This is my final review of The Analytics Edge, an MIT course supplied online by edX. The course officially ended on July 5th with the final exam. Personally I have enjoyed this course; at least the parts I participated in.
Previously I reviewed the following parts of the course:
- Weeks 1 and 2, which gave an introduction to analytics and the statistical programming language R, followed by a real-life case study on the use of linear regression.
- Week 3, which focused on logistic regression and a famous study of heart disease.
- Weeks 4 and 5, which took us on to classification and regression trees, then natural language processing.
- Week 6, which concentrated on clustering methodologies.
Now let me complete the review, beginning with a complete rundown of topics covered during the course:
- Unit 1: An Introduction to Analytics
- Unit 2: Linear Regression
- Unit 3: Logistic Regression
- Unit 4: Trees
- Unit 5: Text Analytics
- Unit 6: Clustering
- Kaggle Competition
- Unit 7: Visualization
- Unit 8: Linear Optimization
- Unit 9: Integer Optimization
I completed most of the material to begin with and then slowly lost pace. This was due to a busy week which meant I did not complete the work and homework for that specific module. Deadlines are two weeks after material is released with new material, however, coming out every week. What I enjoyed most was the lectures and recitations. Especially the recitations worked you through real data and used a case study which made the material interesting.
The biggest drawback of the course, in my opinion, is the length of the homework. The work was not especially difficult but it was time-consuming. For people that are “busier” than a normal academic environment (i.e. full time work and family) more flexibility in the deadlines is required. If they had allowed all homework to be completed by the end of the course it would have permitted everyone greater flexibility and the opportunity to work at their own pace.
Overall, this is really an excellent course and I recommend it to anyone interested. Although my target was to get a certificate for this course I did not manage to get the required score. However, it will serve as a very solid foundation for future courses related to data science and provided an excellent primer on the R statistical programming language.