Back in 2012, the Harvard Business Review called data science “the sexiest job of the 21st century.” Not much has changed since then. If anything, the job of a data scientist has grown even hotter. According to a 2019 report by Indeed, there’s been an almost 30% increase in demand for data scientists year over year and nearly 350% jump since 2013.
The demand for data scientists far outstrips supply. A 2018 LinkedIn survey found a shortage of more than 150,000 people with data science skills in the U.S. alone. As many as 50% of data scientists who already have a job get contacted at least once a week about new opportunities. 85% are contacted about once a month. This talent crunch means that, on average, a data science job stays vacant for 45 days. It comes as no surprise, then, that when businesses finally manage to attract data science talent, they pay them well. According to Glassdoor, as of June 2020, the average data scientist salary in the U.S. is $113,309.
For employment-focused students, studying data science is a no-brainer. But not everyone has thousands of dollars to spare on a data science degree (or the time to do it, for that matter). Online courses offer a cost-effective alternative to degrees and the field of data science benefits largely from e-learning. As long as you can stay the course as a self-paced learner, you can outperform anyone with a traditional degree in data science. That is, if you choose the right online course.
These are the best online courses to learn data science:
- Best Overall: Data Science Online Bootcamp (Thinkful)
- Best for Beginners: Data Science for Everyone (DataCamp)
- Best for Certification: Data Science Specialization (Coursera)
- Data Scientist Nanodegree (Udacity)
- Data Science Career Track (Springboard)
- IBM Data Science Professional Certificate (Coursera)
- Applied Data Science with Python Specialization (Coursera)
- Data Science: The Big Picture (Pluralsight)
- Data Science MicroMasters (edX)
- Data Science Professional Certificate (edX)
- Data Science Literacy Path (Pluralsight)
Best Overall: Data Science Online Bootcamp (Thinkful)
This program is in a league of its own, with its star-studded mentor lineup and a curriculum that outshines most degrees.
To kick things off, we have Thinkful’s Data Science Online Bootcamp. Right off the bat, keep in mind that this program is NOT like your typical Udemy course. The curriculum is much closer to a Master’s degree than to the average MOOC. This also means that the admissions process vets applicants more selectively than most other online learning platforms.
Passing the admissions process, while demanding, is a task worth undertaking. That is because all admitted students are met with a one-of-a-kind data science curriculum that has numerous benefits over its competitors. These benefits include:
- Biweekly 1-on-1 meetings with expert mentors;
- Best-in-class post-graduation career services;
- Data science specialization options based on your career goals;
- Personal capstone projects that can be showcased to employers.
Before getting into the nitty-gritty of big data analysis, the program introduces new students to the basic concepts of data science through a prep course. This covers an introduction to Python and its packages, probability and statistics, and a quick primer on career planning. After this prep course, the students dive head-first into the core principles of data science, with lessons on SQL, supervised/unsupervised learning, and many, many more. For a first-hand overview of the syllabus, have a look at Brendan Martin’s post on the program.
To sum it up, Thinkful’s data science program truly is the best of its kind. But, due to its length and stricter-than-average admissions process, it’s not a one-size-fits-all type of program. But, we felt it easily deserved the title of THE best data science course on the market.
Best for Beginners: Data Science for Everyone (DataCamp)
With hundreds of data science courses on offer, you can go from beginner to advanced learner in no time with DataCamp.
DataCamp offers hundreds of data science online classes for both complete beginners and advanced learners. Examples of popular beginner courses include Data Science for Everyone, which introduces you to data science (no coding involved!) and Introduction to R, which teaches you the basics of data analysis in just four hours. You can take a skill assessment to get course recommendations if you have some knowledge of data science,
While you can take DataCamp courses individually in pretty much any order you choose, many students prefer to take a “Skill Track” or a “Career Track” instead. Whereas skill tracks help you become an expert in a specific technology, domain, or methodology, career tracks make it easier to start a new career in the data science industry.
Most lessons consist of videos and hands-on coding practices. When you complete a course, you can practice your new skills with DataCamp’s numerous projects. Visualizing COVID-19, Exploring 67 Years of LEGO, and Exploring the Bitcoin Cryptocurrency Market are just some of the projects that caught my eye.
It doesn’t matter whether you’re a beginner or advanced student, DataCamp has data science (online) training courses that’ll suit just about everyone — as long as you learn best by doing and don’t want to spend a lot of time learning theory.
Best for Certification: Data Science Specialization (Coursera)
This ten-course program will help you get to the next level in your career if you have experience with Python and some knowledge of regression.
Created by John Hopkins University and hosted on Coursera, the Data Science Specialization is a ten-course program that covers everything from R programming to reproducible research to machine learning. The program ends with a capstone project, which means that you get a chance to create a data product that can potentially solve a real-world problem. Although this course is suitable for beginners, students should have some programming experience as well as a good knowledge of mathematics.
