Coffee Break

MITx: 15.071x – The Analytics Edge on EDX

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I have FINALLY completed this course on edX. Aside from I Heart Statistics, this is by far one of the best statistics course I have ever taken in my life – and I encourage everyone who is getting into Data Science to check it out as well as the materials are still very relevant. Some of the things it went over were:

  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Random Forest 
  • Text Analytics (Bag of Words)
  • Clustering
  • Visualization
  • Linear Optimization
  • Integer Optimization
  • Kaggle
Of course, all of these were taught in R, which forced me to learn R. I don’t think it is possible to complete these homework units without R due to a command called set.seed() in R which defines the algorithmic pattern of certain random selection/generation functions used by R packages. So for those who wants to complete this course in Python, you have been warned. 

Now to the meat. I was extremely impressed on how the topics were presented in this course. The videos were on average 5 minutes long each were succinct enough to teach about individual topics with real world examples. One of the worst way of learning is learning without relevant applicability, and this course has done a great job in this realm. 

For example, I didn’t know American Airlines used Linear Optimization to change their way of selling seats. This lead to the science of revenue management of framing the way seats should be sold in airlines where regular seats are sold enough to cover operating costs and discount seats are sold in order to generate income (this is looking at 10,000 feet point of view explanation). In 1985, American Airlines launched a program called “Ultimate Super Saver”. This move competed with People Express, another major airline, and forced them into bankruptcy due to competitive pricing strategies. 

“Donald Burr, the CEO of People Express, is quoted as saying “We were a vibrant, profitable company from 1981 to 1985, and then we tipped right over into losing $50 million a month… We had been profitable from the day we started until American came at us with Ultimate Super Savers.” 

What did I gained from taking this course?
  • Understanding R vs Python 
  • Learning how to frame problems 
  • Conducting test and validating using training sets and testing sets 
  • Usage of different techniques based on use case and what are some general strengths/weaknesses of each techniques
Over the course of next few weeks, I’ll be re-using some concepts I learned from this course and going into details of building models. Stay tuned!



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