Data Science Courses/MOOCS

Coursera

Specializations:

Data Science Specialization

Machine Learning Specialization

Data Analysis and Interpretation Specialization

Mining Massive Data Sets (Stanford) https://www.coursera.org/course/mmds

Big Data specialization (UC San Diego): https://www.coursera.org/specializations/big-data
Introduction to Big Data https://www.coursera.org/learn/intro-to-big-data
Hadoop Platform and Application Framework https://www.coursera.org/learn/hadoop
Introduction to Big Data Analytics https://www.coursera.org/learn/bigdata-analytics
Machine Learning with Big Data https://www.coursera.org/learn/machinelearningwithbigdata
Introduction to Graph Analytics https://www.coursera.org/learn/graph-analytics
Big Data – Capstone Project https://www.coursera.org/learn/big-data-capstone

Machine Learning specialization (U. of Washington): https://www.coursera.org/specializations/machine-learning
Machine Learning Foundations: A Case Study Approach https://www.coursera.org/learn/ml-foundations
Regression https://www.coursera.org/learn/ml-regression
Classification https://www.coursera.org/learn/ml-classification
Recommender Systems & Dimensionality Reduction https://www.coursera.org/learn/ml-recommenders
Clustering & Retrieval https://www.coursera.org/learn/ml-clustering-and-retrieval
Machine Learning Capstone: An Intelligent Application with Deep Learning https://www.coursera.org/learn/ml-capstone

Data Analysis and Interpretation specialization (Weslayan): https://www.coursera.org/specializations/data-analysis
Data Management and Visualization https://www.coursera.org/learn/data-visualization
Data Analysis Tools https://www.coursera.org/learn/data-analysis-tools
Regression Modeling in Practice https://www.coursera.org/learn/regression-modeling-practice
Machine Learning for Data Analysis https://www.coursera.org/learn/machine-learning-data-analysis
Data Analysis and Interpretation Capstone https://www.coursera.org/learn/data-analysis-capstone


edX


DataCamp

Introduction to R

Data Analysis and Statistical Inference

  • Introduction to R
  • Introduction to data
  • Probability
  • Foundations for inference: Sampling distributions
  • Foundations for inference: Confidence intervals
  • Inference for numerical data
  • Inference for categorical data
  • Introduction to linear regression
  • Multiple linear regression

Intro to Computational Finance with R

  • Return calculations
  • Random variables and probability distributions
  • Bivariate distributions
  • Simulating time series data
  • Analyzing stock returns
  • Constant expected return model
  • Introduction to portfolio theory
  • Computing efficient portfolios using matrix algebra

YouTube
Data School – Data science for beginners! | Data Science
edureka! | Data Science
Zipfian Academy | Data Science
David Langer | Data Science with R
Derek Kane | Data Science
MarinStatsLectures | Statistics
LearnR | R programming
Christoph Scherber | Statistics
Brandon Foltz | Statistics
statisticsfun | Statistics
Java and R Tutorials | R programming
bigdata simplified | All things big data
Derek Banas | Playlists on SQL and Python

Must MOOCs for Data Science

Advertisements