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

4.7
Sterne
12,263 Bewertungen
1,773 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

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.

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.

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1651 - 1675 von 1,756 Bewertungen für Datenanalyse mit Python

von Mia W

Dec 27, 2019

the lab is extremely useful, however, videos are too short

von Michael A D R

Nov 01, 2019

Extremely interesting BUT it gets long and hard to follow.

von Nihal N

Apr 18, 2019

not in depth.... needs more clarity on a variety of topics

von Alejandro A S

Jul 25, 2019

Experimented a lot of problems to complete the assignment

von Troy S

Mar 14, 2019

Quizzes are too easy. Don't even need to watch the videos

von Anurag P

Jan 18, 2020

Mostly theoretical; very little to implement on our own.

von Pulkit D

Jun 29, 2019

Please update and explain Rigid Regression a little more

von Appa R M

Oct 24, 2019

The kernal is stuck for some questions and its annoying

von Qing L

Jan 26, 2020

Kurs gut organisiert aber

die Fragen sehr oberflächlich

von Jakubina K

Dec 19, 2018

It would be more useful if labs were be rated as well.

von Ankit S

Jan 29, 2020

It would be nice if the course had more assignments.

von Bhanu S

Apr 28, 2019

It was difficult to retain the knowledge imparted.

von Alton M

Jun 08, 2019

The course requires more interactive programming.

von XIANGYU L

Jan 19, 2019

There are lots of mistakes throughout the courses

von Abdul M A

Apr 17, 2019

Not very interactive with fewer help to learners

von Ashwin G

Apr 26, 2019

Too fast and could have included more examples.

von Gerhard E

Feb 12, 2019

Copy of videos, not a fan of tools used in labs

von ABOUDA Y

Feb 03, 2020

Un cours riche et adéquat pour les débutants

von Hiro H

Nov 27, 2019

Very nice course. It gives you what you need

von Brian S

Mar 29, 2020

Notebooks are sloppy, with typos and errors

von Fariha M

Sep 29, 2020

The course didn't seem challenging to me.

von Sachin L

Sep 26, 2019

More examples and detailed explanation

von Nilanjana

Jul 12, 2019

More examples and code examples needed

von Hamed A

Apr 09, 2019

The course needs a final assignment!

von piyush d

Dec 06, 2019

exercises could have been better.