Course material is taught via video lessons and complementary readings. Your knowledge is tested via quizzes and peer-graded assignments. Students are also expected to do their own research.
While you can audit the course to see the course material for free, you’ll need to sign up for the Specialization if you want to earn a certificate. There’s also a free 7-day trial, so you can try the course before you commit to it. After the trial, you’ll be charged a monthly fee, so the quicker you complete the course, the cheaper it’s going to be.
All in all, Data Science Specialization is definitely another one of the best online data science courses out there. According to Coursera, almost half of the students that took this course started a new career. And, nearly 20% received a pay increase or promotion.
Data Scientist Nanodegree (Udacity)
At the end of this 4-month course, you will have a better understanding of data manipulation, machine learning, and big data.
Udacity’s Data Scientist Nanodegree is best suited for students with some background in statistics and programming. The program aims to teach you how to gather, manipulate, analyze, and visualize data using Python and its packages, such as NumPy, Pandas, and SciPy. The program covers a wide range of data-related topics in its 4-month curriculum, including wrangling, analysis, visualization, and MapReduce.
The classes are taught through video lessons and include quizzes and interesting assignments. For example, after the first lesson, you’re asked to use NumPy and Pandas to forecast the passenger survival rate on the Titanic.
Udacity also offers a free course “Intro to Data Science“. However, since the course focuses on breadth, many students find the coverage of certain topics too brief. On the other hand, if the course went much more in-depth, you wouldn’t be able to complete it in just two months (the estimated timeline for the course). Besides, the whole point of this course is to introduce you to key topics in data science, not turn you into an expert.
The Data Scientist Nanodegree, is, without a doubt, a superb course on data science. It covers all the most critical data science topics and even lets you build a data science project from start to finish. And, it’s also worth a mention that Udacity’s career services are offered to all Nanodegree students, giving extra value to career-building students. Our readers can get $50 off this (and any other) Nanodegree with this link.
Data Science Career Track (Springboard)
Data Science Career Track promises students either a job within 6 months of finishing the program or a refund.
Springboard offers a job guarantee to all its graduates, which means that you won’t have to pay for the course until you get a data science job (if you decide to pay upfront, they’ll pay you back should you fail to get a job). No other course provider does that. The reason Springboard is so confident its course will help you get hired? Its mentors are world-class data scientists and some of them are hiring managers themselves.
The course includes more than 500 hours of content, one on one mentor support, and 14 real-world projects. The curriculum is divided into 18 units, which cover topics such as Python, machine learning, Hadoop, and SQL, among others. Students complete two capstone projects towards the end of the course, which they can use as part of a portfolio.
Students can expect to complete the course in just 6 months, provided that they spend between 15 and 20 hours a week studying. As soon as students complete the course, they can avail of career support, including one on one mock interviews and access to Springboard’s employer network.
Not everyone who applies to this program will get accepted, though. Only students with six months of coding experience and knowledge of probability and statistics stand a chance of getting in.
If you’re worried that a data science course won’t necessarily help you land a job in the industry, Springboard’s Data Science Career Track will put your mind at ease. Out of almost 2,000 students who enrolled in this course since 2016, there’s been only one job guarantee refund. As such, it’s probably fair to say that the Data Science Career Track is one of the best advanced data science courses on the market.
IBM Data Science Professional Certificate (Coursera)
A well put together short course that is filled with student projects.
Available on Coursera, IBM’ Data Science Professional Certificate is suitable even for absolute beginners. In fact, the course, which is divided into nine sub-courses, actually starts by answering “what is data science?” before delving into topics such as open-source tools and libraries, Python, SQL, data analysis, machine learning, and more.
The course places a strong emphasis on hands-on learning. Students practice in the IBM Cloud with real-world data sets and real data science tools.
Since there’s a 7-day free trial, you can try the course before you buy it. Coursera says that students can finish the course in about 10 months if they put in 4 hours a week. Once you complete the course, you’ll receive a shareable certificate from Coursera as well as a digital badge from IBM, acknowledging your proficiency in data science. In addition, you’ll also gain access to IBM’s Talent Network, which is great if you’ve always wanted a job with IBM.
With more than 120,000 ratings, most of which are glowing, the IBM Data Science Professional Certificate course is a popular choice for getting to grips with data science.
Applied Data Science with Python Specialization (Coursera)
Learn data science through Python, one of the most popular languages in the industry.
Applied Data Science with Python Specialization on Coursera is a series of five courses that aim to teach you how to use Python for data science applications. Offered by the University of Michigan, the courses cover plotting, charting & data representation, machine learning, text mining, and social network analysis. Each course focuses on free Python libraries like NumPy, SciPy, Pandas, Matplotlib, seaborn, scikit-learn, NLTK, Gensim, and NetworkX.
