In my decade of teaching online, the most significant inspiration has been that online learning democratizes access to education globally. Regardless of your ethnic background, income level, and geographical location—as long as you can surf the web—you can find an ocean of free educational content to help you learn new skills.
This article introduces six top-notch, free data science resources ideal for aspiring data analysts, data scientists, or anyone aiming to enhance their analytical skills.
1. 365 Data Science Flashcards
At 365 Data Science, we offer a range of expertly designed flashcard decks to teach fundamental data science concepts—including terms and glossaries for tools like Microsoft Excel, SQL, Python, and ChatGPT. Additionally, our flashcards cover math, statistics, probability, and machine learning—providing an excellent starting point for beginners by familiarizing them with the essential data science language. Free Udemy Courses
2. Udemy
Udemy is the go-to marketplace for online courses. Their content library includes over 100,000 titles on almost every topic—including data analytics and data science. They also offer free courses uploaded by authors eager to share their knowledge with the public at no cost. Use the filtering options when browsing the marketplace to discover unique learning materials.
3. 365 Data Science Statistics Calculators
Recently, 365 Data Science launched a series of statistics calculators designed for university students and practitioners eager to grasp statistical calculations’ underlying mechanics and theory—beyond merely achieving results through tools like Excel or Python. These calculators enable users to input problem data for homework, exams, or practice, revealing each step necessary to arrive at the solution rather than only the outcome. Each calculator includes a detailed statistical article to explain the concept—offering an invaluable opportunity to learn through comprehension and application.
Utilize these complimentary statistics calculators to discover how to:
- Study the measures of central tendency
- Obtain dispersion measures such as variance, standard deviation, and coefficient of variation
- Get an idea about the shape of a statistical distribution: skewness and kurtosis
- Calculate confidence intervals
- Perform hypothesis testing
- Obtain p-value and decide on the significance of A/B testing results
- Calculate the difference in means
- Run simple linear regression
4. YouTube Tutorials
YouTube’s data content creators deliver immense value—offering everything from concise tutorials and job-seeking advice in data science to comprehensive courses. If you’re seeking exceptional, free data science learning resources, consider these top recommendations:
- Programming with Mosh’s full course on Python Programming for Beginners
- freeCodeCamp’s full course on Data Science Fundamentals
- MySQL Basics for Data Analysts playlist by Alex the Analyst
- SQL Sundays playlist by Tina Huang
- Data Science projects playlist by Ken Lee
5. 365 Data Science Course Notes and Career Guides
At 365 Data Science, we offer a wealth of free resources to our students. For those keen on exploring data science without financial constraints, download our complimentary course notes and career guides. You can access various topics at no cost, including Intro to Data Science, Statistics, Probability, Python, Machine Learning, Data Strategy, and others.
In addition to course notes, you can download 365’s free Data Analyst Career Guide and Data Scientist Career Guide.
6. Free Big Tech Courses
Google, Microsoft, Amazon, and other Big Tech organizations have shown increasing interest in providing free online courses to individuals worldwide.
For instance, you can sign up at no cost for Google’s Data Analytics Professional Certification on Coursera, accessing courses for free until opting to pay a reasonable fee for a certificate of completion.
Conclusion
This comprehensive list of free data science learning resources is a testament to the quality content available online at no cost. The wealth of available educational resources will motivate future data analysts and scientists—enhancing global skillsets and career prospects, regardless of humble origins.
It’s a pathetic list. Not everyone is a python fanboy. There are no links to R resources. R is a popular language for many data scientists.
Yes, you’re right that R is popular but Python is always catching up on the data science tools. But you cannot deny that Python is more widely used as a programming language and hence it is easier to attract people using Python for other purpose into the domain of data science.
Google,Microsoft,Amazon
Data Analysis