DataCamp is designed to be beginner-friendly.
While there are many languages and disciplines to choose from, some of the most popular are R and Python. It's totally fine to learn both at the same time! Generally speaking, Python is more versatile: it was developed as a general-purpose programming language and has evolved to be great for data science. With Python, you can build web apps, games, and more, in addition to performing common data science tasks.
R was originally designed as a statistics language and has evolved to do much more. R excels at exploratory data analysis, data visualization, and other data-related tasks. In many cases, each language's strengths can complement the other's.
Once you've come to a decision, signing up for a career track would be the next best step. You can begin with the R Programmer or Python Programmer track, which will give you a solid foundation and make your learning curve smoother. You can then jump in the Data Analyst with R or Data analyst with Python track. It includes the courses of the Programmer track, so you'll already have a head start on more than half of the courses. Finally, you can jump into the Data Scientist with R or Data Scientist with Python track, which already includes the courses of the Analyst track. This last track comprises several Machine Learning courses.
After completing these tracks, you'll have enough knowledge and skills to cherry-pick additional topics you'd like to learn next. There isn't a single way to complete courses in DataCamp - it depends on what you want to focus on first. If you're going to strengthen statistical methods, you can take advanced statistics courses, and if you're going to do Natural Language Processing, you will choose the Machine Learning courses that correspond, etc. This is simply a guide, but it's totally up to you.
Learn, practice and apply your data science skills with DataCamp. Enjoy your data science journey!