7 Certified Data Science Courses to Upgrade Your Job Skills With Coursera

Ben Stegner 03-09-2018

Looking to start a career path around data science? Why not get started with Coursera?

We’ve previously highlighted some of the best Coursera courses worth paying for The 10 Best Free Coursera Courses You'll Want to Pay For You can learn anything online with Coursera. These 10 free courses are so good that you'll want to pay to earn a certificate, too. Read More . But if those were too broad for you, have a look at these excellent courses in data science.

What Is Data Science?

Just in case you’re not aware, we’ll briefly describe the field of data science so you have an idea of what these courses involve.

Data science, in a sentence, is a field that uses all sorts of methods to pull insights from data. This enables people to make better decisions.

With the explosion of big data What Is Big Data, Why Is It Important, and How Dangerous Is It? Big data powers many industries and has an effect on all of our lives. But is it more dangerous or helpful? Read More and easier ways to collect data in large quantities than ever before, having data science around to process and make meaningful choices based on it is essential. These courses will introduce you to data science and help you branch out to a specific area that you’re interested in.

1. The Data Scientist’s Toolbox by Johns Hopkins University

The first course in the university’s data science specialization. It serves as an overview of what data scientists do and work with. You’ll learn the basics of how to turn data into information you can take action on, as well as technical tools used in other data science courses like R programming, git, and similar.

You won’t get into the nitty-gritty of data science just yet, but this serves as a valuable foundation for the tools of the trade.

2. Getting and Cleaning Data by Johns Hopkins University

As this course’s description says, before you can work with data, you need some data! Thus, this class focuses on ways to obtain some. You’ll learn how to grab data from the internet, databases, various APIs, and more.

Similarly, you’ll learn the essentials of data cleaning, the process of making your data neat so you can work with it more easily. By keeping your data in good shape, it becomes much easier to work with and more useful.

3. Machine Learning by Stanford

Machine learning, the process of making computers act without explicit programming, is huge today. The progress made in self-driving cars, automated web technologies, and similar fields has been fantastic, and machine learning powers them all.

It’s an important part of data science, making it a great Coursera course to take. You’ll get some practice working with machine learning techniques, how to apply them, and some best practices in the field. Interestingly, this course is taught by Andrew Ng, the co-founder of Coursera.

4. Introduction to Data Science in Python by University of Michigan

Python is a popular programming language for all sorts of purposes, so it’s no surprise to see it used in data science. This course, the first in a five-part Applied Data Science with Python Specialization set from the University of Michigan, looks at the basics of Python and data manipulation.

After this course, you’ll know how to clean and manipulate data in Python. It’s an intermediate-level course, so total newcomers to Python or statistics need not apply.

5. Google Cloud Platform Fundamentals: Core Infrastructure by Google Cloud

Google’s cloud technology is one of the front runners of data science, so why not learn from the best? This course is the first part of Google’s cloud platform specialization, and walks you through the basics of working with the various services. You’ll meet Google App Engine and Google Computer Engine, for starters.

It’s a great overview of the powerful services Google has at its disposal and will help you decide if you want to continue learning about them. Notably, this course has just one week of study, so you can complete it in roughly seven hours.

6. Inferential Statistics by University of Amsterdam

If you don’t have any experience with statistics, you might run into trouble understanding data science. In those cases, this course will provide you with some background on the field.

You’ll learn basic principles for testing specifics, then explore common statistical tests and how to interpret them.

7. Data Science Specialization by Johns Hopkins University

If you’re serious about data science, take a look at Coursera’s data science specialization. This is a nine-course introduction to the discipline, capped off by a real-world project.

Some of the above courses were taken from this specialization, so you can take them individually if you only have a passing interest in the subject. But working through the whole package enables you to learn much more, and you’ll have a valuable certificate upon completion.

This specialization takes about nine months to complete, with five hours of work per week. It’s intended for beginners and doesn’t require any background knowledge other than a basic working knowledge of Python.

Ready to Learn About Data Science?

We’ve highlighted six courses that cover different areas of the data scientist’s toolkit for you to explore on Coursera. If you want to go further, look into the Johns Hopkins specialization for much more on this topic.

Data science is an exciting field, and it will only continue to grow as technology becomes more powerful. Take advantage of Coursera‘s excellent (and affordable) courses now to get your career started!

Related topics: Big Data, Online Courses.

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