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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.
This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web.
This is a 6-week evening program providing a hands-on introduction to the Hadoop and Spark ecosystem of Big Data technologies. The course will cover these key components of Apache Hadoop: HDFS, MapReduce with streaming, Hive, and Spark. Programming will be done in Python. The course will begin with a review of Python concepts needed for our examples. The course format is interactive. Students will need to bring laptops to class. We will do our work on AWS (Amazon Web Services); instructions will be provided ahead of time on how to connect to AWS and obtain an account.
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.