369 Best + Free Data Science Courses & Certification [UPDATED]
As featured on Harvard EDU, Stackify and Inc - CourseDuck identifies and rates the Best Data 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
- 1. Data Science And Machine Learning Masterclass [Eduonix] - Best Paid Course
- 2. Python for Data Science [edX] - Best Course Overall
- 3. Learn Python For Data Science [YouTube] - Best YouTube Tutorial
- 4. The Data Scientist's Toolbox [Coursera]
- 5. Introduction to Computational Thinking and Data Science [edX]
- 6. Intro to Data Analysis [YouTube]
- 7. Introduction to Data Science [edX]
- 8. Introduction to Data Science in Python [Coursera]
- 9. CS109 Data Science [GitHub]
- 10. Data Science: R Basics [edX]
Data Science And Machine Learning Masterclass (2020)
Python for Data Science (2017)
- Course teaches by example, giving you a realistic glimpse into legitimate data science.
- Course encourages peer interaction to build a supportive community that expands learning.
- All lecture videos include subtitles.
- Interaction with instructors can be slow and limited.
- Jupyter section is UNIX heavy and can be troubling to perform on Windows machines.
- Completing course does not guarantee reception of the certificate.
Learn Python For Data Science (2016)
- YouTube tutorials are always free and repeatable - one of their greatest strengths.
- Course delves well beyond the basics of Python and gets deep into databases for data science.
- Course caters to an audience that already understands the fundamentals of programming and doesn't waste time on things you already know.
- Content covers the usage of powerful resources. Accessing and installing them can provide barriers in completing the course.
- Interaction with instructor is extremely limited unless you pay for the additional DataCamp course.
The Data Scientist's Toolbox (2019)
- 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.
Introduction to Computational Thinking and Data Science (2015)
- 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.
Intro to Data Analysis (2016)
- It's short. Taking up less than two hours of your life, this course will not feel grueling or overwhelming.
- It's on YouTube. That means it's free and accessible.
- Demo-based teaching allows you to see concepts in motion.
- It's short. Truly living up to the word "intro", this course does not delve deeply into analytical techniques. It only covers the bare basics and will not teach the tools for professional analysis.
- Tutorial is more fun than serious. While information is accurate, it does not reflect the data science profession.
- Series is more of an overview of a few ideas than a true course in data science.