IBM Data Science Professional Certificate

• What is the refund policy?

  If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

• Can I just enroll in a single course?

  Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Certificate, you’re automatically subscribed to the full Certificate. Visit your learner dashboard to track your progress.

• Is this course really 100% online? Do I need to attend any classes in person?

  This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

• How can I earn my IBM Badge?

  Upon completion of this program, you will receive an email from Coursera with directions on how to claim your IBM Badge through Acclaim. Learn more about IBM Badges 

• What is data science?

  D​ata science is the process of collecting, storing, and analyzing data. Data scientists use data to tell compelling stories to inform business decisions. Learn more about what data science is and what data scientists do in the first course of this Professional Certificate, "What is Data Science?"

• What are some examples of careers in data science?

  An understanding of data science and the ability to make data driven decisions is useful in any career, but some careers specifically require a data science background. Some examples of careers in data science include: 

  -​ Business Intelligence Analyst

  -​ Data Analyst

  -​ Data Architect

  -​ Data Engineer

  -​ Data Scientist

  -​ Machine Learning Engineer

  -​ Marketing Analyst

  -​ Operations Analyst

  -​ Quantitative Analyst

• How long does it take to complete the Professional Certificate?

  The Professional Certificate requires completion of 9 courses. Each course typically contains 3-6 modules with an average effort of 2 to 4 hours per module. If learning part-time (e.g. 1 module per week), it would take 6 to 12 months to complete the entire certificate. If learning full-time (e.g. 1 module per day) the certificate can be completed in 2 to 3 months.

• What background knowledge do I need for this program?

  This Professional Certificate is open for anyone with any job and academic background. No prior computer programming experience is necessary, but is an asset, as are familiarity working with computers, high school math, and communication and presentation skills. For the last few courses, knowledge of calculus and linear algebra is an asset but not an absolute requirement.

• Do I need to take the courses in a specific order?

  Yes, it is highly recommended to take the courses in the order they are listed, as they progressively build on concepts taught in previous courses. For example the Data Analysis, Data Visualization, and Machine Learning courses require knowledge of Python covered earlier in the program.

• Will I earn university credit for completing the Professional Certificate?

  No, there is no university credit involved with taking these courses.

• What will I be able to do upon completing the Professional Certificate?

  Become job ready for a career in Data Science. Develop practical skills using hands-on labs in Cloud environments, projects and captsones.

• I already completed some of the other courses in this Professional Certificate. Will I get "credit" for them?

  If you have already completed some of the courses in this Professional Certificate, either individually or as part of another Specialization, they will be marked as "Complete". You do not have to take those courses again, and will be able to finish the Professional Certificate more quickly. You will only need to complete the courses that you have not yet completed.

• I have already completed the Introduction to Data Science Specialization. Can I still enroll in this Professional Certificate?

  Yes, absolutely. Any courses that you have already completed as part of that Specialization will be marked as "Complete". You do not have to take those courses again and will be able to finish the Professional Certificate more quickly.

• Which program should I enroll in - the Introduction to Data Science Specialization, or this Professional Certificate?

  This Professional Certificate consists of 9 courses. The "Introduction to Data Science" Specialization has 4 courses, all of which are also included in this Professional Certificate.

  If you are unsure about your ability to commit to the level of effort and time required to complete this Professional Certificate, we recommend starting with the Introduction to Data Science Specialization, which has fewer courses. If, after completing the Specialization, you are still determined to continue building your data science skills, you can then enroll for this Professional Certificate and then just complete the courses that are not in the Specialization.

• I have already completed the Applied Data Science Specialization. Can I still enroll in this Professional Certificate?

  Yes, absolutely. Any courses that you have already completed as part of that Specialization will be marked as "Complete". You do not have to take those courses again and will be able to finish this Professional Certificate more quickly.

• How can I access job opportunities with IBM and other organizations after completing this Professional Certificate?

  As a Coursera learner who completes this Professional Certificate, you will have special access to join IBM’s Talent Network. Our Talent Network members receive all of the tools you need to land a dream job with IBM - sent directly to your inbox! You will get job opportunities as soon as they are posted, recommendations to apply matched directly to your skills and interests, and tips and tricks to help you stand apart from the crowd.

More questions? Visit the Learner Help Center.