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Skilled data scientists remain in high demand. It’s a great time to get into data science. But how—and where—do you start?
Should you enroll in bootcamps, professional certifications, and master’s programs to learn data science? Yes, these are all good options. However, you can learn data science for free and still successfully change careers.
To assist you get started, we’ve put together a list of free and high-quality college courses that will assist you learn data science from the ground up. Because these courses have a structured curriculum, you don’t have to worry about what to learn and in what order — and you can just focus on learning and improving.
Let’s get started!
If you need a refresher on Python programming before you start learning data science, check out CS50 Introduction to Python Programming taught at Harvard University.
Once you have learned the basics of Python programming, you can check this out Introduction to Data Science with Python Of course, also from Harvard.
In this course you will learn about the following topics:
- Basics of programing
- Using Python for Coding, Statistics, and Data Storytelling
- Python data science libraries like NumPy, pandas, matplotlib, and scikit-learn
- Building and Evaluating Machine Learning Models
- Applications of machine learning
Link to the course: Introduction to Data Science with Python
Introduction to Computational Thinking and Data Science from MIT is another good course to learn the basics of data science. This course will assist you get familiar with data science and basic statistical concepts.
Below is an overview of the course scope:
- Optimization problems
- Stochastic thinking
- Random walks
- Monte Carlo simulation
- Confidence intervals
- Understanding experimental data
- Grouping
- Classification
Link to the course: Introduction to Computational Thinking and Data Science
Statistical learning at Sanford University is another popular course where you can learn how different machine learning algorithms work.
The programming exercises in this course are in R. But you can also work through them using Python. I also suggest you apply the Python edition of Introduction to Statistical Learning (which is also free) as a companion to this course.
The course covers the following topics:
- Linear Regression
- Classification
- Resampling methods
- Model selection
- Regularization
- Tree-based methods
- Support Vector Machines
- Unsupervised learning – these are some of the topics covered in this course
Link to the course: Statistical learning
Even if you are familiar with building machine learning models using Python and Python libraries like scikit-learn, you should also understand some mathematical concepts.
Learning the math concepts will be helpful if you ever want to get into machine learning research, and it will also give you an edge in job interviews. This is vital, learning these concepts will assist you gain an edge, it will give you an edge in job interviews
This Math Topics in Data Science course from MIT will teach you some mathematical topics related to data science. Specifically, advanced dimensionality reduction and clustering concepts.
Here are some of the topics you will learn:
- Principal Component Analysis
- Spectral clustering
- Compressed detection
- Approximation algorithms
Link to the course: Math Topics in Data Science
Based on one or more of the courses we’ve seen so far, you should be comfortable in the following areas:
- Python Data Science Libraries
- How machine learning algorithms work
This Data Science: Machine Learning This course from Harvard will assist you review the fundamentals of machine learning and apply them to build a recommendation system.
This course will teach you:
- Machine Learning Basics
- Cross Validation
- Popular Machine Learning Algorithms
- Regularization techniques
- Building a Recommendation System
Link to the course: Data Science: Machine Learning
So now you have a list of high-quality data science courses from elite universities like Harvard, MIT, and Stanford to assist you delve deeper into data science.
From Python data science libraries to the inner workings of machine learning algorithms, you can check out one more of these courses to find the one that best suits you. Elated learning!
Priya C Girl is a software developer and technical writer from India. She enjoys working at the intersection of mathematics, programming, data science, and content creation. Her areas of interest and expertise include DevOps, data science, and natural language processing. She enjoys reading, writing, coding, and drinking coffee! She is currently working on learning and sharing her knowledge with the developer community by creating tutorials, how-to guides, opinion pieces, and more. Bala also creates engaging resource reviews and coding tutorials.