Introduction to Data Science Specialization
Launch your career in data science. Gain foundational data science skills to prepare for a career or further advanced learning in data science.
Skills you will gain
About this Specialization
Applied Learning Project
All courses in the specialization contain multiple hands-on labs and assignments to help you gain practical experience and skills with a variety of data sets and tools like Jupyter, GitHub, and R Studio. Build your data science portfolio from the artifacts you produce throughout this program. Course-culminating projects include:
Creating and sharing a Jupyter Notebook containing code blocks and markdown
Devising a problem that can be solved by applying the data science methodology and explain how to apply each stage of the methodology to solve it
Using SQL to query census, crime, and demographic data sets to identify causes that impact enrollment, safety, health, and environment ratings in schools
How the Specialization Works
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.
Svetlana LevitanSenior Developer Advocate with IBM Center for Open Data and AI Technologies
Frequently Asked Questions
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More questions? Visit the Learner Help Center.