176 Best + Free Introduction to Computer Science Courses & Certification [2020][UPDATED]

As featured on Harvard EDU, Stackify and Inc - CourseDuck identifies and rates the Best Introduction to Computer Science Courses, Tutorials, Providers and Certifications, based on 12,000+ student reviews, public mentions, recommendations, ratings and polling 5,000+ highly active StackOverFlow members. Learn more

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60 Filtered Courses

1 )

Introduction to Computer Science and Programming Using Python (2013)

4.6
This two-part certification course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Part 1 of this class will culminate in building a version of the classic arcade game "Pong".
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Pros
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Cons
    • Designed to be a first-ever experience with computer science. This is the ultimate beginner-friendly course.
    • Designed by MIT.
    • Large pool of exercises and supplemental resources to expand the concepts taught in the course.
    • Community resources encourage students to help each other.
    • Course is best followed by purchasing the supplemental textbook, raising the overall cost.
    • Focuses more on data science than most introductory Python courses.
    • This 8-week course might really take 8 weeks to complete.
An Introduction to Interactive Programming in Python
provider

2 )

An Introduction to Interactive Programming in Python (2013)

4.9
This two-part certification course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Part 1 of this class will culminate in building a version of the classic arcade game "Pong".
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Pros
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Cons
    • Two-part split makes it much easier for beginners to break into Python programming.
    • A total of 30 hours of course material creates a comprehensive learning experience.
    • By focusing on building a game from the ground up, application of the course feels more intuitive and enjoyable than more theoretical teaching methods.
    • Course focuses on peer grading, which can be inconsistent.
    • Part 1 focuses more on programming in general than the deeper aspects of using Python specifically.
    • Project-focused learning will not suit students who excel in theoretical environments.
The Data Scientist's Toolbox
provider

3 )

The Data Scientist's Toolbox (2019)

5.0
This Coursera course was created by Johns Hopkins University. It introduces tools and resources that are essential to working in data science, and it splits lessons into a theoretical and practical half.
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Pros
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Cons
    • Course takes a light introduction on a broad range of topics that all apply to data science. Great preparation for a full-dive, multicourse adventure into data science.
    • Covers mindset of data science in a way most courses skip.
    • Course ensures that you have the tools to take on a journey to truly master data science.
    • Course covers a substantial range of data science tools. Accessing all of them can potentially add a hefty price tag to completing the course.
    • Course is not a Capstone project. It is intended to prepare for a data science Capstone project.
    • Course teaches very little data science itself. It is more like going over the syllabus and prerequisites before diving into real learning.
Front-End Web Development with React
provider

4 )

Front-End Web Development with React (2018)

4.7
Developed by The Hong Kong University of Science and Technology, this Coursera course covers front-end development with React. It is a course for beginners that covers the essentials of using the React library to build web applications.
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Pros
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Cons
    • Course does not require an extensive background in coding or computer science.
    • Course will take newcomers by the hand to make an easy introduction into React development.
    • Course is built around a master project that will be revisited throughout. Helps to focus the learning.
    • Course is introductory. This is not a comprehensive course on professional-grade usage of React. Advanced students will be disappointed.
    • Course neglects automated testing.
    • Supplemental help comes primarily from forums rather than from direct interaction with the instructor.
Introduction to Computational Thinking and Data Science
provider

5 )

Introduction to Computational Thinking and Data Science (2015)

4.6
This MIT EdX course covers a brief introduction into data science and computational problem solving. It is not an introduction to computer science; students are expected to have programming experience in Python. Course introduces tools for simulating and modeling with data.
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Pros
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Cons
    • Covers some of the most common and important algorithms in all of programming.
    • Supplemental MIT resources are available that make this into a master class in computational science.
    • Completing the substantial challenges in this course is richly rewarding and will help develop a strong understanding of data science.
    • Prerequisites are not to be taken lightly. This course covers deep topics related to data scientists and assumes a strong background in Python.
    • Course is difficult and will overwhelm students who are not prepared to be challenged.
    • Trying this course without first completely 6.00.1x can prove prohibitively difficult.
Introduction to Data Science in Python
provider

6 )

Introduction to Data Science in Python (2016)

4.4
Coursera brings you this resource that was developed by the University of Michigan. It serves as an introduction to Python and applying it to data science. It will teach students how to manipulate data and make use of Pythons robust libraries. It is the first in a five-course series, and it can be completed in roughly 15 hours.
Introduction to Structured Query Language (SQL)
provider
Best Advanced Course

7 )

Introduction to Structured Query Language (SQL) (2017)

4.7
This University of Michigan course, hosted by Coursera, teaches computer science students how to create MySQL databases. It is the second in a series of courses that teach web applications, and it is entirely self-paced. It is budgeted for 10 hours of lecture and practical learning, and by the end, students will have a working knowledge of database management using MySQL.
Front-End JavaScript Frameworks: Angular
provider

8 )

Front-End JavaScript Frameworks: Angular (2017)

4.7
The Hong Kong University of Science and Technology built this course to take a deep look at a specific JavaScript framework. Coursera students will learn how to use Angular in front-end development and applications. With 44 hours of mixed-presentation instruction, this course provides a thorough look into Angular usage. By the end, students will have a strong understanding of the fundamentals of Angular and be able to deploy their skills in Angular front-end development.

9 )

Introduction to R for Data Science (2018)

4.4
EdX hosts this Microsoft course that takes students through an introduction to R and how to use in data science applications. It is a 4-week, 12-hour course. It is free to enroll, and a Microsoft certificate can be obtained upon completion for a fee.
Introduction to Computer Science and Programming Using Python
provider

10 )

Introduction to Computer Science and Programming Using Python

0.0
This course is the first of a two-course sequence: Introduction to Computer Science and Programming Using Python, and Introduction to Computational Thinking and Data Science. Together, they 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. This run features lecture videos, lecture exercises, and problem sets using Python 3.5. Even if you previously took the course with Python 2.7, you will be able to easily transition to Python 3.5 in future courses, or enroll now to refresh your learning.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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