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.
This course is part of the Vital Skills for Data Science Specialization
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About this Course
Knowledge of R required and knowledge of tidyverse is helpful.
What you will learn
By taking this course, you will be able explain what data science is and identify the key disciplines involved.
You will be able to use the steps of the data science process to create a reproducible data analysis and identify personal biases.
You will be able to identify interesting data science applications, locate jobs in Data Science, and begin developing a professional network.
Skills you will gain
- Data Science
- Applied Mathematics
- Information Science
- Statistics
- Computer Science
Knowledge of R required and knowledge of tidyverse is helpful.
Offered by

University of Colorado Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
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Syllabus - What you will learn from this course
Introduction to Data Science: the Past, Present, and Future of a New Discipline
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.
Data Science in Industry, Government, and Academia
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.
Data Science Process and Pitfalls
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.
Communicating Your Results
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.
Reviews
- 5 stars80%
- 4 stars6.66%
- 3 stars6.66%
- 1 star6.66%
TOP REVIEWS FROM DATA SCIENCE AS A FIELD
Very practical overview of the field. Does require knowledge of R to do 2 simple projects if you take it for credit.
Exercises and lectures were hands-on and informative. I enjoyed the practical advice on data science as a profession.
Good course for exercise R programming, data analysis and communication skills.
A great introduction to Data Science, with plenty of practical assignments that are flexible enough to explore our own questions of interest.
About the Vital Skills for Data Science Specialization
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.

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