nice

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I liked the idea of doing a capstone project to bring together all of the skills of the previous courses. This course is pretty good and Dr. Chuck's teaching style is a plus as always. But there were a few reasons why I was a little less enthusiastic than the previous courses of this specialization. For this capstone, the videos aren't all that helpful when the assignments require few changes to the scripts that are readily available. The most I learned was when I was working on a project or question that I was interested in. If I got stuck, then I would then go back and watch the videos in closer detail where I got stuck and/or code in the examples. That would solidify the lessons a little bit more in my head. The quiz format in the earlier courses was great but it wasn't included here, partly because of the format. What could be done in the capstone is to have snippets of code that are missing then ask us to fill it in. Alternatively, you can have different snippets of code and ask us which is correct to properly execute a section. In addition, I thought we would get to present our coding work on the project of interest, even if it was just optional. Sharing our work would have allowed for a shared sense of accomplishment with others who finished the specialization. Group gratification can be a good motivator. In the end, though, I really enjoyed this specialization and enjoyed completing the courses.

I wanted to mention that this last course in the specialization, despite being as great as the other four, has a huge number of typos. I took screenshots of some of them which I can share at nicolas.posunko@gmail.com. I'll try to list those I noticed since I can't paste the screenshots here:

— Week 7 > Visualizing new Data Sources - Introduction: This week you will discuss the analysis of your data *to the class*.

— Final test: Which of the following lines will never print out regardless *fo* the value of "x"?

— Final test: To *insure* that all Python reserved words are properly spelled.

— Week 4 > Loading and Modeling Mail Data: *This assignment you will start* the spidering of …

— Week 4 > Mailing List Data - Part I: … and it *make* take a few days to get graded.

— Week 5 > README: Analyzing an EMAIL Archive from gmane and *vizualizing* the data …

— Week 6 > Visualizing Email Data: … we must *be* remember that not all …

— Week 6 > Visualizing Email Data: This is also a good time *to remember to remind* those with slow …

The Capstone starts with a quiz which covers the prior courses to give you both the Capstone Course and the Specialization certificate. Then it goes on with some lectures, worked examples and additional assignments, which adds Honors to your Course Certificate. Modules which contain these assignments are alternated with optional modules where you can work on a personal data analysis project ,based on a data source of your choice among those suggested (or even another one of your free choice). Overall, it is a good capstone, however I would have preferred that the assignments were more separated from the personal project, moreover the personal project could be more guided or some suggestions on the choice of the source could be provided.

I think this is a great beginners course on how to code, and the foundational concepts you will need to know to do work as a Data Aanlyst/Python user. That being said, while the lectures and sample code are great, I feel that the assignments were too easy / not challenging enough to really engrain the material.

There is lots of sample code that uses things we did not learn, and while the lectures explain this, it can be a bit dizzying at first as they rapidly move through content. I think with more fleshed out assignments requiring the student to create and build more of the code would solve some of these issues.

The capstone project should be more involving in terms of coding in python. Mostly I do is to run the same files in the same order to parse the same information which Dr. Chuck has already extracted in the videos and doing all the steps same. It is lagging the novelty from the student part. There should a section where we got to write some part of the code to perform certain steps, may be code correction, may be changing some steps to bring out a different output. Although the teaching style of Dr. Chuck is commendable and so is the course material.