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Master of Science in Data Science
209.946.2992
datascience@pacific.edu
Dina Dell'Aringa
Administrative Assistant

Certificate in Computing for Data Science


About the program
Data Analytics is one of the hottest topics in industry today and the skills required to enter this exciting world are in high demand. This 10-week certificate course in Computing for Data Science will introduce participants to all of the foundational skills they require to begin their data science/analytics career. You will learn how to conduct data analysis using some of the most sought-after programming language skills, such as Python and R. By the end of the course, participants will be able to tackle typical data analysis problems that companies often face. The course focuses on how to apply this knowledge to real-world data sets, with an emphasis on statistical and machine learning analysis, and predictive modeling.

Location: Online
Duration: 10 weeks
Times: Saturday's, weekday evening
Cost: $2,490

What you will learn:

  • How to manipulate data files within the Unix Shell
  • Creating dynamic journals and reports, with embedded R and Python code using Jupyter Notebook
  • The foundational concepts of data structures and the syntax of the R and Python programming languages
  • All of the essential programming constructs
  • How to use some of the most powerful, and most commonly used programming packages
  • How to design and develop analytic solutions

Get practical, hands-on experience
You will not only learn the mathematical and programming skills necessary for a career in Data Analytics, but also practical hands-on experience in some of the latest tools used in industry today, including:

  • The R and Python programming languages
  • RStudio development environment
  • Numpy
  • Matplotlib
  • Pandas

Is the Certificate in Computing for Data Science for you?
The Computing for Data Science Certificate is intended for those who wish to enhance career through increasing their understanding of how to access data, prepare it for analysis, apply typical analytic techniques, and produce high impact presentations.


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