Doing Data Science


In this course, students get a practical hands-on overview of the end-to-end data science process using industry standard tools and techniques. Students will also be given real-world examples to connect the dots between data science concepts and their practical application in industry settings.


Tools for Data Science, Reproducible Research, Data Selection, Data Wrangling, Exploratory Data Analysis (EDA), Machine Learning, Time Series Modeling and Forecasting


  • R, RStudio, knitr, Github, and packages for Web scraping, Data Wrangling, Machine Learning and Time Series modeling.