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Introduction to Machine Learning & AI

In Lesson 1 you will be introduced to the wonderful world of AI, specifically machine learning. By the end of lesson 2 you would have created a super clever "self learning" chat bot using lists (scratch) and in Lesson 3, have a go at being Elon Musk and creating an auto (self) driving car, also in scratch. In Lesson 4, we look at a professional site, Kaggle, for data scientists, where you could enter competitions, learn and even earn money!


Check out Google's Quick draw. Neural networks are used to detect your doodling! How do you think it works?

Video Lesson 1

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Definitions and additional information

AI: Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.

Machine-learning algorithms are responsible for the vast majority of the artificial intelligence advancements and applications you hear about. (For more background, check out MIT's flowchart on "What is AI?" here.) Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you. If it can be digitally stored, it can be fed into a machine-learning algorithm.

Read about the three types of machine learning here: