Good Resources for Data Science

Post date: Apr 11, 2014 5:52:12 AM

Data Science, Data Analysis and Analytics

Udacity:

• Intro to Data Science -- Learn What It Takes to Become a Data Scientist
• Data Wrangling with MongoDB -- Data Manipulation and Retrieval
• Exploratory Data Analysis -- Investigate, Visualize, and Summarize Data Using R
• Intro to Hadoop and MapReduce -- How To Process Big Data

Coursera:

• Specialization on Data Science -- This is a specialization track consist of several great courses, based on R programming.
  • The Data Scientist’s Toolbox
  • R Programming
  • Getting and Cleaning Data
  • Exploratory Data Analysis
  • Reproducible Research
  • Statistical Inference
  • Regression Models
  • Practical Machine Learning
  • Developing Data Products
• Introduction to Data Science -- The course covers so many aspects about data science, very comprehensive curriculum.

EdX:

• Introduction to Linux Develop a good working knowledge of Linux using both the graphical interface and command line, covering the major Linux distribution families.
• Explore Statistics with R Learn statistics in a practical, experimental way, through statistical programming with R, using examples from the health sciences. We will take you on a journey from basic concepts of statistics to examples from the health science research frontier.
• Big Data and Social Physics Understanding big data, how to use it to improve companies, cities, and government, and best-practice for privacy
• Introduction to Computational Thinking and Data Science An introduction to using computation to understand real-world phenomena.
• The Analytics Edge Through inspiring examples and stories, discover the power of data and use analytics to provide an edge to your career and your life.
• Sabermetrics 101: Introduction to Baseball Analytics An introduction to sabermetrics, baseball analytics, data science, the R Language, and SQL.

UC Berkeley:

• Analyzing Big Data with Twitter: The course is taught by Twitter engineers/researchers and covers many major topics of Big Data processing. For example, Pig, Trend detection, Anomaly detection, etc.

Others:

• Sliderule: This dashboard provides awesome pointers for you to self-study toward Data Analytics career.

Machine learning and Statistics

Machine learning by Andrew Ng, Coursera

Machine Learning by Andrew Ng, Stanford (more advanced than what on Coursera)

Statistical Learning by Trevor Hastie and Rob Tibshirani, the authors of the famous ESL book

Learning from data by EdX Dr. Abu-Mostafa Caltech, a more theoretical course than that in coursera

Data, analytics and learning by EdX; talking about social network analysis

Data structure and algorithm

Introduction to algorithm -- OCW MIT

Data structures and Algorithm -- Stanford

Tools for Data Science

Database and SQL

Introduction to Database, Stanford

Python

MITx: 6.00.1x Introduction to Computer Science and Programming

There are the following courses on OCW MIT:

introduction-to-computer-science-and-programming which talks in more details about Python, for instance, hash, class, OOP, inheritance, k-mean clustering, curve fitting.