Introduction to Data Analysis using R

The course examines different approaches to a data analysis project, with a framework for organizing an analytical effort. Popular tools for data analysis, such as R and Python, are introduced to carry out analysis. The course covers how to obtain and manipulate the raw data for use, as well as the basic exploratory analysis and common data analytical techniques such as regression, simulation, estimation and forecasting. It includes several graphing and visualization tools to understand the data and to present findings and results. Overall goal of this class is to introduce participants to the discipline of data analysis/ data mining, a science of understanding and analyzing data. The class is designed to provide participants with the tools they need for solving real world problems using statistics and a better understanding of data analysis techniques. By the end of the course, you will learn a working framework to approach any data analysis project. You will be able to use R (or Python) to complete a large data analysis project, including a write-up with findings, insights and visuals. All tools used are open sourced. In this program, you will learn the practical expertise regarding data analysis. You will understand how it is the process of transforming data into useful information to support decision making. It is the foundation for data mining, business intelligence, and predictive analytics. This course presents the tools, techniques and common practices used in the industry, including how to obtain, manipulate, explore, model, simulate and present data. It will help you build the essential technical skills to perform as data analyst or data scientist, and to continue other course studies in the certificate program. This is module#3