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Отзывы учащихся о курсе Introduction to Data Science in Python от партнера Мичиганский университет

Оценки: 26,495

О курсе

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python....

Лучшие рецензии


28 сент. 2021 г.

This is the practical course.There is some concepts and assignments like: pandas, data-frame, merge and time. The asg 3 and asg4 are difficult but I think that it's very useful and improve my ability.


9 мая 2020 г.

The course had helped in understanding the concepts of NumPy and pandas. The assignments were so helpful to apply these concepts which provide an in-depth understanding of the Numpy as well as pandans

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3926–3950 из 5,808 отзывов о курсе Introduction to Data Science in Python

автор: Jatin S

15 мая 2020 г.

You teach well but you need to take some more classes dedicated towards solving problems.

You need to make us all solve a wide variety of problems and then give assignment. This is the only thing that was missing.

автор: Sankalp J

17 июня 2019 г.

A bit hard course to start with. If you are looking to enter in the field of data science, better don't go with this course. But if you have some basic knowledge of field then it's awesome. Thumps Up!!! Go For It.

автор: Alejandro L

18 дек. 2018 г.

Is a great course, I don't give it 5 starts not because it is pretty tough (at least for me) but because the lectures are very simple compared to the HW. If you like to be challenged, I fully recommend this course

автор: Simone B

1 мая 2022 г.

The descriptions of the tasks are awful. It's not really clear what to do. In the forum you can see, that many other people have the same problem...

The explanations are excellent, and I really enjoyed the course.

автор: Shams R R

27 авг. 2021 г.

Overall the course is pretty comprehensive and requires quite a bit of experience in coding. The lectures are precise and directed. However, some lectures should incorporate further explanation and clarification.

автор: abhishek s

7 июня 2020 г.

The lectures could have have been more detailed as learning self might be difficult foe beginners. The Assignments were very good and an active discussion forum helped in solving those.Overall I liked this course

автор: Azeem F

15 мая 2020 г.

a brief introduction to data science in python,and how to use the library 'pandas' and how it plays an important role in data cleaning is being taught,indeed a good course to kickstart for data science in python

автор: Jun K

27 окт. 2018 г.

This is good course as a whole, but lecture videos are a little short for assignments and sometimes assignment's definition is not clear. So it's hard to complete assignments without the help of discussion forum.

автор: Oleg S

7 авг. 2017 г.

Thanks God I'm just after "P4E"-specialisation, but anyway it was difficult. Additional resources was needed through all assignment. Real help was/is/will "Learning Pandas'-book!

4-grade just for difficulty reason

автор: Shashank S

17 янв. 2019 г.

The questions for the assignment could be more clear with a sample output. Also, the instructions for the assignments could be clearer. Apart from these, the course is fantastic to get started with data science.

автор: Matthew M

4 нояб. 2017 г.

Lectures are VERY dense with material. I needed to pause the video and study the learning point (using jupyter notebook and Python API) to absorb it. That said, I was new to Python, which also slowed me down.

автор: Victor E

17 июля 2017 г.

The course is fantastic. Lectures are clear and informative. Assignments are well-designed and encourage studying. Grader is not great, this adds up to frustration and reduces the overall score for the course.

автор: Lajos P

4 сент. 2020 г.

Felt like a real college course in that more learning occurred outside of the lectures.. I'm excited to see what the new course version will include, it looks promising based off what they say will be added.

автор: Tushar T

14 мая 2020 г.

The course is really good and easy to learn. Only thing is that the content is less. Maybe because it's just the introduction. But overall, course is good and one really get to learn basic about data science.

автор: Paresh B

17 дек. 2017 г.

This course is amazing. Explanation are good. Assignments really provide some exciting challenges which create curiosity to find multiple ways of achieving a result. Looking forward for same with next course.

автор: SANKET P

7 апр. 2020 г.

It's a bit fast-paced for new learners nut is a perfect way to dive into the applied world of python for intermediate learners. I would highly recommend this course(12/10).

Thanks for the AWESOME experience!

автор: Aminath K G

1 авг. 2020 г.

I thoroughly enjoyed it. The pace for week 3 and 4 were a bit fast given that it was 1 month course (at least for me, as someone with full-time job). I look forward to playing around with Pandas and Numpy.

автор: BIJOY K G

23 июня 2020 г.

It was an interesting course i came to learn a lot of new things under python like how to use the pandas, Matplot and Numpy libaries. It has taught me how the data are being process under the pandas libary.

автор: Shashwat D

9 мая 2020 г.

This course is quiet hard as compared to Python 3 specialization courses. Use of interactive textbook just like in Python 3 course would have been better along with jupyter notebook. Course content is good.

автор: Gan C W

19 мая 2019 г.

i find this to be a great follow up from the Python for Everyone course. The course introduces python functions which are commonly used in data analysis and the course assignments are practical and useful.

автор: Prathamesh P

7 февр. 2017 г.

Very well structured course. I would really appreciate if there are more video lectures. For someone like who is not from CS background, self-study topics can get really difficult.

Apart from that loved it.

автор: Ali M

2 сент. 2020 г.

This course is a great introduction for the basics of data cleaning, searching and proving hypothesis. The main con is that sometime the question in an assignment isn't that clear, but overall, thumbs up.

автор: Krishna B S

30 дек. 2018 г.

This is an excellent course for laying strong foundation for data science skill-set.

The course assignments are very thorough and reference/further reading resources are very handy.

Many thanks for this.

автор: Yi-Hsuan L

22 июня 2018 г.

The structure of the course could be more organised (the current content is more scattered). In that way, the content could be more understandable for people who are not that experienced in python coding.

автор: Sopan S

30 янв. 2017 г.

The course content is great - Prof Christopher seriously made justice to the content. He is great instructor. He has presented course in right manner, with right speed.

Looking for more courses from Him.