Data Science Career Track Prep Course

Learn the foundational coding and statistics skills needed to pass our Data Science Career Track admissions technical skills survey.

About the course

Need more prep for our Data Science Career Track? You've come to the right place. In this mentor-led course, you'll spend 4-6 weeks learning foundational skills in Python programming and statistics, as well as introductory data science concepts—all via a curriculum specifically designed to help you pass the Data Science Career Track admissions technical skills survey. 

Use Python to complete real-world coding exercises and begin your data science journey

Your own mentor, focused on your success

What you'll learn




Confidently tackle our Data Science Career Track technical skills survey

Determine whether the Data Science Career Track is right for you by trialing our unique Springboard learning experience

Each week, you'll have 30 minutes of 1-on-1 time with your personal mentor, a data science expert. You can expect:
Get assistance on any problem, big or small, from your personal mentor, an industry expert
Personalized learning support
Control over your agenda
Decide what you want to talk about, from weekly deliverables to career advice and more
Inspiration and motivation from the best
As an experienced data scientist, your mentor is your window into the world of data science

Frequently asked questions

When can I start the prep course?

The prep course starts each Monday. Simply click “Enroll now” and select the cohort that best works for you.

How long is the course?
The total estimated workload is 40-60 hours, expected to be completed in 4-6 weeks. You may complete the course faster if you have previous programming experience or if you are able to dedicate additional time to the material. You may also need more time to finish if you are brand new to programming or have a constrained schedule—but that's no problem; you have access to the course as long as you need!

Are there any prerequisites for this course? Do I need to know Python?

No prior coding experience is required, but to be successful, we recommend that students are already proficient in high-school level mathematics with an openness to learning more advanced concepts where necessary.

Does this prep course guarantee I get accepted into the Data Science Career Track?

This course will prepare you with the skills needed in Python and statistics to pass our admissions technical skills survey, but enrolling in this course does not guarantee admission into the Data Science Career Track.

How do I transition from this course to the Data Science Career Track?

You may apply to the Data Science Career Track at any time, even after enrolling in the prep course. As soon as you feel comfortable in Python and statistics, we encourage you to fill out an application and take the admissions technical skills survey. However, students who complete the entire prep course and submit the final project will be fast-tracked through the Career Track application process.

What role does my mentor play?

You’ll interact 1-on-1 with your personal mentor every week in a 30-minute video call. Your mentor is there to help you understand the material, push you to succeed, assist with any technical or broader questions, and offer insight into the world of data science. Feel free to develop your mentor relationship however works best for you both!

What additional support will I have?

You will be invited to join our broader weekly data science office hours with all current data science students. You will also have access to the community, where you can ask technical questions or seek assistance from fellow classmates or the course community manager, an expert data scientist. Furthermore, you will have the support of a dedicated student advisor, there to assist you throughout the course. Finally, your classmates! You aren’t going through this alone; you'll have the support of others starting out on their own unique data science journeys.

Will I have lifetime access to the material?

Yes, once you enroll you will have lifetime access to the curriculum and exercises. You will not, however, have lifetime access to the mentorship. You will receive six mentor calls, one per week, for the expected 4-6 week duration of the course.

What happens if I need more than six weeks to finish the material?

You will have 6 weekly mentor calls once the course starts and you will be paired with your mentor before the official start date. If you need additional time to complete, you are able to continue through the curriculum without a mentor beyond 6 weeks for as long as needed as you will have lifetime access.

Does this course make me eligible for the job guarantee?

Job guarantee eligibility for the Data Science Career Track is determined independently of the prep course; to see if you qualify, please review our job guarantee.

What does lifetime access to my Springboard account mean?

Once you complete the course, you'll have lifetime access to your Springboard account, including the online community and office hours. We'll even provide you with an additional six months of access to external resources, upon request. Whenever our course development team updates the curriculum, you'll see it too. Lifelong learning guaranteed!

Is this course conducted online or in person?

All our courses take place entirely online. All you need is an internet connection.

Can my employer pay for this course on my behalf?

Absolutely! Many of our students have been sponsored by their employers. Most companies are very happy to invest in their employees' learning and development. Check with your employer to find out whether they can support your tuition.

Can I receive a refund if I cancel without completing the course?
Due to the short duration of the course and fast paced nature of the curriculum we do not offer refunds for our prep course. If you have a unique situation we encourage you to reach out to your student adviser to discuss potential options.

Don't see your question here? Contact us at

This course is for go-getters who want to enroll in our Data Science Career Track, but who need an introduction to, or a refresher in, Python programming or core data science concepts. No prior coding experience is required, but to be successful, we recommend that students are already proficient in high-school level mathematics with an openness to learning more advanced concepts where necessary.

By the end of the course, you'll be able to:

Meet some of the mentors

Alex Chao

Data Scientist

Mitul Tiwari

Lead Data Scientist

Ike Okonkwo

Senior Data Scientist

Sameera Poduri

Head of Data Science

Our world-class mentors are hand-picked for their experience and love of teaching.

Duration of the program 

4-6 weeks 

Enroll now

Who this course is for

Enroll now


Time to complete depends on your weekly commitment. On average, it takes 4-6 weeks to complete on a 10 to 15-hour-per-week schedule.


What's included in the course fee:

Curriculum created by educators and experts in Python and data science—specifically designed for future Data Science Career Track students

6 weekly sessions (30 minutes each) with your expert mentor

Lifetime access to the curriculum and practice exercises

Proprietary learning content, practice exercises, quizzes, and projects

Dedicated student advisor and student operations support

Weekly office hours with the broader Springboard data science community

Mentor support, including review of exercises and your final project

Preferential Data Science Career Track application review and admissions fast-tracking upon course completion

1. Introduction to Data Science & Python
  • Introduction to Python
  • Statistics refresher
  • Data visualization

Estimated Time: 10-15 hours

The curriculum is split into 6 content areas; during each one you'll complete detailed practice exercises to reinforce key learning concepts.
2. Intermediate Python for Data Science
  • Dictionaries and their applications
  • Advanced control flow techniques
  • Input and output

Estimated Time: 4-5 hours

What you'll learn

3. Foundations of Probability
  • Counting and probability
  • Conditional probability and independence
  • Bayes Theorem

Estimated Time: 4-5 hours

5. Exploring Data
  • Assemble your Python toolkit
  • Data wrangling with Pandas
  • Data visualization with matplotlib

Estimated Time: 10-15 hours

6. Python Case Study
  • Acquire, clean, and transform data
  • Explore data, identify patterns
  • Solve a realistic business problem for Yelp

Estimated Time: 5-10 hours

4. Computer Science Primer
  • Basics of data structures
  • Fundamentals of algorithm analysis 
  • Basic algorithms: sort and search

Estimated Time: 5-10 hours

Download a detailed syllabus

Cohorts begin every Monday

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