19 de abr de 2019
perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.
5 de mai de 2020
I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.
por Shripathi K•
18 de ago de 2019
I audited the course. I did not complete the quizzes because my goal was to get a very quick overview of pandas and scikit and pick up on basics. This was at the right level for me and did not go haphazardly. It did not try to convince me that something was simple, hard or not important.
I recommend this as a starting point for most who have little experience with Python but are well-versed in programming otherwise and want to get a look at a little of the ecosystem for ML using Python.
por Ricardo K•
1 de dez de 2022
This course is great!!!
I just have a little suggestion/request that is on week 4, Pipeline theme, that they could detached it from polynomial regression and dedicate a couple minutes to detail it a little bit further on code, applications anda variations. (it was spent exact 1 min).
Besides it, it was a very practice course, I learnt a lot and certainly this course expanded my tool box in my portfolio and for sure I'll have to continue my practice to domain it properly!
por Elizabeth S•
3 de jul de 2020
I will say an excellent class! You will learn a lot essential data analysis methods, and the concepts.
Ok, it's never easy for someone who never learned such knowledges before, now encounters all those statistics concepts along with python code. But still, this class managed to use an easy way to explain all those abstract concepts. The forum also helps a lot to explain some difficulties. You might feel lost in the models, but once you learn it, you feel good.
por Milan D•
3 de fev de 2019
Really good stuff in terms of outlining what is necessary in order to properly analyze the data. One thing to note is the powerpoint slides are off sometimes. Some of the stuff is not spelled correctly in the code.
Another issue is that x and y axis variables will be assigned, but be on the opposite axes (I.E when x = df['price'] but in the scatterplot it's actually the target variable, and thus on the y-axis.
por Soumya G•
14 de abr de 2020
This is an excellent course to begin with analyzing data in python. However, it would have been even more useful and interesting had it contained some more discussions on the topics like logarithmic transformation of features, when to apply it, how to do bi-variate and mutivariate analysis, exercises on topics like manipulation of dataframes using pivot, melt, crosstab etc.
por Rishi S•
11 de set de 2019
Fantastic introduction to some of main python libraries and functions used in order to do anything related to data analysis, also a good entry point for machine learning, big data and other data science specialisations - highly recommended for anyone comfortable with high level scripting and basic oops concepts - if you don't then best take a basic course in python first...
por Chung M•
6 de mai de 2020
This course is useful for statistics students who are not taught any programming languages before. It gives us a quick way to organize data. It is also an excellent online course with lab assignments by the end of the modules to practice the Python. I would say it would definitely benefit my career as data is increasingly available nowadays at any corporations.
por BrajKishore P•
7 de ago de 2019
The course material was excellent , quizzes makes this course more efficient and handy, all the lectures are explained well , the most important part of this course providing notebooks of each week for self practicing and to judge our-self . Discussion forums are provided asking queries, Overall the course was excellent both for beginners and intermediate.
por Arindam G•
20 de dez de 2018
No Doubt COURSERA is always best AND MNC like IBM,Google courses associated with coursera are MIND-BLOWING.
The Instructors are so great at Explanation Part that hardly anyone won't Understand All the Topics
I would love to thank all the INSTRUCTORS who created such a Awesome Content for us.
My Personal Ratings For All the Instructors: 100 / 100
28 de mai de 2020
Excellent Course, i've learned a lot, i can analyze any data and give a conclusion from it. It's great course with a very clear explanation. If you are not understanding from the videos you can have a full understanding of the course from the Lab Notebook. The best is giving you a chance to access on IBM Cloud, creating new dynamic projects. Thank you
por Ram K•
7 de mai de 2020
Initial part of course was easy, but the labs proved more and more useful. As I learned the course, I applied the charting skills directly to work, and was able to use Pandas to combine data from 3 databases, evaluate and report on the data to my company. It is already making a difference in our ability to make better data driven decisions every day.
