Certificate in Data Analytics in R
R is now considered one of the most popular analytics tools in the world. In this certificate program you will develop the skill set necessary to perform all key aspects of data science efficiently. The courses cover the application of core analytics concepts in the R programming environment to allow a scalable implementation.
You’ll learn techniques for manipulating and visualizing data, describing data through descriptive statistics, and clustering. You’ll extend these basic reporting approaches through classification and predictive analytics using traditional parametric models (regression and logistic regression) as well as machine learning techniques. In addition, you’ll develop linear, nonlinear, and Monte Carlo decision-making models that will allow you to make more informed decisions.
The courses in this certificate will equip you to…
- Understand, model and visualize data using R
- Make predictions for qualitative and quantitative dependent variables using R
- Efficiently use the full breadth of parametric and non-parametric predictive data models in R
- Develop models to make complex, large-scale decisions through the use of mathematical approximations such as optimization (linear, nonlinear, dynamic programming) and Monte Carlo simulation using R
This certificate has 3 online courses requiring ~72 hours to complete.
- Clustering, Classification, and Machine Learning in R
- Predictive Analytics in R
- Prescriptive Analytics in R
Who Should Take This Certificate Series?
This certificate is appropriate for analysts, developers, data scientists, functional managers, consultants, any professional that uses data to make business decisions.
Participants who successfully complete all 3 courses in this certificate series will receive a Certificate in Data Analytics in R from Cornell University’s SC Johnson College of Business.
Participants will also receive 1.5 Professional Continuing Education Units (CEUs) for each course that is successfully completed.