Practice Makes Perfect: Announcing Tracks, Challenges, and Projects

Tracks

Since we launched Dataquest a year ago, tens of thousands of people a month have learned data science and have started to experience the benefits in their respective careers. Dataquest continues to grow because of people like you who give us feedback and push us to improve the experience of learning data science.

We are announcing the Data Analyst and Data Scientist tracks to provide more organized learning paths and to help you better achieve your career goals. While you can still browse our regular Courses view from the navigation bar, Tracks make it easier to keep track of your progress.

Our Data Analyst track is for people who feel bottlenecked by their existing data analysis tools and want to learn Python and Pandas to enhance their workflow. This track helps people transition from Business Analyst, Marketing Analyst, and Research Analyst roles into Data Analyst roles.

Our Data Scientist track is for people who want to dive into more advanced data science techniques like Machine Learning and Computer Science and better prepare themselves for Data Scientist positions.

Challenges

We are huge believers in learning through doing and we are announcing Challenges and Projects to enable you to get more data science experience.

Challenges are stand-alone exercises that let you test what you've learned. While challenges are highly structured and guided, we provide feedback by evaluating your code in our code cells. If you've heard enough and want to check out our first challenge, head over to Dataquest.

If you get stuck on a challenge, we receommend posting in our forums or discussing in our Slack community.

Projects

Projects are more open-ended and closely resemble the workflow that data analysts and data scientists in industry experience on a daily basis. Completing projects and building a portfolio is the best way to stand out on job applications, as you're able to demonstrate both your data science skills as well as your ability to step through the entire data science lifecycle. Since projects are much more open-ended than challenges, you will need to highly specific and personal feedback to help you better understand your strengths and weaknesses.

Our first project is all about analyzing US births and we encourage you to check it out the project page.

Srini Kadamati

Srini Kadamati

Director of Content at Dataquest.io. Based in Austin, TX.

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