When you enroll in this course, you'll also be enrolled in this Specialization.
Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate
There are 4 modules in this course
This course provides a general introduction to the field of Data Science. It has been designed for aspiring data scientists, content experts who work with data scientists, or anyone interested in learning about what Data Science is and what it’s used for. Weekly topics include an overview of the skills needed to be a data scientist; the process and pitfalls involved in data science; and the practice of data science in the professional and academic world. This course is part of CU Boulder’s Master’s of Science in Data Science and was collaboratively designed by both academics and industry professionals to provide learners with an insider’s perspective on this exciting, evolving, and increasingly vital discipline.
Data Science as a Field 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.
This week we will talk about the past, present and future of data science. The growth of data science has been fueled by the growth of the internet, social media and online shopping as well as by the rapid increases in data storage capabilities. You will watch several short videos and participate in discussions about the future of data science.
What's included
4 videos4 readings2 discussion prompts
Show info about module content
4 videos•Total 15 minutes
Data Science as a Field Course Introduction •3 minutes
Where Does Data Science Come From?•3 minutes
The Current State of the Field•7 minutes
Where is Data Science Going?•2 minutes
4 readings•Total 31 minutes
Course Updates and Accessibility Support•1 minute
Earn Academic Credit for your Work!•10 minutes
Course Support•10 minutes
Assessment Expectations•10 minutes
2 discussion prompts•Total 20 minutes
Introduce Yourself!•10 minutes
Data Science and Privacy Concerns•10 minutes
Data Science in Industry, Government, and Academia
Module 2•4 hours to complete
Module details
This week you will watch videos and have a reading on some applications of data science in industry and academia. You will hear from data scientists in different fields to find out how they use data science.
Introduction to "Data Science in Business, Industry, and the Professional World"•1 minute
Brian Brown & Rinaldo Maldera•16 minutes
Natalie Jackson•12 minutes
Vilja Hulden•16 minutes
Robin Burke•10 minutes
Seth Spielman•17 minutes
Katharina Kann•15 minutes
Dan Larremore•10 minutes
7 readings•Total 70 minutes
Introducing Brian Brown and Rinaldo Maldera•10 minutes
Introducing Natalie Jackson•10 minutes
Introducing Vilja Hulden•10 minutes
Introducing Robin Burke•10 minutes
Introducing Seth Spielman•10 minutes
Introducing Katharina Kann•10 minutes
Introducing Dan Larremore•10 minutes
1 peer review•Total 60 minutes
Data Science in Industry, Government, and Academia•60 minutes
3 discussion prompts•Total 30 minutes
Applications of Data Science•10 minutes
Data Science at AirBnB•10 minutes
Application Areas and Skills•10 minutes
Data Science Process and Pitfalls
Module 3•4 hours to complete
Module details
This week you will learn about the importance of reproducibility and how to achieve it, learn the steps in a data analysis process and learn about the possible pitfalls in data science. You will watch demonstrating the various steps in the data science process and try out these processes for yourself on a different dataset.
This week you will learn about important ways of communicating your results. We will discuss the important things to know about presentations and reports. You will also learn about the importance of networking and try it out.
Do’s and Don’ts for Good Reports and Presentations•5 minutes
CU Boulder’s MS in Data Science: Where to Go from Here?•3 minutes
1 reading•Total 10 minutes
Imposter Syndrome•10 minutes
1 peer review•Total 60 minutes
Communicating your Results•60 minutes
3 discussion prompts•Total 30 minutes
Elevator Pitch•10 minutes
Attend a Meetup•10 minutes
Imposter Syndrome•10 minutes
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Build toward a degree
This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
View eligible degrees
Build toward a degree
This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
¹Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information.
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What will I get if I subscribe to this Specialization?
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. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.