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4.6

4,730 Bewertungen

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589 Bewertungen

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....

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.

Jul 13, 2018

I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course

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von Sadanand U

•Apr 09, 2019

It would be great if we go in a little more details of when to use which metrics for evaluation. Instead of running through a bunch of concepts you could have spent a little more time in each of them.

von Chioma J E

•Apr 10, 2019

The course was not detailed enough. I think the instructor assumed that people taking the course would know a lot about Regression, Correlation and some other statistical functions, that it was hard to understand or follow at times. Maybe consider 'dumbing' down down the statistical functions so that newbies can also follow.

Overall interesting course. Thank you.

von Nadeesha J S

•Apr 11, 2019

I would like to see a final project in this course. It will encourage the learners to do more work.

von Ashwin G

•Apr 26, 2019

Too fast and could have included more examples.

von Robert P

•May 17, 2019

Some concepts were quite confusing and not that well explained.

von Maciej L

•May 16, 2019

Too many complicated things happening at once. It is hard to digest and follow.

von BT

•May 28, 2019

Lots of good concepts. However, too complicated and could have been explained a bit more.

von Jessica B

•Jun 14, 2019

Good content, but lots of typos. The outsourcing is extremely evident.

von Bjoern K

•Jun 14, 2019

Week 4 is somewhat hard to follow - Here, an overview over the different concepts would really help

von Alexander 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 Jesse Z

•Jun 05, 2019

For such a important topic, it seems like the videos sped through some essential topics.

von Jackson V

•Jun 06, 2019

Not as impressed with this course as the previous courses. My main complaints were:

-Seemed to be some gaps between the lectures and labs

-Some lectures seemed rushed through w/ simple questions, and did not prepare well for the lab

-Pre-written code in labs would produce errors

-Spelling mistakes (i.e. the week 5 "Quizz")

-No final project to conclude and summarize up our learning

von Alton M

•Jun 08, 2019

The course requires more interactive programming.

von Ahmad H

•Jun 08, 2019

This course is very tough

von Ana C

•Jun 11, 2019

To short

Goes to fast in some aspects, the theory is completely missing in this course

von David V R

•Jun 17, 2019

Exams should be harder

von Ramakrishna B

•Jun 19, 2019

More explanations would be great. Its very difficult to understand Data exploration / evaluation sections

von Nirav

•Jun 26, 2019

Lot's of errors in this course, please update and correct it.

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 Brisa A

•Jun 28, 2019

A lot of errors make the course confusing. Also, the assigments and labs are "too easy"... it is clearly shown in the videos that there is much more to be done, but the course only demands you do about 50% of what is taught. How are we supposed to really learn without practice?? Give us real and demanding projects!

von Felix S

•Jul 01, 2019

Material to learn data analysis was very good but had quite a few bugs. It was very annoying to review the assignment of a peer because it is not possible to zoom into the screenshot. Furthermore did I need to flag a person because he had copied screenshots and his notebook was empty or only with screenshots but I was still required to review a second person to complete the course.

von Pulkit D

•Jun 29, 2019

Please update and explain Rigid Regression a little more

von Riddhima S

•Jul 08, 2019

la lala la la laa aaa

von Roberto B

•Jul 10, 2019

I'm not convinced that this is a great way to learn, I just feel there needs to be a better way of learning this than the approach this course takes, I kind of learned the python commands but I'm not sure I understand how to apply them in the real world. We'll see

von Nilanjana

•Jul 12, 2019

More examples and code examples needed

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