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学生对 IBM 提供的 Data Analysis with Python 的评价和反馈

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19,533 个评分

课程概述

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement....

热门审阅

BM

Jul 16, 2020

Although good to learn the know-how of basic data analysis techniques, the quizzes are predictable and you don't end up coding as much as you should. A good starter course to wet your feet in DA!

UA

Jul 28, 2020

AN excellent course. Hands-on training on the cloud makes an individual really involved. So far the best online course I have ever taken, and I have learned Python programming a lot from this course.

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2151 - Data Analysis with Python 的 2175 个评论（共 3,098 个）

创建者 Достон М

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Nov 17, 2024

Good

创建者 Alejandra S M

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Oct 9, 2024

good

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Oct 6, 2024

Good

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Sep 11, 2024

good

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Sep 10, 2024

GOOD

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Sep 9, 2024

GOOD

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Aug 30, 2024

good

创建者 Narayan B

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Aug 21, 2024

nice

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Aug 20, 2024

good

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Aug 6, 2024

good

创建者 Suggar A S N

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Aug 5, 2024

NICE

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Jul 4, 2024

Nice

创建者 Dilfuza T

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Jun 14, 2024

GOOD

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Jun 7, 2024

good

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Jun 6, 2024

good

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Jun 1, 2024

GOOD

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May 30, 2024

Nice

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May 30, 2024

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May 28, 2024

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May 28, 2024

good

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May 26, 2024

GOOD

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May 26, 2024

GOOD

创建者 MOHAMMED N

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Feb 24, 2024

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创建者 Jomya M G

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Oct 12, 2023

good