About this Specialization

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Interested in learning more about data science, but don’t know where to start? This 4-course Specialization from IBM will provide you with the key foundational skills any data scientist needs to prepare you for a career in data science or further advanced learning in the field. This Specialization will introduce you to what data science is and what data scientists do. You’ll discover the applicability of data science across fields, and learn how data analysis can help you make data driven decisions. You’ll find that you can kickstart your career path in the field without prior knowledge of computer science or programming languages: this Specialization will give you the foundation you need for more advanced learning to support your career goals. You’ll grasp concepts like big data, statistical analysis, and relational databases, and gain familiarity with various open source tools and data science programs used by data scientists, like Jupyter Notebooks, RStudio, GitHub, and SQL. You'll complete hands-on labs and projects to learn the methodology involved in tackling data science problems and apply your newly acquired skills and knowledge to real world data sets. In addition to earning a Specialization completion certificate from Coursera, you’ll also receive a digital badge from IBM recognizing you as a specialist in data science foundations. This Specialization can also be applied toward the IBM Data Science Professional Certificate.
Learner Career Outcomes
46%
Started a new career after completing this specialization.
19%
Got a pay increase or promotion.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Approx. 4 months to complete
Suggested 4 hours/week
English
Subtitles: English, Russian, Korean, Persian, Arabic
Learner Career Outcomes
46%
Started a new career after completing this specialization.
19%
Got a pay increase or promotion.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Approx. 4 months to complete
Suggested 4 hours/week
English
Subtitles: English, Russian, Korean, Persian, Arabic

There are 4 Courses in this Specialization

Course1

Course 1

What is Data Science?

4.7
stars
38,132 ratings
7,069 reviews
Course2

Course 2

Tools for Data Science

4.5
stars
18,789 ratings
2,770 reviews
Course3

Course 3

Data Science Methodology

4.6
stars
14,430 ratings
1,658 reviews
Course4

Course 4

Databases and SQL for Data Science

4.7
stars
11,625 ratings
1,281 reviews

Offered by

IBM logo

IBM

Frequently Asked Questions

  • 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.

  • 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 Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.

  • 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.

  • Upon completion of the program, you will receive an email from Acclaim with your IBM Badge recognizing your expertise in the field. Some badges are issued almost immediately after completion of the badge activities, while others may take 1-2 weeks before they are issued. Once issued, you will receive a notification email from admin@youracclaim.com with instructions for claiming the badge. Learn more about IBM Badges 

  • 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 IBM Course, "What is 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

  • The Specialization consists of 4 courses. Suggested time to complete each course is 3-4 weeks. If you follow recommended timelines, it would take 3 to 4 months to complete the entire Specialization.

  • This Specialization is intended for learners wanting to build foundational skills in data science. No prior background in data science or programming is required.

  • In order to get the most out of this Specialization, it is recommended to take the courses in the order they are listed.

  • No, there is no university credit associated with completing this Specialization.

  • In this Specialization, learners will develop foundational data science skills to prepare them for a career or further learning that involves more advanced topics in data science.

More questions? Visit the Learner Help Center.