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

4.5
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Оценки: 26,484

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

PK

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

YY

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.

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3701–3725 из 5,805 отзывов о курсе Introduction to Data Science in Python

автор: Ahmad M

21 февр. 2021 г.

Great professor to listen to and pretty good videos but some assignment questions super challenging and very different from the examples. First three quizzes were weird as they were mostly simple but took 24 hours to output grade. Other than these two complaints, good course to understand how data manipulation works and to learn more about Python's data specific libraries.

автор: Andrew K

18 февр. 2017 г.

This course has greatly helped my understanding of not only some python, but pandas as well. My only suggestion to anyone that wants to take this course is to make sure to allocate as much time as possible to it. They give estimates as to how long it should take you to complete a week's worth of material, but this can vary highly from person to person. Overall, I enjoyed!

автор: Janina d W

28 мая 2018 г.

Despite having some basic python and pandas skills, I have learned a lot with course. The assignments are challenging and you need to do a lot of self-study, but I find that it is a good way to learn. The only reasons I am not giving a five-star rating is that some of the questions in the assignments (especially week 4) are very unclear, and can definitely be improved.

автор: Swati s

9 авг. 2020 г.

The knowledge offered in this course is very useful and to the point. However, I found it quite fast , as the students enrolled in this course has no idea of data science so it is quite difficult for us to understand the material at such a pace. Apart from this , the quality of the material was excellent and helpful.

Looking forward to enroll myself in other courses too.

автор: Raunak T

2 мая 2020 г.

I think Hypothesis testing was not given a lot of time and was barely skimmed through. Another problem was the auto grader itself which was quite painful to work with. I think Coursera should have the latest version of packages on their server as without that there were always inconsistencies with the way my offline python responded vs how the online server responded.

автор: James T

29 нояб. 2018 г.

Excellent Intro course. Videos are short and to the point. Does require you to have familiarity with Python and to research on your own to complete the assignments. In that regard, it may be different from other online courses, but I did find the process helpful in gaining a better handle on Pandas data handling. Additional readings are also relevant and helpful.

автор: Nav K

12 июня 2020 г.

For a beginner I found this course quite fast paced. One must have a good understanding of pandas and numpy functionality for doing the assignments. The difficulty level of assignments is relatively high to the amount of content being covered in the course itself. I feel more videos should be added to understand the concepts upto the depth of questions being asked.

автор: José F Q

7 окт. 2020 г.

Very nice introductory course, I think it would have been good to include a brief introduction to visualization. But the statistics concepts and theory were very well explained plus the assignments were designed to apply all of the learned concepts, I would have liked to see more practical exercises done by the instructor as I didn't have a programming background.

автор: Jean K J

13 мар. 2018 г.

Assignments are really tough which will make you do a lot of research and self learning to come up with the desired answers. The pace of the lectures is too quick and hence the depth is lost at times. Will have to do additional research to understand the concepts clearly . Overall, a good course to understand the introductory concepts to the world of Data Science

автор: Christian L

25 окт. 2018 г.

Value of the course is mostly about personal research and work to complete weekly assignments (whose allocated time is vastly under-estimated). There are some useful examples in the videos but the course would benefit from developing a more explanatory teaching framework to understand and navigate Python. TAs were awesome to support and coach during assignments.

автор: Hugo S

26 мая 2018 г.

The class material was very good and the assignment improved the understanding.

The only negative is the graders for some of the assignment do not always provide useful feedback. Thankfully posts from Stephanie Greene (a TA) in the discussion Forum provided helpful automated testers that often provided useful clues on the specific answers the grader was expecting

автор: Shrinidhi V

1 июля 2020 г.

I found the assignments a bit challenging since I was a newcomer to the concept of exploratory data analysis. I would like the background of the lectures to be taken off and get them replaced with a white one in order to avoid any possible distractions. This was one thing I observed with my focus span after having taken multiple courses on Coursera. Thank you.

автор: Mark M

8 июня 2017 г.

I really like this approach of the specialization. Data wrangling with pandas is essential. Also referencing some controversial discussions reagarding the limits and problems we are facing as data scientists is appreciated.

