Chevron Left
Вернуться к Анализ данных с Python

Отзывы учащихся о курсе Анализ данных с Python от партнера IBM

4.7
звезд
Оценки: 7,949
Рецензии: 1,006

О курсе

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....

Лучшие рецензии

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.

AB

Feb 13, 2020

Great introduction to data manipulation and analysis for common problems that arise in data science. Also allows you to gain a further understanding of Python syntax, specifically the pandas library.

Фильтр по:

901–925 из 997 отзывов о курсе Анализ данных с Python

автор: Bjoern K

Jun 14, 2019

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

автор: 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.

автор: Nathan P

Jan 02, 2020

It was cool to see the stuff at work but I need more hands on practice to really learn stuff.

автор: Varun V

Dec 19, 2018

This looks good for experienced but not the best of course for beginners/intermediate level.

автор: BT

May 28, 2019

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

автор: Jesse Z

Jun 05, 2019

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

автор: Debra C

Mar 24, 2019

Course was worthwhile for general understanding of what can be accomplished with Python.

автор: Chau N N H

Jan 29, 2020

The lesson need more explanations on Polynomial Regression, Pipeline, Ridge Regression.

автор: Xinyi W

Jan 26, 2020

Superfacial level of Python while being not very through on the data analysis methods.

автор: Ana C

Jun 11, 2019

To short

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

автор: Sathiya P

Aug 27, 2019

Nicely thought, but I felt concepts like Decision trees, Random forest were missing

автор: Rosana R M

Aug 13, 2019

The course is too long. The material should be divided and explained more detailed.

автор: Maciej L

May 16, 2019

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

автор: Tomasz S

Nov 19, 2018

Few small hiccups with the training videos and quite a few in the lab-excercise

автор: Pierre-Antoine M

Feb 19, 2020

Videos are nice but they are mistakes in the notebooks that disturbs learning

автор: Jessica B

Jun 14, 2019

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

автор: Arjun S C

Aug 14, 2019

Lots of bugs and errors. No instructors reply on the discussion forum.

автор: Filippo M

Sep 27, 2019

Useful course, but the IBM online platforms are not working well.

автор: Robert P

May 17, 2019

Some concepts were quite confusing and not that well explained.

автор: Atharva Y

Jan 23, 2020

As compared to other courses this course seems to be too fast

автор: Nirav

Jun 26, 2019

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

автор: Anmol K P

Oct 14, 2019

Course could have been more elaborate in depth and scenarios

автор: Mia W

Dec 27, 2019

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

автор: Michael A D R

Nov 01, 2019

Extremely interesting BUT it gets long and hard to follow.

автор: Nihal N

Apr 18, 2019

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