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學生對 IBM 技能网络 提供的 使用 Python 进行数据分析 的評價和反饋

15,272 個評分


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....




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.



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.


2151 - 使用 Python 进行数据分析 的 2175 個評論(共 2,310 個)

創建者 Nadeesha J S


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

創建者 Edward S


The week 4 lab had issues with pipelines and did not function well and the final exam locked up.

創建者 Miguel V


Needs more information on statistical tests. Specifically, when to use one model over another.

創建者 Poorna M


Videos in this section could be little more descriptive. It was not in the pace of a beginner.

創建者 Nathan P


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

創建者 Varun V


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

創建者 Connor F


when it got to model development it got too complicated too fast. The first half was great.

創建者 Badri T


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

創建者 Jesse Z


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

創建者 Debra C


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

創建者 Miguel A


Exelent training to get familiar and intruducing to Python capabilities and programing

創建者 Xinyi W


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

創建者 Ana C


To short

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

創建者 Sathiya P


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

創建者 Rosana R


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

創建者 Amanda A


There were many typos in the labs which made it difficult to understand at points.

創建者 Juan S A G


very simple exercises which does not help to learn altough videos were exeptional

創建者 Mohsen R


The course does not explain the processes enough, there should be more examples.

創建者 Maciej L


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

創建者 Tomasz S


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

創建者 Craig S M


It ok. Some parts of the course were bare bone. I liked the hands on sections.

創建者 Steven B


Overall I felt it was not broken down very well and seemed confusing at time.

創建者 Pierre-Antoine M


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

創建者 Toan N


The lab is disconnected every so often that can't complete it smoothly.

創建者 Jessica B


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