines interpret and generate human communication. By the end, you will be able to speak confidently about the major pillars of AI and approach new tools and frameworks with clarity, whether you are preparing for a tech role, enhancing your programming portfolio, or simply building future-proof skills.
Video class: Introduction - CS50's Introduction to Artificial Intelligence with Python 2020
01m
Video class: Search - Lecture 0 - CS50's Introduction to Artificial Intelligence with Python 2020
1h49m
Exercise: _What is artificial intelligence?
Video class: Knowledge - Lecture 1 - CS50's Introduction to Artificial Intelligence with Python 2020
1h47m
Exercise: _What are knowledge-based agents in artificial intelligence?
Video class: Uncertainty - Lecture 2 - CS50's Introduction to Artificial Intelligence with Python 2020
1h54m
Exercise: What is an important rule in probability theory?
Video class: Optimization - Lecture 3 - CS50's Introduction to Artificial Intelligence with Python 2020
1h44m
Exercise: What is a key characteristic of local search algorithms?
Video class: Learning - Lecture 4 - CS50's Introduction to Artificial Intelligence with Python 2020
1h45m
Exercise: What is the main idea behind supervised machine learning?
Video class: Neural Networks - Lecture 5 - CS50's Introduction to Artificial Intelligence with Python 2020
1h41m
Exercise: What is the role of a kernel matrix in image convolution?
Video class: Language - Lecture 6 - CS50's Introduction to Artificial Intelligence with Python 2020
1h54m
Exercise: What is a significant task within natural language processing aimed at making AI understand human languages?
12 hours and 40 minutes of online video course
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Course comments: Artificial intelligence
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ZEWDU TECHAN DEGNE
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CHANDAN KUSHWAHA
AWESOME
Ashish joon
best one
Baisampayan Chatterjee
Very good