por Mona A•
17 de jun de 2019
Great Course! I got a great insight into multiple steps involved in data analysis using python starting from an initial data set to pre-processing it, exploratory analysis, doing multiple operations to create possible models and ways to evaluate the models. I hope to be able to use them to solve some sample data sets and come up with possible models
por Volodymyr C•
23 de jun de 2019
Did this after Andrew Ng's Machine Learning to learn to do the same things in Python. Great course for people somewhat familiar with Python basics (I used datacamp to get a feel for Python and methods etc. first). Labs were really good for reinforcing knowledge from quizzes and videos. Overall, very nice course - will recommend to others!
por Ramjan A•
19 de dez de 2018
This is my first course that i completed, and i am very glad to do this .
thanking you for giving me this opportunity to enrolled this course
i learned a lot of new things from this course this was very fruitful for me.
the slides was nicely represented and the way of teaching was so amazing
i am very very thankful to all the Coursera Team
por Penchalaiah G•
7 de ago de 2019
This course is very use for regression model end to end scratch of evaluation and easily understand the coding theory explanation but ridge regression is somewhat improvement is needed.
Finally, I suggested to this course for learning data analysis with python.
Thanks for wonder full opportunity to learn this course in course-era team...
por Muhammad Y•
7 de out de 2018
This course is probably the most concise and well explained course I have ever taken on the subject. Materials are explained very well, and in a concise manner. The only downside is that the assessment for this course is based on quizzes, which are way too easy. Nevertheless, the course contains ungraded labs which are really useful.
por Azhar S•
2 de mar de 2022
Good course for beginners, kindly remove the project at the end of the course, make two projects one after completion of 50% of the course and the remaining after 75% of the course.
increase the questions that are mostly related to project, practical work, interview with more focus on the conceptual understanding, than on the syntax.
por Mihailo P•
12 de abr de 2020
This is the most complex course in the IBM Data Specialization Curriculum until now. There is a lot to cover and I would advise the students to go through the notebooks for practice 2 times to make sure to remember everything. One thing that is a bit confusing are functions for creating plots as we did not cover them in details yet.
por Rohit B•
16 de mar de 2020
Awesome course on gaining Python skills for performing structured data analyses. If you are already attending the IBM Data Science certification, this course is a "step up" from the initial courses to bring a lot of things together. I would highly recommend doing it in the recommended order, else the learning curve may be too steep.
por D E•
2 de fev de 2020
Wow! Excellent course that provides a great skills-focused overview on how to do data analysis with Python. The videos are first-rate, high quality and summarize the essential points nicely. The data set is real and it is used throughout the course and that helps understand the different features of data analysis taught by pandas.
por Paul C•
5 de nov de 2022
The course content is pitched at the right level. I suggest that the presenters provide complete threads of code for the earlier videos since some learners may not have the background skills.
I had challenges with electricity so I had to keep restarting the labs and that aected my performance.
Overall a very empowering experience
por Helena R•
1 de mai de 2022
Not that the course was over-challenging. A few ideas were better explained (Ridge Regression, Polynomial Models & pipelines). Would have preferred to have had access to slides rathan than the textual notes. Thought that the discussion forum was extremely helpful and the staff who responded earned their rightl. Congrats.
por Stuart S•
2 de abr de 2020
Great introduction for using Python for data analysis. I found the segments on using Pandas, scikitlearn, and Matplotlib, particularly useful. Also, the labs' use of Jupyter notebooks, were excellent, because of the ability to introduce new variables or other data, and to see how it affects the outcome. Thank you very much!
por Dongre O•
2 de mai de 2020
This course gave me very good understanding on basic concepts in Data Science and how we can make use of python. I would recommend this course to people who are searching for basics of data science. If you are from programmer then you will be able to correlate software development life cycle and Data Science Development.
por Mmr R•
27 de mai de 2019
It was really helpful for me. Now i can clearly explain what is data. How we can explore data from a big data-set, How we can analyze different type of data-set. I am so much happy with this course. Now i will try to use this technique in my next steps. Special thanks Coursera community for creating this opportunity.