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Vital Skills for Data Science Specialization

Gain Exposure to Key Data Science Areas . Gain professional knowledge in the field of Data Science and learn applicable skills in Cybersecurity and Ethics.
Vital Skills for Data Science introduces students to several areas that every data scientist should be familiar with. Each of the topics is a field in itself. This specialization provides a “taste” of each of these areas which will allow the student to determine if any of these areas is something they want to explore further. In this specialization, students will learn about different applications of data science and how to apply the steps in a data science process to real life data. They will be introduced to the ethical questions every data scientist should be aware of when doing an analysis. The field of cybersecurity makes the data scientist aware of how to protect their data from loss.

This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

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Applied Learning Project
Projects will encourage students to engage in ethical discussions, hone networking skills, address cybersecurity threats, and explore the professional world of Data Science. These projects will help students develop an understanding of the field and gain skills that will help them be successful.

Course Information

Estimated Time: Approximately 5 months to complete Suggested pace of 4 hours/week

Difficulty: Intermediate

Free

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Course Information

Estimated Time: Approximately 5 months to complete Suggested pace of 4 hours/week

Difficulty: Intermediate