Embarking on a data science career path? Springboard’s Data Science Career Track is a popular choice, but it incorporates a coding and statistics challenge as part of its application process. This challenge is designed to ensure you possess the foundational skills necessary to thrive in their intensive program.
To effectively tackle this challenge, a solid grasp of Python programming and statistical concepts is essential. The Career Track curriculum immediately delves into advanced libraries such as pandas and matplotlib, presuming a pre-existing comfort with Python fundamentals. For those new to Python, Springboard offers a preparatory Data Science Career Track Prep course. Alternatively, interactive learning environments like Dataquest can rapidly bring you up to speed with the Python proficiency required for data science. If you prefer reading, numerous free Python books are available in resources like this free book list.
Beyond programming, a college-level understanding of statistics and linear algebra is also critical. The application challenges effectively filter candidates lacking this knowledge base. The curriculum assumes familiarity with these subjects, and unlike introductory courses such as Andrew Ng’s Machine Learning course on Coursera (link), dedicated time isn’t spent on foundational linear algebra within the Data Science Career Track itself.
The application process is generally straightforward:
- Submit your application online (typically takes 10-15 minutes).
- Complete the coding and statistics challenge (allow approximately 3 hours).
- Upon successfully passing the challenge, select your preferred start date and payment plan.
- Begin your immersive data science learning journey.
In conclusion, thorough preparation for the Springboard Data Science Career Track coding and stats challenge is paramount for your success in the program. Prioritize building a robust foundation in Python, statistics, and linear algebra. With adequate preparation in these key areas, you will be well-positioned to confidently pass the challenge and excel in your data science career track.
