This is a great training course, simple and interesting. This course contains a well-balanced variety of topics, such as vim usage, pandas, dask, and git among others It is highly recommended.

Don't let the intro videos with the odd presentation format dissuade you, the rest of the course is excellent and uses normal slides to teach! Very good refresher, thank you!

3.5 rounded up

The course provides a great overview of real-world tools, and covers important concepts in Python as well as software development. The lab is a bit too simple in my view, as well, when it comes to installation of new tools and Shell commands, It makes more sense to try it on my own laptop rather than in the lab environment.

Will continue with the next course of the specialization.

The goal of the curse is to be an introduction course in Python with some Pandas and for me, as someone who has some use of Python in my job, it was a great course: the explanations were god and clear, it remembers some functions that I didn't use frequently and teach me some things about Python that I ignored before.

But I think that the course should be difficult if you are new in programming. Maybe you should prefer a slower course, where you can take your time to understand and digest better the concepts.

A good crash course through Python and Pandas. I would highly recommend that you take some other introductory Python course (there are many available online) before attempting this course to get the most value out of your time and effort. For me, this course offered a good revision of the core concepts, and a good introduction to big data analytics (Pyspark and Dask). Recommended if you are interested in data engineering.

This Duke University course was excellent in delivery and a quick game changer as I was introduced to Python and Pandas for Data Engineering. I was able to quickly use the concepts taught in this course by Kennedy Behrman, and the approach was very practical. I am excited and look forward to the next course in this specialization: Linux and Bash for Data Engineering.

#dataengineering

It is a great and professional introduction to various tools used by data engineers. You can dig deeper in the materials mentioned in this course. I think this course did a pretty good job of setting me up to further study in this field.

excellent course, in terms of course design and interactivity. labs and exercises were extensive and helped me get things easier. even I took this course to refresh my knowledge, I feel learned more in depth. thanks!

Great course! I wish they put introduction to VS code in the first week, so that all work can be done there, but othewise, a good beginner course.

### Free format review: This combination of four courses covers a wide range of perspectives, technologies such as Python, SQL, cloud platforms, and applications like data pipelines, ETL processes, and basic machine learning tasks. It is particularly suitable for those who need a solid introduction to basic Data Engineering concepts and practical skills for simple tasks. I recommend starting with these courses and then progressing to more in-depth materials to gain a more comprehensive, contextual understanding of the topics. ### Why not 5 stars? Like many others, I keep a daily study log or tracker where I set daily goals, such as "Complete 50–75% of Module 1." At the end of each day, I evaluate my progress and adjust the next day's goals accordingly. However, a significant issue with these courses is the inconsistency in workload between modules, even within the same course. This variability makes it challenging to plan studies and set realistic daily goals effectively. Additionally, some course videos appear to be taken out of context from other course series. Starting with "part 17," such as abruptly diving into a specific technical demo or project example without any prior introduction or explanation or practical replicability creates confusion. Different instructors also tend to assume prior knowledge that hasn't necessarily been covered previously. Occasionally, the paradigm shifts or evolves so quickly that it's hard to keep track of what's happening—particularly noticeable in the otherwise commendable instruction of Alfredo Deza; a former top Olympian athlete, currently one of the leading Data Engineers globally. However, I want to emphasize that all instructors, especially Mr. Deza, clearly demonstrate deep expertise, evident from their impressive careers in leading companies within their fields. A special mention to Noah Gift, whose expertise goes beyond merely teaching technical skills—he truly stands out as both an engaging instructor with exceptional breadth and depth of knowledge. Additionally, Mr. Behrman's pacing and calm, clear manner of teaching make him particularly effective in conveying foundational concepts across different topics.

Why did I give this course one star? I did because there are far too many typos. It seemed like I flagged almost every page for spelling mistakes. I spent more time flagging errors than I did actually doing the class itself. It makes me wonder if this is an English class instead of a Data Science class, in that maybe the goal is to teach us how to proofread, since whoever wrote the text in this course sure doesn't know how to.

Learned a lot from this course and I like the way how the instructor presented in the videos. However, it seems that the specialization is not focused on Python, so I may need to find other courses for more advanced Python techniques. Week 4 is a little bit isolated from the 3 weeks' content, but in Week 4 some of the tools introduced by the instructor are useful to me. Thanks Duke University for this course.

Clear explanation of concepts, helped to gradually get a high level understanding of the subject. Although some sort of model solutions for the coding part would have enhanced the learning process in my opinion. Thanks to the Duke University for a great course on Python.

Excellent course, well-organised; the Instructors give clear and exceptional explanations of the content with many examples. Even after I finished the course, I got an invitation to review an update.

Considero que el curso es muy bueno, esta muy bien extructurado y completo. Me siento muy satisfecha con mi progreso y sin dudas lo recomiendo mucho.

Easy to follow introduction to python/ libraries and doesn't fall into the "theoretical" trap, has practical application throughout the course

Very clear, well-organized course for the beginner. I am surprised at how much I learned fairly quickly and easily. Great job. Thank you.

Great flow, not a lot of extraneous learning and super relevant. Could use a practical final project to test full set of new skills

The lessons were laid out well and were easy to follow. I enjoyed how the labs reinforced the material that was covered.

Exceptional course content, would recommend to anyone who got a break from hands on data engineering core skills !