Little explanation and practice for a person who is new with python

very troubling technical difficulties

Reset deadlines is not useful

Really bad.

The course "Python Project for Data Science" is truly a valuable journey for anyone looking to explore and apply Python in the field of data science. Throughout the course, I had the opportunity to experience hands-on exercises and real-world projects, which helped me solidify my Python skills, especially in practical scenarios such as web scraping, financial data analysis, and visualization. I learned how to extract data from websites using the BeautifulSoup library to explore the revenues of major companies like Tesla and GameStop. What I appreciated most about this course was its focus on ensuring learners not only learn theory but also practice immediately, with thorough guidance from using functions like `yfinance` to extract stock data to synchronizing data for creating dynamic visualizations. The most exciting part was practicing plotting stock and revenue graphs, where I personally explored and put effort into creating clear, intuitive charts that reflected the real financial situations of companies. Applying popular libraries like Plotly to create visually appealing visualizations helped me enhance my data analysis and presentation skills. This course truly made me appreciate the combination of Python and data science. It is not only suitable for beginners but also for those who want to strengthen their knowledge and practical skills in this field. The lively hands-on environment and real-world projects gave learners the opportunity to apply what they had learned immediately. In summary, "Python Project for Data Science" is an excellent course with well-prepared and practical content. I highly recommend this course to anyone who wants to step into the world of data science and improve their Python skills in real-world scenarios.

I recently enrolled in the "Python Project for Data Science" course, which is part of the IBM Data Science Professional Certificate specialization on Coursera, and I am thrilled to share my experience. This course is a fantastic journey into the world of data science, providing a perfect blend of theory and practical application. The curriculum is well-structured and engaging, offering clear explanations and hands-on projects that solidify the concepts. The instructors are knowledgeable and supportive, making complex topics accessible and enjoyable to learn. The real-world datasets and projects helping me to apply what I learned in a practical context, which significantly enhancing my understanding and skills. I appreciate the emphasis on Python, a versatile and powerful programming language for data science. The course materials are top-notch, and the platform is user-friendly, making the entire learning experience seamless and efficient. Overall, this course is an excellent investment for anyone looking to dive into data science with Python. Whether you are a beginner or looking to refine your skills, the "Python Project for Data Science" course will equip you with the knowledge and confidence to excel in the field. I highly recommend it!

Course was impactful, and compact. Was able to recall just one previous introduction to stocks. Challenge was the use of indexing and dataframe slicing to some extent. Appreciated the project in dealing with multiple figures oin the same g0raph. Had originally mis-read the question and interpreted it as plotting single graphs, In process, had opportunity to read on different graphing methods to perform multiple graphing. Looking for a real world opportunity to demonstrate learnt concepts.

Against my better judgment, I'll give this course a 5-star review instead of 4. I was thinking 4 because there are some issues with the codes and tools provided to make this course fully understandable. Luckily, people can be resourceful and the support staff was pretty supportive and knowledgeable as well. I enjoyed the practice this course gives you on this material, one that I really didn't understand before, but I'm glad I took this course; it made me even more confident in my coding :)

Coursera is a versatile and comprehensive online learning platform that offers courses across a wide range of subjects, from technology and business to arts and personal development. One of its standout features is the collaboration with top universities and industry leaders, ensuring high-quality content delivered by experts in the field. The platform provides a flexible learning experience with options for self-paced study or structured schedules, catering to diverse learning preferences.

I enjoyed a lot with each practice, it is a challenge, the more you advance, you have to analyze to understand the code and be able to extract the data, as you understand the code everything becomes an automatic process and easy to understand, the final activity was another level because you concentrate all the practical knowledge in several data extraction operations and discover new ways to display the data. Translated with www.DeepL.com/Translator (free version)

Usually, I don't rate courses cause I don't have this kinda ability to reflex, but this course is different. It got a lot of negative rates and opinions that it's kinda too difficult. But I completed this course within one day and all the previous courses in specialization and even the latest one are enough. And course project is very interesting, giving real world scenario. Thanks for the course team!

It's an excellent course which establish well by guiding learner step by step and provide me a chance to do python project. Difficulty of the course is suit for Beginner, like me, without any python background. Details are explain in details, I have an opportunity to express in my own words in python and design what statement to use. It's a great improvement to do a project. Appreciate for the course!

This Python Project for Data Science course helped me in understanding BeautifulSoup library and its real life used cases. Web Scrapping is also very well explained. The use of Plotly library also gave great insights in the form of charts and graph. Looking forward to explore more into this newly acquired skill set. Thank you IBM and Coursera for this great course and access to IBM Watson Studio.

I've enjoyed this experience and learned other things about Data Science world, like Python libraries, Python fuction, etc. Furthermore, I've played the role of a Data Scientist / Data Analyst working on a real project, demonstrate my skills in Python, built a dashboard using libraries like Pandas, Beautiful Soup and Plotly thanks to the Jupyter notebook.

Thanks to all !

Enrico

This course was pretty challenging, but also very fulfilling once completed. Taking it has definitely boosted my confidence in tackling the rest of this course. Since this is relatively new, the initial reviews that I read had me skeptical about the content, but it looks like whatever problems there may have been have now been ironed out - and I'm thankful for it!

I found this assignment worthwhile and was a good recap of the skills taught so far in the course. I'm actually quite suprised at a bunch of the low reviews that say the material didn't prepare them. If you take notes, work in your own Jupyter Notebooks, google a bit, and read a bit of material outside of the course, this project will be a breeze!

Nice course, don't know why there are a lot of negative reviews, if you doing everything step by step, this course is smooth and easy, of course this course doesn't tell everything about Python, but for completing Project (which is the main purpose) given information is enough, so totally recommend, course is really interesting!

I enjoyed a lot having this project to apply all what was learnt in the previous course. One thing though you could explain a little more in detail the code, like the make_graph function in one of the labs, I know were not supposed to program all that, but it'd be quite interesting to get to know how to code to that level.

I enjoyed all the labs in this course, they helped to cement the knowledge learned in the prior basic Python course. The estimation for time to complete the labs is extremely low though. Please consider amending the estimated completion times to reflect the fact that novice Python programmers are taking this course.

Hi! This is a great course! It is desirable to have at least a basic knowledge of python. Even without any skills, I recommend this course, it takes you from the basics of the language to the very essence of its use. I happily remembered what I knew, repeated it, and gained new knowledge. Thank you for this course!

I wish all the courses in this IBM certificate had this sort of assignment instead of quizzes. It would be great to make a better platform for screenshots - it is not visible, and hence peers provide wrong answers to the submission.

But overall, this was the most useful course in the certificate series.

The practical work presented in this project is truly commendable. The author demonstrates a strong understanding of the subject matter and skillfully navigates through various challenges.

One of the standout aspects of this work is the incremental approach taken towards increasing hardness.

In comparison with other IBM courses, this one is objectively weaker, due to the small amount of information provided. At the same time, it is always useful to repeat parsing materials, and laboratory materials are beyond praise. Upfront 5 stars, but recommend deepening the course.

I've enjoyed the course more than I was expecting. I believe they have upgraded it, looking at previous reviews.

I liked that we had to look at libraries to get the slight changes to the code taught in previous courses.

I also think the time pressure is a good gauge to get it done.

This mini project guided course is really good to kick start your Data Science Project. However, If you do not have any prior experience in Python Programming, I would suggest you to take "Python for Data Science, AI & Development" before you take this course.