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Kursteilnehmer-Bewertung und -Feedback für Datenanalyse mit Python von IBM

4.7
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12,080 Bewertungen
1,746 Bewertungen

Über den Kurs

Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Topics covered: 1) Importing Datasets 2) Cleaning the Data 3) Data frame manipulation 4) Summarizing the Data 5) Building machine learning Regression models 6) Building data pipelines Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts: Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

Top-Bewertungen

SC

May 06, 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.

RP

Apr 20, 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.

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1551 - 1575 von 1,726 Bewertungen für Datenanalyse mit Python

von Joseph M

Feb 21, 2019

There were serious problems with this course, not in the instructional material but in the execution. There were multiple typos in the code. The especially grievous ones being in the dictionary names.

von Deren T

Jan 07, 2019

This is the 6th course of the specialization and I gave 5 stars to the previous courses. But this course have many typos in videos and codes. It makes harder to understand some points.

von Kristen P

Aug 19, 2019

The work in this course was incredibly interesting. However, there are many errors and the forums went for over a week without response to questions...It seems hastily put together.

von L V P K M

May 14, 2020

Videos are very fast and dont go into details. Assignment is very easy, it could have been more challenging which can test and make learner to think using several concepts learned.

von Ivan L

Apr 29, 2019

Typos are very unprofessional and spoil impressions of the course. Tests and labs are super-easy and do not make you think, and you only need to repeat commands from the lectures.

von Vladimir K

Feb 24, 2020

So many errors in materials. It's unacceptable for course of such level. Even though people mentioned these errors in discussion forumns noone seems to bother about correct em.

von Naveen B

Jul 13, 2019

Some of the codes shown in the videos had minor errors. Also, a bit more explanation for function (in statistics terms) would have helped in having a better understanding.

von Marta I C

Aug 23, 2020

This is a good course for beginners with Python. The content is explained in a very direct and comprehensible way, but more programming exercises and tasks are required.

von Ying W O

Sep 27, 2019

There are lots of typos in the labs and assignments, which can be frustrating. I expect better quality from IBM. Content is great and easy to understand nevertheless.

von Matteo T

Jan 01, 2020

This course is quite good. The bad thing is that the arguments of the last "lesson week" are treated very superficially, taking for granted some advanced knowledge.

von Marcel V

Jun 28, 2019

A lot (too much maybe) is covered in this coarse

It really helps a lot when you know some statistics. Like linear regression,

Why gridsearch was covered I wonder.

von Dylan H

Apr 03, 2019

While a bit fast and loose with the concepts, does contain a lot of practical code as to how exactly to bring things discussed about, which is appreciated.

von Xuecong L

Feb 16, 2019

Thanks for teaching me the systematic way to do data analysis! However, I found quite a few mistakes in the lectures in this course, hope it will improve!

von Hao Z

Aug 12, 2019

IBM Cloud is difficult to use.

The generated link of notebook will not share the latest version, if you click the share icon before editing the notebook.

von Neo B

Feb 11, 2019

Data visualization was taught in details in course 7 and regression was taught in course 8. With no backgrounds, the codes in this course are scaring pe

von Goh S T

Apr 08, 2020

The section on model development and evaluation is not so clear. It is difficult to understand if you have no prior knowledge of machine learning.

von Girgis F

Dec 31, 2018

Course was great however i felt a lot of material was covered in a short period of time, this course can be 2 or 3 courses based on the content

von Guillermo M M

Aug 20, 2018

It is missing a last project like in the two other courses... It would have been quite fun to be able to apply what we learnt in a project.

von A P

Jun 14, 2019

Lots of spelling and grammatical errors that made it difficult to understand some of the material. It is otherwise an interesting course.

von 靳文彬

Mar 11, 2020

There is no slides to download or review after class which makes it hard to go over the knowledge again without watching the video again

von Siwei L

Jan 23, 2020

The video is too short and many concepts remain unclear or poorly explained. More contents need to be added to the questions and tests.

von Carlos R

Mar 26, 2020

It's an excellent course; the best part is the labs. It's a pity that we (the students) have a lot of problems loading the labs.

von Pedro F

Aug 22, 2019

Little bit confusing, unstructured and not easy to follow. Material inside is good though, but the course needs to be improved.

von sangeet a

Apr 08, 2020

Things are too fast in this course and many things remain unexplained which makes it difficult for one to understand properly

von Dominic M L C L

Sep 16, 2019

Too many errors in the code and explanations. Makes it very difficult to understand which is the right procedure/conclusion.