About this Specialization

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Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions. The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the Capstone Project, you will use real data to address an important issue in society, and report your findings in a professional-quality report. You will have the opportunity to work with our industry partners, DRIVENDATA and The Connection. Help DRIVENDATA solve some of the world's biggest social challenges by joining one of their competitions, or help The Connection better understand recidivism risk for people on parole in substance use treatment. Regular feedback from peers will provide you a chance to reshape your question. This Specialization is designed to help you whether you are considering a career in data, work in a context where supervisors are looking to you for data insights, or you just have some burning questions you want to explore. No prior experience is required. By the end you will have mastered statistical methods to conduct original research to inform complex decisions.
Learner Career Outcomes
50%
Started a new career after completing this specialization.
17%
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. 5 months to complete
Suggested 3 hours/week
English
Subtitles: English, Korean, German
Learner Career Outcomes
50%
Started a new career after completing this specialization.
17%
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. 5 months to complete
Suggested 3 hours/week
English
Subtitles: English, Korean, German

There are 5 Courses in this Specialization

Course1

Course 1

Data Management and Visualization

4.4
stars
768 ratings
214 reviews
Course2

Course 2

Data Analysis Tools

4.5
stars
369 ratings
80 reviews
Course3

Course 3

Regression Modeling in Practice

4.4
stars
249 ratings
48 reviews
Course4

Course 4

Machine Learning for Data Analysis

4.2
stars
242 ratings
53 reviews

Offered by

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Wesleyan University

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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.

  • This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • No, Specializations are a premium product, and learners must pay or apply for financial aid to join them. You can access individual course content for free by searching for the course title in the catalog and choosing the This Course Only option when enrolling. You will not earn a Certificate in the free version of the course, or be able to access the Capstone Project.

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 6-7 months.

  • Each course in the Specialization is offered on a regular schedule, with sessions starting about once per month. If you don't complete a course on the first try, you can easily transfer to the next session, and your completed work and grades will carry over. The Capstone Project will be offered four times per year on a recurring schedule.

  • We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.

  • Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • You will be able to access and manage data using either the Python or SAS programming language, explore patterns and associations among variables, and use machine learning methods to develop predictive algorithms. Additionally, you will have a portfolio of hands-on project work that demonstrates your ability to apply all of these methods to real-world situations.

  • You may choose to use either Python or SAS to complete the assignments. Both of these software packages are being made freely available.

  • This Specialization is appropriate for anyone interested in learning more about data analysis, including those new to the field. Some knowledge of basic programming and familiarity with linear algebra concepts may be helpful, but no specific background is required.

More questions? Visit the Learner Help Center.