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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: 24,558
Рецензии: 5,516

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

SI
15 мар. 2018 г.

overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .

Фильтр по:

4001–4025 из 5,464 отзывов о курсе Introduction to Data Science in Python

автор: Aditya M

25 июля 2019 г.

Overall you get to learn new and good ways of doing pands and matplotlib but its way too fast for anyone with basic knowledge

автор: SHUBHAM S P

9 февр. 2019 г.

Really good course for beginners in Data Science . The Faculty is very nice and explains each and every concept very clearly.

автор: EMRE D

2 авг. 2018 г.

Submissions were generally hard, if you want to take this course you should learn most of the programming things by yourself.

автор: Sang L

16 апр. 2018 г.

Good Intro part for pandas. The homework part is more difficult than the materials. Materials could have been more organized.

автор: Duvert P

7 сент. 2021 г.

You need kind of basics about programming, Further, the activities you need a lot of self research to clarify the statements

автор: jordanno p

27 июня 2021 г.

Course itself really good, assignments rather boring, specially the repetition and the manual cleaning/checking of the data.

автор: Matthew H

27 апр. 2021 г.

This is an intro class but it feels like Data Science 5000. Be prepared for long nights, but I feel there will be a payoff.

автор: Guido L

19 янв. 2018 г.

Takes some more time than it is said in the course. I didn't have any experience in Python so that is probably the reason.

автор: Moustafa S

15 июля 2020 г.

it was really good and challenging and of course it made me feel like i'm solving a problem for a job or a life experience

автор: sunit j

25 апр. 2020 г.

A very good course for any aspiring data scientist to improve their data wrangling and pre-processing skills using Python.

автор: Saurav K

3 сент. 2019 г.

The Video content is not satisfactory. The content must be improved. It does cover only the edge. This should be enriched.

автор: Tiago F M

17 июня 2018 г.

Curso muito bom e esclarecedor, apenas as atividades a serem desenvolvidas que são um pouco mal apresentadas ao estudante.

автор: Zaks L

8 апр. 2018 г.

Good course - requires a lot of self-learning, but that's not a huge problem. I think we could use a little more support.

автор: Vaishnavi C

30 июня 2017 г.

The course assignments were very helpful in understanding the concepts better while encouraging the students to self-learn

автор: Marcus

10 июня 2017 г.

The assignment is useful, however, the grading does not give much information on the submission except the points awarded.

автор: Nico A

3 февр. 2017 г.

This course will be a great start for people to know about data science with python and get familiar with few simple data.

автор: Rahul S

28 янв. 2017 г.

The material seemed a bit hurried at times..but overall a great learning experience and the assignments were truly helpful

автор: Ozgun S

29 июля 2020 г.

First, classes give you knowledge about topics. Then,

challenging

assignments come which encourages you to learn more.

автор: Rômulo M R

10 апр. 2017 г.

In my opinion, the assignments problems could be more clearily explained, I think it could be improved for next sessions.

автор: JAI K

16 июня 2020 г.

The videos could have been more Assignment friendly, as the assignments were tough to crack after seeing just the basics

автор: Akshay S

10 сент. 2019 г.

The assignments and the projects touched upon not just the basics. The video lectures could've been a bit more detailed.

автор: DK

3 июля 2018 г.

The pace of the course is fast, need quite a bit of python experience and a lot of study outside of the course material.

автор: Youdinghuan C

22 янв. 2017 г.

First two weeks are great. The third week becomes a bit disporportionately difficult. The autograder is very inflexible.

автор: Geoffroy D

3 дек. 2016 г.

Good course, going a bit fast on certain aspects but good use of Jupyter and interesting coursework, challenging enough.

автор: Charles K

16 июля 2020 г.

Difficult, but do-able. Recommend having a strong baseline understanding of Python + Jupyter Notebooks before starting.