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If you want to become an expert data scientist, you must know how to understand and analyze data. And for this statistics are important.
However, learning statistics can be difficult, especially if you don't have a background in mathematics or computer science. But do not worry. We've compiled a list of statistics courses, from introductory statistics to slightly more advanced concepts, that you can take for free.
You don't need to take all of these courses to master statistics for data science. So do not hesitate to consult the courses that you find especially interesting. Let us begin!
Note: Can audit All of the following courses for free on Coursera.
He Introduction to statistics The Stanford course is a good first statistics course. This course aims to teach all the statistical thinking concepts that are necessary to understand and analyze data.
Here is an overview of the course content. There is an overview of what the course covers:
- Introduction and descriptive statistics for data exploration.
- Data production and sampling.
- Probability
- Normal approximation and binomial distribution.
- Sampling distributions and the central limit theorem
- Regression
- Confidence intervals
- Significance tests
- Resampling
- Categorical data analysis.
- One-way analysis of variance (ANOVA)
- Multiple comparisons
Link: Introduction to statistics
Basic Statistics from the University of Amsterdam is also another statistics course for beginners. This course requires you to be familiar with R programming and covers the following topics:
- Exploring data
- Correlation and regression
- Probability and probability distribution.
- Sampling distributions
- confidence intervals and significance tests
Link: Basic Statistics
He Statistics for data science with Python IBM offers it as part of Data Science Fundamentals with a specialization in Python and SQL.
This course will teach you how to use Python to perform statistical tests and interpret the results of statistical analyses. The contents of this course are the following:
- Python Basics
- Introduction and descriptive statistics.
- Data visualization
- Introduction to probability distributions.
- Hypothesis evaluation
- Regression analysis
Link: Statistics for data science with Python
The power of statistics Google offers it as part of its Google Advanced Data Analytics Professional Certificate.
From summarizing data sets to performing hypothesis testing and modeling data using probability distributions, this course also focuses on statistical analysis with Python. This course covers the following topics:
- Introduction to statistics
- Probability
- Sampling
- Confidence intervals
- Introduction to hypothesis testing.
Link: The power of statistics
He Statistics with specialization in Python offered by the University of Michigan teaches you how to use Python for data visualization, statistical inference, and modeling. It also emphasizes the importance of connecting the business questions you need to answer with relevant data analysis methods.
This is a three-course specialization that covers the required theory as well as programming assignments in Python to help you apply everything you've learned. The specialization courses are the following:
- Understand and visualize data with Python
- Inferential statistical analysis with Python
- Fitting statistical models to data with Python
Link: Statistics with specialization in Python
And that's a wrap. We review five courses you can take for free to learn statistics and improve your data science skills.
Because most of these courses focus on programming and running statistical tests with Python rather than learning just theoretical concepts, I'm sure you'll find plenty of opportunities to apply what you've learned. Happy learning and keep coding!
Bala Priya C. is a developer and technical writer from India. He enjoys working at the intersection of mathematics, programming, data science, and content creation. His areas of interest and expertise include DevOps, data science, and natural language processing. He likes to read, write, code and drink coffee! Currently, he is working to learn and share his knowledge with the developer community by creating tutorials, how-to guides, opinion pieces, and more.
