DataCamp Data Science Career Track

Become a Data Scientist by learning to code on DataCamp. A practical approach to learning data science online.

Data Science is an emerging career and tech companies are constantly looking to hire experienced and skilled data scientists and engineers.

One of the best ways to help get your foot in the door of Data Science is by completing online data science courses and bootcamps.

In this text, I want to review what DataCamp has to offer when it comes to learning data science online from scratch. Is DataCamp worth your time?

Why DataCamp is unique for learning Data Science?

First of all, DataCamp is really unique when it comes to teaching Data Science. You might be aware of other platforms like:

• Coursera with hundreds of great courses
• Springboard with Data Science Bootcamp
• Edureka with Data Science Master Program

So what’s unique about DataCamp? Its primary focus is practicality.

You learn by coding!

Within each course, you’ll be able to write and execute code directly in your browser without quitting DataCamp. This is how it looks:

The approach to learning on DataCamp is also unique. Lessons are small, so you can quickly finish one in your lunch break and when you just have a little bit of free time. Thanks to their mobile app, you can learn easily on your smartphone.

Pricing is also well structured. You pay a monthly fee to access all the materials and you can learn as much as you want. The content includes:

• 341 courses
• 14 career tracks
• 44 skill tracks
• Unlimited skill assessments
• Community chat

The good thing is you can register for free without giving any details, to access a preview of every single course and decide whether you like it or not. That’s a very good move from DataCamp!

Courses for Data Scientists on DataCamp

Let’s now look at the content of courses for data scientists. What you learn inside DataCamp depends on you and there’s a great choice. You can start by learning Python with these modules:

Introduction to Python

You’ll learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses.

Intermediate Python

You’ll learn to visualize real data with Matplotlib’s functions and get acquainted with data structures such as the dictionary and the pandas DataFrame.

Introduction to Databases in Python

You’ll learn the basics of using SQL with Python. This will be useful because databases are ubiquitous and data scientists, analysts, and engineers must interact with them constantly.

These 3 courses on DataCamp provide you a great way to start your adventure into data science. But that’s not all. DataCamp doesn’t leave you to just browse through its courses. Different courses are split among different career tracks. So if you want to become a Data Scientist, you can pick a Data Science Career Track on DataCamp to have the whole learning experience ready for you.

In Data Science Career Track on DataCamp you learn how to:

• import,
• clean,
• manipulate,
• and visualize data.

Through interactive exercises, you’ll get hands-on with the most popular Python libraries like pandas, NumPy, Matplotlib, and more.

You’ll work on real-world datasets and learn statistical and machine learning techniques, from decision trees to natural language processing (NLP).

That sounds exciting, right?

DataCamp vs Coursera

Coursera is currently the largest online learning platform. However, with its broad offer, it doesn’t only address data scientists. The catalog of courses is vast but it’s often hard to decide which course to pick (but see this list of top 10 courses on Coursera). On the other hand, DataCamp educational offer is truly unique. Not only it has a great choice of courses related purely to data science and programming, but it also shows you how to learn and more importantly, how to code. Practicality is key in Data Science.

Thanks to these interactive lessons you will quickly become a confident Data Scientist.

Have you completed DataCamp Data Science Career Track? What’s your experience? Please leave your feedback below.

Finally, if you prefer to watch a video version of this text, have a look at my YouTube channel: