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Eric Grimson, John Guttag, and Ana Bell

The courses in the XSeries are designed to help people with no prior exposure to computer science or programming learn to think computationally and write programs to tackle useful problems. Some of the people taking the two courses will use them as a stepping stone to more advanced computer science courses, but for many it will be their first and last computer science courses. Since these courses may be the only formal computer science courses many of the students take, we have chosen to focus on breadth rather than depth. The goal is to provide students with a brief introduction to many topics so they will have an idea of what is possible when they need to think about how to use computation to accomplish some goal later in their career. That said, they are not “computation appreciation” courses. They are challenging and rigorous courses in which the students spend a lot of time and effort learning to bend the computer to their will.

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The courses in the XSeries are designed to help people with no prior exposure to computer science or programming learn to think computationally and write programs to tackle useful problems. Some of the people taking the two courses will use them as a stepping stone to more advanced computer science courses, but for many it will be their first and last computer science courses. Since these courses may be the only formal computer science courses many of the students take, we have chosen to focus on breadth rather than depth. The goal is to provide students with a brief introduction to many topics so they will have an idea of what is possible when they need to think about how to use computation to accomplish some goal later in their career. That said, they are not “computation appreciation” courses. They are challenging and rigorous courses in which the students spend a lot of time and effort learning to bend the computer to their will.

Introduction to Computer Science and Programming Using Python covers the notion of computation, the Python programming language, some simple algorithms, testing and debugging, and informal introduction to algorithmic complexity, and some simple algorithms and data structures. Introduction to Computational Thinking and Data Science will teach you how to use computation to accomplish a variety of goals and provides you with a brief introduction to a variety of topics in computational problem solving.

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What's inside

Two courses

Introduction to Computer Science and Programming Using Python

(135 hours)
This course introduces computer science and programming using Python. It covers basic concepts like computation, the Python language, algorithms, testing, algorithmic complexity, and data structures. Designed for beginners with no prior experience, this course aims to provide a broad understanding of computer science and equip students with the skills to solve problems using computation.

Introduction to Computational Thinking and Data Science

(135 hours)
This course introduces computational thinking and data science, teaching students how to use computation to solve problems. Topics include advanced Python programming, graphs, dynamic programming, probability, and Monte Carlo simulations.

Learning objectives

  • Programming
  • Data structures
  • Computational thinking
  • Data science
  • Algorithms

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