However one star less as as there is no feedback on the submissions. So I really don't know what was good and how can I improve my codings.

автор: Peter S

2 янв. 2017 г.

Great course for data preparation for ML which is sometimes neglected in other courses. Great instructor. Useful assignments. Assignments require research on your own which is good. I would recommend to maybe make the course longer and cover more topics (in-depth string processing etc.), because it felt a bit short. Thanks Dr. Brooks for putting this together.

автор: Michael D

12 апр. 2020 г.

Bon cours. L'indication de difficulté "intermédiaire" correspond aux prérequis pour réussir les exercices avec Python (ne pas être un total novice). Le plus frustrant est l'auto-grader qui n'est pas assez clair quand aux parties des exercices qu'il faudrait corriger, ou bien qui n'aime pas certains codes pour ariver au même résultat. Hâte de voir la suite !

автор: Omar E R L

16 дек. 2019 г.

Fue uno de los cursos más retadores, pero más satisfactorios que he tenido la oportunidad de tomar en una plataforma en línea. Sí, requiere mucha investigación por parte del usuario y algunos de sus incisos requieren mayor dedicación que un curso introductorio, pero las recompensas se vuelven sumamente fortuitas al final. ¡Saludos y éxitos desde El Salvador!

автор: FLAVIO M R I

13 дек. 2019 г.

O curso apresenta de maneira objetiva os conceitos das estruturas de dados com Python, utilizando aulas bem estruturadas, excelentes exemplos e tarefas desafiadoras. Poderia ter um material de apoio um pouco mais elaborado, como alguns resumos dos comandos apresentados em cada aula, para facilitar a execução das tarefas e organização das ideias apresentadas.

автор: Tristan D H

1 февр. 2019 г.

Excellent introduction to the subject with comprehensive example code and solid assignments. I personally avoided most of the optional writing prompts as the anonymous feedback received from other students on the first such assignment was not constructive. I would recommend the optional readings and outside information though, it is quite thought provoking.

автор: Michael S

30 окт. 2022 г.

Learned a great deal about Python for data cleaning and data munging. The instructor, lecture modules, and reading materials were excellent. However, the assignments were frustrating due to the autograder not accepting a correct answer unless it was put in exactly as it expected. I would have given 5 stars if not for the assignment technical problems.

автор: Shourya P

6 мар. 2017 г.

Some topics are very difficult since many of the concepts are outside of what was thought in the lectures so one has to do a lot of research outside of the website. This takes up a lot of time and is way more than the estimated time for each part of the course. I did find excellent help available on the forum. Overall, a very challenging yet fun course.

автор: Fernando S

21 февр. 2020 г.

This was a good course in the sense that I learned a lot. I would have expected more detailed explanations from the teacher, because I did not know anything about Pandas. But at the same time, that forced me to research in order to be able to make the assignments. I don´t know if the fast covering of the subjects by the teacher has that in mind or not

автор: Ria S

24 февр. 2019 г.

Learnt a lot. However, I would credit the helpful answers in the discussion forums behind that. The course material was simple and basic. But not enough to support solving the assessment exercises.

For someone, who had no background to Python/Pandas I had to spend a LOT more time than what I estimated I would be spending at the beginning of the course.

автор: Jamol B

26 июля 2020 г.

Learned a lot in the course, Prof. Brooks is awesome. Last assignment was difficult due to lack of clarification. Task description was different from description of the objective of the run_ttest() function. in the former, it says quarter_before_price to recession_bottom_price, in the latter it says recession_start_price to recession_bottom_price.

автор: Omar M

3 мар. 2019 г.

Great course. Just needs a little time to get used to the pace, specially when they explain you examples and start typing the code. I had to slow down the "playback speed" and also try each step on the Notebook side by side. Not to discredit the course in any way. Just that it was my first attempt at such a course after 30 years. I am a bit rusty.

автор: McKay H

17 нояб. 2017 г.

The video instruction and content is excellent. My one complaint is that there is enough ambiguity to the assignments to where you must read the forums if you want to pass. I would like to see some refinement in the assignment descriptions. Otherwise the assignments are great for getting the experience you are looking for in a class like this.