Showing all 4 results

Data Visualization

Subjects
Level
Time
    R for Business Analysts

    This class will be an introduction to the statistical programming language R for business analysts. We’ll explore data science use cases in the business realm and use R for data wrangling, data mining, visualization and prediction. Throughout the class we will be approaching business problems analytically and we’ll use R to explore data, make better business decisions and identify areas for improving performance. The combination of data analytics, R and the data science process will provide the foundation for using R for data science business problems. Students should come prepared with an understanding of computer programming and a curiosity for data science.

    August 8, 2017 - September 5, 2017 7:00-9:30pm
    Data Science with R: Data Analysis and Visualization

    This course is a 35-hour program designed to provide a comprehensive introduction to R for Data Analysis and Visualization. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. In addition to a theoretical framework in which to understand the process of data analysis, this course focuses on the practical tools needed in data analysis and visualization. By the end of the course, you will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes.

    July 29, 2017 - August 26, 2017 10:00am-5:00pm Other Dates
    Data Science with Python: Data Analysis and Visualization

    This class is a comprehensive introduction to Python for Data Analysis and Visualization. This class targets people who have some basic knowledge of programming and want to take it to the next level. It introduces how to work with different data structures in Python and covers the most popular Python data analysis and visualization modules, including numpy, scipy, pandas, matplotlib, and seaborn. We use Ipython notebook to demonstrate the results of codes and change codes interactively throughout the class.

    July 30, 2017 - August 27, 2017 1:00-5:00pm Other Dates
    Deposit Only - Data Science Bootcamp: Intensive 12-Week
    September 18, 2017 - December 15, 2017