Free Online Courses

• edX.org: free online courses

UIUC Data Mining Specialization

• It includes 5 courses:

• Pattern Discovery in Data Mining

  • Text Retrieval and Search Engines

  • UIUC online course: Cluster Analysis in Data Mining

  • Text Mining and Analytics

  • Data Visualization

Computing for Data Analysis (with R)

YouTube playlists for the videos of the course: week 1; week 2; week 3 and week 4.

Data Analysis (with R)

YouTube playlists for the videos of the course: http://bit.ly/16PPtuI

Machine Learning, by Andrew Ng, Stanford University

Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.

Free Stanford online course on Statistical Learning (with R)

• Covers linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines.

DataCamp courses and tutorials on R and Data Science

Social Network Analysis

Introduction to Data Science

• The lectures in week 3 give an excellent introduction to MapReduce and Hadoop, and demonstrate with examples how to use MapReduce to do various tasks.

Statistical Aspects of Data Mining with R

• Five-hour lecture videos on YouTube

• Natural Language Processing

• A course at Stanford University, containing 18 videos, with each of over 1 hour length

Google Developers R Programming Video Lectures

Open Access Sixteen Hour Online Course on Data Mining with Rattle

A Sequence of 9 Courses on Data Science on Coursera

• The courses, lectured by(Associate/Assistant) Professors of Johns Hopkins University, are designed for students to learn to become Data Scientists and apply their skills in a capstone project.

• Course 1: The Data Scientist’s Toolbox

• Course 2: R Programming

• Course 3: Getting and Cleaning Data

• Course 4: Exploratory Data Analysis

• Course 5: Reproducible Research

• Course 6: Statistical Inference

• Course 7: Regression Models

• Course 8: Practical Machine Learning

• Course 9: Developing Data Products

Stanford online course: Mining Massive Datasets

• Instructors: Jure Leskovec, Anand Rajaraman and Jeff Ullman, Stanford University

Statistics and R for the Life Sciences

• An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences