Python is a high-level programming language known for its emphasis on code readability and indentation. It supports multiple programming paradigms and has a comprehensive standard library. Guido van Rossum developed Python as a successor to the ABC programming language and it has since become one of the most popular programming languages, with its users often referred to as pythonistas.

Stanford University

Fall 2022

An in-depth course focused on building neural networks and leading successful machine learning projects. It covers Convolutional Networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. Students are expected to have basic computer science skills, probability theory knowledge, and linear algebra familiarity.

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+ 35 more conceptsStanford University

Winter 2023

This comprehensive course covers various machine learning principles from supervised, unsupervised to reinforcement learning. Topics also touch on neural networks, support vector machines, bias-variance tradeoffs, and many real-world applications. It requires a background in computer science, probability, multivariable calculus, and linear algebra.

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+ 32 more conceptsUC Berkeley

Summer 2022

A gentle, thorough introduction to computer science, starting with block-based language Snap! and transitioning to Python. The course covers fundamental programming concepts and encourages application in various fields. Level: Beginner friendly.

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+ 21 more conceptsStanford University

Autumn 2022

This course is designed for those with prior programming experience. It focuses on advanced programming methodologies in Python and JavaScript, and covers topics from object-oriented design principles to building web applications.

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+ 29 more conceptsUniversity of Washington

Summer 2022

This course offers an intermediate level of data programming, focusing on different data types, data science tools, code complexity, and memory management. It emphasizes the efficient use of concepts for data programming.

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+ 34 more conceptsUniversity of Washington

Winter 2022

This course dives deep into the role of probability in the realm of computer science, exploring applications such as algorithms, systems, data analysis, machine learning, and more. Prerequisites include CSE 311, MATH 126, and a grasp of calculus, linear algebra, set theory, and basic proof techniques. Concepts covered range from discrete probability to hypothesis testing and bootstrapping.

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+ 41 more conceptsStanford University

Winter 2023

This course helps transition from coding to problem-solving using computers. The course explores techniques, tools, and models for problem-solving across disciplines using C++. Prior programming experience is assumed.

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+ 33 more conceptsStanford University

Autumn 2022-2023

Stanford's CS 221 course teaches foundational principles and practical implementation of AI systems. It covers machine learning, game playing, constraint satisfaction, graphical models, and logic. A rigorous course requiring solid foundational skills in programming, math, and probability.

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+ 88 more conceptsThe University of Massachusetts Amherst

Spring 2023

This course introduces computer programming and problem-solving. Students learn using a modern language, covering variables, data types, branching, functions, classes, and methods. Emphasis is on real-world problem translation, computational understanding, and debugging.

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+ 30 more concepts