Free Online Big Data Analytics Courses from around the World

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There is now no doubt that big data is the hottest IT topic today with an increasingly growing demand for qualified data analytics professionals who are being offered attractive salaries. Fortunately, there are now plenty of free online big data analytics courses provided by various institutes and colleges.

Following are some of the poplar free online data analytics courses from beginner courses in statistics to advanced courses in machine learning.

 1. Learning from Data

Offered by: California Institute of Technology

About the Course: This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to automatically learn how to perform a desired task based on information extracted from the data. This is a real California Institute of Technology course and has been the live classroom recording.

Prerequisites for the course: Basic probability, matrices, and calculus. Familiarity with some programming language or platform will help with the homework.

Course length: 10 weeks

Estimated Effort: 10 hours/week

Introductory Video:

Course Page:  You can access the Learning from Data course at:

2. Big Data For Better Performance

Offered by: Open2Study

Course Introduction: This course shows you how big data equals business opportunity. Find out what ‘big data’ means and where it comes from – including ordinary transactions and social interactions. See how smart businesses use data to target their offerings and get ahead of market trends. Consider how marketing data can be based on false assumptions such as the ‘last click myth’.

Course Length: 4 weeks

Estimated Effort: 3 hours/week

Prerequisites for the course: None

Introduction Video: 

Course Page:  You can access the Big Data for Better Performance course at:

3. Introduction Data Science

Offered by: University of Washington

Course Introduction: This course is about the basic techniques of data science, including both SQL and NoSQL solutions for massive data management (e.g., MapReduce and contemporaries), algorithms for data mining (e.g., clustering and association rule mining), and basic statistical modeling (e.g., linear and non-linear regression).

Course Length: 8 weeks

Estimated Effort: 10 hours/week

Prerequisites for the course: Intermediate programming experience and familiarity with databases, roughly equivalent to two college courses.  We will have four programming assignments: two in Python, one in SQL, and one in R.

Introduction Video: You can check the course videos here ->

Course Page: You can access the Introduction to Data Science course at:

4. Web Intelligence and Big Data

Offered by: Indian Institute of Technology Delhi

Course Introduction: This course is about building `web-intelligence’ applications exploiting big data sources arising social media, mobile devices and sensors, using new big-data platforms based on the ‘map-reduce’ parallel programming paradigm.

Course Length: 10 weeks

Estimated Effort: 3 hours/week

Prerequisites for the course: Basic programming, SQL and data structures,Exposure to probability, statistics and matrices.

Introduction Video: 

Course Page: You can access the Introduction to Data Science course at:

5. Making Sense of Data

Offered by: Google

Course Introduction: Do you work with surveys, demographic information, evaluation data, test scores or observation data? What questions are you looking to answer, and what story are you trying to tell with your data?
This self-paced, online course is intended for anyone who wants to learn more about how to structure, visualize, and manipulate data. This includes students, educators, researchers, journalists, and small business owners.

Course Length: self paced

Estimated Effort: self paced

Prerequisites for the course: None

Introduction Video: 

Course Page: You can access the Making Sense of Data course at:

6. Statistics- The Science of Decisions

Offered by: San Jose State University

Course Introduction: A great beginners course into statistics. We live in a time of unprecedented access to information…data. Whether researching the best school, job, or relationship, the Internet has thrown open the doors to vast pools of data. Statistics are simply objective and systematic methods for describing and interpreting information so that you may make the most informed decisions about life.

Course Length: 16 weeks

Estimated Effort: 6 Hours/Week

Prerequisites for the course: It sounds strange to say, but math is not the focus of this class. To do well, however, it is necessary to have a basic understanding of proportions (fractions, decimals, and percentages), negative numbers, basic algebra (solving equations), and exponents and square roots.

Introduction Video: 

Course Page: You can access Statistics- The Science of Decision course at:

7. Data Analysis with R

Offered by: Facebook

Course Introduction: Exploratory Data Analysis (EDA) is an approach to data analysis for summarizing and visualizing the important characteristics of a data set. Promoted by John Tukey, exploratory data analysis focuses on exploring data to understand the data’s underlying structure and variables, to develop intuition about the data set, consider how that data set came into existence, and decide how it can be investigated with more formal statistical methods.

Course Length: 8 weeks

Estimated Effort: 6 Hours/Week

Prerequisites for the course: A background in statistics is helpful but not required& Familiarity with the following CS and Math topics will help students.

Introduction Video: 

Course Page: You can access Data Analytics with R at:!/c-ud651/l-685569241/e-824578546/m-824578547

8. The Analytics Edge

Offered by: Massachusetts Institute of Technology

Course Introduction: Through inspiring examples and stories, discover the power of data and use analytics to provide an edge to your career and your life. We will be using the statistical software R to build models and work with data. The contents of this course are essentially the same as those of the corresponding MIT class (The Analytics Edge). It is a challenging class, but it will enable you to apply analytics to real-world applications. 

Course Length: 11 weeks

Estimated Effort:  8 Hours/Week

Prerequisites for the course: Basic mathematical knowledge (at a high school level). You should be familiar with concepts like mean, standard deviation, and scatterplots.

Introduction Video: 

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