Introduction to Data Science Coursera Course Review

Introduction to Data Science is a MOOC offered by the University of Washington on the Coursera platform. Introduction to data science is a misleading title for this course because it is not introductory level and it does not have a sensible flow that builds from one week to the next as you would expect from an intro course. Instead, the course acts as more of a data science sampler that introduces new topics each week that often have little to do with material covered in previous weeks. Lecture topics include relational databases, relational algebra, SQL, MapReduce, No SQL, miscellaneous topics in statistics, machine learning, visualization and graph analytics. If that sounds like a disjointed smorgasbord of topics, it is. To make matters even more complicated, the programming assignments use three different languages: Python, R and SQL. This course is best suited for those who have some exposure to Python, R, SQL and statistics.


If you have the appropriate background knowledge, this course touches on many interesting topics and while the lecturer's delivery is not great, he is quite knowledgeable and the material usually isn't too hard to grasp. Although the homework assignments require different languages and may take you a while to complete, they are rewarding. For instance, you'll work with real Twitter data you capture from the net, implement MapReduce operations in Python and participate in a machine learning competition on Kaggle.com.


Introduction to data science is likely to be frustrating to those expecting a general intro to data science. The course jumps around too much and uses too many different tools to be a good first course in data science, but the breadth of topics covered and programming assignments make this course worth a look if you already have some exposure to data science or the tools the course uses. If nothing else, you can skip through the lectures and watch sections that are of particular interest to you.

I give this course 3 out of 5 stars: Satisfactory.