Good course to give a basic understanding of predictive modelling and analytics. Good assignments and opportunity to review peer submissions help reinforce the learnings.
Excelent! Even for someone that doesnt work usually with statistic models, this course give the fundamentals insights so that we can go deeper by ourself.
By Germán A R R•
Overall is a practical and interesting course. Sometimes the quizes or assignments are not direct related to the lecture, however you can get to the point thinking a little. Will be important to update the XL Miner explanations because the software is currently more up to date than was shown. Additionally, even we get lot of practical exercises where you can identify robustness and types of models, for me is not still clear how to get a predictive model for my daily use. Expect to cover that on further lectures.
By Eric Z•
I really enjoyed this course, but I did struggle more than I should have with the software tools. In many cases, my version of the tool (the latest) did not match the instructor's version, and I worked to translate my version to his, and that's not a good use of my time. That said, the material was interesting, and the professor did a great job presenting it. I would recommend the course, but I would recommend that you learn to get the results not just in XL Miner, but in R or some other software, as well
By Mohana P L•
This course mainly aims at someone who knows about econometric regression and basics of ML algorithms. To me, I had little problem in understanding some concepts in ML as I didn't know all algorithms in detail. However, I put effort to read the basics of each algorithm and then watched the lectures. Thank you Professor Dan Zhang
By Colin P•
Very interesting course that covers a lot, which is good in that it gives exposure to different mining techniques, but bad in that I feel very far from mastering the techniques. Each mining technique could be its own course. Course could do a better job of explaining how to interpret the model outputs.
By Haiying Z•
The knowledge and information are very useful. However, the choice of software is poor. It took a few times (days) to install/uninstall to make it finally worked. Once it was running, it was unstable, malfunctioning unpredictably. A better software should be use for this class in future.
Don't mind the negative reviews. Most issues are years old and have been fixed. Didn't face a single issue. The course Does require an additional tool to complete assignment which is only free for 15 days. Also the accent of the professor is hard to understand.
By Shafeeq S•
Very good course for understanding Regression, classification. Other advance predictive models like trees, random forest, neural networks are covered fast. Could have been little more lengthy sessions.
instructor is very fast in explaining concepts.
By PRATIK J P•
The instructor's tone was difficult to Interpret. It was not fluent and pronunciations were uneasy. Overall content was excellent, though there must have been examples after terms explanation rather than one complete video at end
By La V M•
The course is a great course.
The only difficulity I had was in the last assessment where we had to use XLMiner. I was not able to use it properly as I had difficulity loading it on my computer because of the Windows version.
it is really a good course which helps me to understand the basic knowledge of data mining in which I learned about logistic and linear regression and also about boosting, bagging, and random forest.
By Rhonda M•
Professor is a little tough to understand, so I had to read the transcript during some of the videos. However, once I got the XLMiner issues resolved, it continued to be a great class and experience.
By Cayla C•
Really like the course and learned a lot. Wish that the quizzes didn't offer as much guidance on the steps to use XL Miner. Because this is given, it's not fully testing students on the material
By Miah M Z•
A good introduction to various techniques of predictive modeling. To better understand, further study on the topics is necessary.
By Patrick C•
some items were unclear, the definitions, the explanation, the examples were necessary. however, I could google to get those.
By Pelin T•
Although the material presented in the course was very useful, it was hard to keep up with the instructer.
By Thejes S V•
The Case Assignments are pretty useful
By SOUMYA B•
very well explained
By Akintan O•
Tricky to Pass
By Santiago F•
The course although presents great topics, it needs improvement to support students with questions about exams and assignments. I'm not gonna sugar code this review, it took me hours and hours of dedication to pass the quizzes and assignments, and did not get much help from the professors, one of the instructors has poor English skills and is very hard to understand his lectures. However, this course presents you a challenge to better yourself, believe me, if you spend the time, read the questions that other students post in the discussion forum, and follow the guidelines from the videos, you'll pass. I struggled at the end but ended up getting 97% in my final grade. One advice, keep track of the correct and wrong answers you get from the quizzes, many questions repeat themselves, take notes from the videos or ppt, is not enough just watch, be an active learner and you'll be fine.
By Chris m•
Instructor wants the students to learn but the method of presentation and practice doesn't align. The software required uses an outdated software that many users struggle to obtain and install. The lectures do provide some visuals but the amount of information flooded to the student is overwhelming. The quizzes need a improvement, almost all require the use of XLMiner which is complete rubbish. I suggest requiring the students to get familiar with the formulas rather than use a tool which results in a black box scenario for the learners. I do appreciate the time and effort put forth but providing the most current and up to date method of learning is the better option.
By Otto C•
I think it would be more helpful to fully explain an example of how the techniques you learn help you to solve problems. I think that I learned the basics of the regressions and trees but I wouldn't know what to do after you get the results, maybe the example could include what you do next after you get the results from XL Miner. Professor Dan is a really smart person and you can definitely tell he know what he's teaching, however I think he could be more friendly to the camera and maybe smile more :)
By NAGABHAIRU V K•
I really want to mention two thing about this course. The first thing is the content (Algorithms) which are talked in this course are Really usefull and important mostly used algorithms to learn clearly.and another thing is the instruction was so bad in explaining the subject .He is so fast in explaing concepts and math beahind it .Even not only he is fast his native english pronosation is so bad and its really tough to understand.
By Emiljo J•
I found the course content to be good and explanations to be concise but sometimes rushed through. The choice of software to use, however well aimed as it did not require manual programming, it proved a more frustrating experience than actually writing it in Python. I also hardly believe that I would be using Analytic Solver in the future.
A good course overall; however, I expected some further reading recommendations by the lecturer to help develop a deeper understanding of predictive models.
The last peer assignment was boring and too simple relative to the course knowledge level. Plus, one of the tasks was replicated from another one that I previously did.
By Matthew G•
Covers a lot of essential topics around analytics and predictive modeling. However, the delivery in the lectures lacks enthusiasm and seems very scripted. Also, the final project, despite being primarily a predictive analytics courses is simple a re-hash of the Week 1 project, and is not cumulative of all topics covered.