Showing all 8 results

Data Science Courses

Subjects
Level
Time
    Introductory Python
    Introductory

    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 I/O, and introduce modules for downloading data from the web. Advanced data analyses, such as machine-learning, are covered in more advanced classes.

    January 23, 2017 - February 15, 2017 7:00-9:30pm Other Dates
    Big Data with Hadoop and Spark

    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.

    January 23, 2017 - March 6, 2017 7:00-9:30pm Other Dates
    Data Science with Python: Machine Learning

    This 20-hour course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them. The five sessions cover: simple and multiple Linear regressions; classification methods including logistic regression, discriminant analysis and naive bayes, support vector machines (SVMs) and tree based methods; cross-validation and feature selection; regularization; principal component analysis (PCA) and clustering algorithms. After successfully completing of this course, you will be able to explain the principles of machine learning algorithms and implement these methods to analyze complex datasets and make predictions.

    October 23, 2016 - December 4, 2016 1:00-5:00pm Other Dates
    Data Science with R: Machine Learning

    This 35-hour course introduces both the theoretical foundation of machine learning algorithms as well as their practical applications of machine learning techniques in R. It will introduce you to data mining, performance measures and dimension reduction, regression models, both linear and generalized, KNN and Naïve Bayes models, tree models, and SVMs as well as the Association Rule for analysis. After successfully completing of this course, you will be able to break down the mathematics behind major machine learning algorithms, explain the principles of machine learning algorithms, and implement these methods to solve real-world problems.

    January 21, 2017 - February 25, 2017 10:00am-5:00pm Other Dates
    Data Science with Python: Data Analysis and Visualization

    This class is a comprehensive introduction to data analysis with the Python programming language. 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 data analytics 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.

    October 23, 2016 - February 18, 2016 Other Dates
    Data Science with R: Data Analysis and Visualization

    This course is a 35-hour program designed to provide a comprehensive introduction to R. 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 you will learn 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.

    October 22, 2016 - December 3, 2016 10:00am-5:00pm Other Dates
    Intro to Data Science with R (2-day intensive)
    This course is a 2-day intensive workshop on basic R programming. You’ll learn how to load, save, and transform data as well as write functions, generate graphs, and run basic statistical models. You’ll acquire not only the theoretical framework that helps you understand the process of data analysis, but also practical skills that allow you to utilize as soon as you get back from the course.
    October 13, 2016 - October 14, 2016 9:00am-5:00pm
    Deposit Only - Data Science Bootcamp: Intensive 12-Week
    January 9, 2017 - March 31, 2017 Other Dates