About this Course
If you’re curious about working in data science — or frankly, if it’s time to refresh your basic quantitative and programming skills — you’re not alone. To understand the what, why and how-to’s of data science, you’ll need to build up your foundational knowledge of algebra, calculus, statistics and Python — the common language of data science.
In this course, you’ll get a solid introduction to data science, including how to identify data types and collection methods. You’ll learn to use Python programming for data-science tasks, then refresh your knowledge of basic linear algebra and calculus. As you begin to explore the intricacies of data analysis, you’ll build your data-science vocabulary and learn about descriptive statistics, probability theory and data handling. In the end, you'll take away practical knowledge you can use to derive meaningful insights from complex data.
▸You can take this course on its own or to strengthen some of the quantitative and programming skills you’ll need to successfully apply to the Certificate in Data Science.
DESIGNED FOR
Anyone with basic knowledge of algebra and programming who wants to get started in data science.
See Requirements
ADMISSION REQUIREMENTS
To apply, you must have:
- Familiarity with algebra and basic statistics concepts (mean, median and standard deviation, etc.)
- Some exposure to programming (e.g. having basic scripting experience or completed an introductory programming course like Foundations of Programming (Python))
- Basic experience using spreadsheet software such Excel or Google Sheets to organize and format data
- Familiarity with basic data types (numeric, text, dates, etc.) and how to manipulate them
TIME COMMITMENT
Including time in class, you should expect to spend about seven to nine hours per week on coursework.
English Proficiency
If English is not your native language, you should have advanced English skills to enroll. To see if you qualify, make sure you are at the C1 level on the CEFR self-assessment grid. To learn more, see English Language Proficiency Requirements – Noncredit Programs.
International Students
Because this offering is 100% online, no visa is required and international students are welcome to apply. For more information, see Admission Requirements for International Students.
Technology Requirements
- Access to a computer with a recent operating system and web browser
- High-speed internet connection
- Headset and webcam (recommended)
Completing the Course
To successfully complete this course, you must fulfill the requirements outlined by your instructor.
▸ Explore More: Looking for something more advanced? Check out the Certificate in Data Science — or find the right data program for you.
WHAT YOU’LL LEARN
- Basic calculus, linear algebra and descriptive statistics
- Fundamental and advanced Python programming
- Data manipulation and data visualization using Python libraries
- SQL for working with relational databases
- APIs and Git for data and code management
GET HANDS-ON EXPERIENCE
You’ll work with real-world datasets and case studies, and you’ll use Python to wrangle data and create basic data visualizations.
EARN A DIGITAL BADGE
After successfully completing this course, you can claim a digital achievement badge that can be shared on LinkedIn and other social media sites. Learn more about digital badges.