Loading...

Blog

Latest posts

How to Define Your Learning Path in Data Science

Deciding what to learn next is hard.

Data science is a booming field with an ever-increasing number of specializations and roles to fill. Along with the boom, there are more courses, books, and articles that are aimed towards helping data scientists learn the skills they need to be good at their jobs (or to get a job). There are so many things to learn. So what is the best way to decide where you should go next?

Basics

Once you have a solid understanding of the basic concepts that make up this thing we call data science, there are a lot of different options for how to decide what to learn next. There is no perfect way, and there are pros and cons to each learning path you might take.

Option 1: Focus Your Learning on What’s New

Pros:

Cons:

Option 2: Specialize in an Area of Interest

Pros:

Cons:

Option 3: Learn Things to Complete a Job or Project

Pros:

Cons:

Option 4: Follow a Curriculum

Pros:

Cons:

Option 5: Add Value to What You Provide

Pros:

Cons:

Conclusion

This post was originally posted on Towards Data Science.

APPLY NOW