The courses are easy to follow. The content is taught via video lessons, readings, external tools, discussions, and peer-graded assignments. The word “Applied” in the course title is there for a reason. The course focuses less on theory and more on usage. In other words, you’ll learn just enough to understand the homework assignments. If you want to delve deeper, you’ll have to self-learn through books and other online content.
The course is marked as intermediate-level, so students are expected to know how to code in Python. They should also have some knowledge of statistics and discrete mathematics. If you dedicate about six hours a week to the course, you can complete it in about five months.
According to a 2018 Cloud Academy Report, there’s more demand for data engineers and scientists proficient in Python than any other programming language, including R. As such, this Python data science course can help you get noticed by the industry.
Data Science: The Big Picture (Pluralsight)
If you don’t know much about data science but would like to learn more, this course is what you’re looking for.
Data Science: The Big Picture on Pluralsight is one of the best data science courses for beginners. There are no prerequisites to taking this course. The course instructor, Matthew Renze, will explain everything you need to know as you go along, including what data science is, why it’s so important, and where data science trends seem to be going. The course is split into six sections: Introduction, Data Analytics, Internet of Things, Big Data, Machine Learning, and Closing the Loop.
The curriculum is taught via videos and short quizzes. Since the course is just over an hour long, it’s unlikely to overwhelm you. But if you’re already familiar with the basics of data science, it probably won’t teach you anything new, either. That being said, Renze is a great teacher and he obviously knows what he’s talking about.
This course is best suited for absolute beginners who know little to nothing about data science. However, I’ve yet to find an introductory course into data science that is as digestible and easy to follow as Data Science: The Big Picture.
Data Science MicroMasters (edX)
This MicroMasters by UC San Diego provides deep learning in data science, is recognized by most employers, and can count towards a Master’s degree.
“Learn data science by doing data science” with the Data Science MicroMasters offered by the University of California San Diego (UC San Diego) on edX. This course is an online version of the Master’s degree program in data science taught at UC San Diego. It explores both the mathematical and the applied side of data science learning. Mathematical courses look at statistics, probability, and machine learning. The applied courses, on the other hand, cover data science toolkits and languages, such as Python, SciPy, Pandas, Numpy, Matplotlib, Apache Spark, and Jupyter Notebook.
The four-course program lasts 10 months. Students are required to dedicate between 9 and 11 hours to the course a week. Each course (Machine Learning Fundamentals, Python for Data Science, Probability and Statistics in Data Science Using Python, and Big Data Analytics Using Spark) takes 10 weeks to complete.
This program was designed with advanced students in mind. To make the most of it, students should have a fairly good level of programming knowledge. Although expensive (the program costs $1,400), this program can count as credit towards a Master’s degree program. For example, the Rochester Institute of Technology (RIT) will count the MicroMasters certificate as 30% of its Master of Science degree in Data Science.
You won’t regret taking the thorough Data Science MicroMasters by UC San Diego if you’re serious about becoming an expert in data science.
Data Science Professional Certificate (edX)
Learn data science from a world-renowned Harvard professor for under $500.
Available on edX, Data Science Professional Certificate by Harvard University is a comprehensive 9-course program. The program teaches you R programming, visualization, probability, wrangling, machine learning, and more using real-world case studies. The courses are taught by Rafael Irizarry, Harvard’s Professor of Biostatistics.
It should take you a year and five months to finish all the courses in this program. However, you don’t have to complete all of the courses within a single course run.
Anyone can sign up for this program and start learning. You don’t need to have prior computer science knowledge. The program begins with data science fundamentals and ends with a capstone project. The project is a tangible product you can show to potential employers. However, the capstone project isn’t the only time students can practice what they’ve learned. Hands-on coding exercises are plentiful. For example, during the machine learning course, students get to build a movie recommendation system.
If you’ve always wanted to attend Harvard, now’s your chance! Although an online program, the Data Science Professional is great for gaining deep experience in data science.
Data Science Literacy Path (Pluralsight)
Fill the gaps in your data science knowledge with this quick and easy learning path by Pluralsight.
Data Science Literacy Path is a series of data science courses available on Pluralsight. The “path” (Pluralsight’s way of referring to a group of related courses) will give you foundational knowledge behind data science, with a strong emphasis on Microsoft Azure. As part of this course, students will learn things like data shaping and munging and the application of basic statistics.
The course is divided into three sections: beginner, intermediate, and advanced. There are eight courses in total, including Representing, Processing, and Preparing Data (beginner), Interpreting Data with Statistical Models (intermediate), and Validating Models in Microsoft Azure (advanced).
Each course is about three hours long. As such, the entire path should take you about 23 hours to complete. The really cool thing about the Data Science Literacy Path is that you don’t necessarily have to start at the beginning if you’re already familiar with the topic. You can take a Data Science Literacy skill assessment to see what content you should focus on.
Both beginners and advanced learners will love this course. Beginners will love the fact that this path will teach them data science from start to finish. Conversely, advanced learners will appreciate the personalized guidance they receive through the skill assessment.