Data Science (HarvardX)

Colleagues, the “Data Science” program from  HarvardX prepares you with the necessary knowledge base and useful skills to tackle real-world data analysis challenges. The program covers concepts such as probability, inference, regression, and machine learning and helps you develop an essential skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and reproducible document preparation with RStudio. In each course, we use motivating case studies, ask specific questions, and learn by answering these through data analysis. Case studies include: Trends in World Health and Economics, US Crime Rates, The Financial Crisis of 2007-2008, Election Forecasting, Building a Baseball Team (inspired by Moneyball), and Movie Recommendation Systems. You will learn Fundamental R programming skills, Statistical concepts such as probability, inference, and modeling and how to apply them in practice, Gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr, Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio, Implement machine learning algorithms, and In-depth knowledge of fundamental data science concepts through motivating real-world case studies. The 9 courses that comprise this program include: 1) R Basics, 2) Visualization, 3) Probability, 4) Inference and Modeling, 5) Productivity Tools, 6) Wrangling, 7) Linear Regression, 8) Building Machine Learning Models, and 9) Capstone Project.

Enroll today!: Teams and executives are welcome: https://edx.sjv.io/9LVMxy

Recommended Reading: “Data-Driven Organizations” series.

1 - The Promise of Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much career success from the Data Science Academy (please subscribe and share with your colleagues)