Cohorts begin every Monday | Apply tuition to the Career Track

Data Science Prep Course

Learn the foundational coding and statistics skills needed to start your career in data science.

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.
By the end of the course, you'll be able to:
Use Python to complete real-world coding exercises and begin your data science journey
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

Who this course is for

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 and are eager to learn more advanced concepts where necessary.

What you'll learn

Introduction to Data Science & Python
Intermediate Python for Data Science
Foundations of Probability
Computer Science Primer
Exploring Data
Python Case Study
Estimated time: 15+ Hours
  • Introduction to Python
  • Statistics refresher
  • Data visualization
Estimated time: 5+ Hours
  • Dictionaries and their applications
  • Advanced control flow techniques
  • Input and output
Estimated time: 5+ Hours
  • Counting and probability
  • Conditional probability and independence
  • Bayes Theorem
Estimated time: 10+ Hours
  • Basics of data structures
  • Fundamentals of algorithm analysis
  • Basic algorithms: sort and search
Estimated time: 15+ Hours
  • Assemble your Python toolkit
  • Data wrangling with Pandas
  • Data visualization with matplotlib
Estimated time: 10+ Hours
  • Acquire, clean, and transform data
  • Explore data, identify patterns
  • Solve a realistic business problem for Yelp

Request a detailed syllabus


Your own mentor, focused on your success

Each week, you'll have 30 minutes of 1-on-1 time with your personal mentor, a data science expert. You can expect:

Personalized learning support

Get assistance on any problem, big or small, from your personal mentor, an industry expert

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
"My mentor was great, had real-world experience and served as a great resource to help me define a project as well as solve technical questions with my coding. She also provided extra resources if I wanted to practice or further develop a skill from the program."
Esme Gaisford
Data science graduate
Alex Chao
Data Scientist
Ike Okonkwo
Data Scientist
Mitul Tiwari
Lead Data Scientist
Sameera Poduri
Data Science Manager

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Cohorts begin every Monday. Apply tuition to the Career Track. Read how in FAQs.

One time payment


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

Frequently asked questions

How long is the course?

The total estimated workload is 40-60 hours, expected to be completed in 4-6 weeks.

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.