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Data Science Fundamentals Part 2: Unit 1

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Data Science Fundamentals Part 2: Unit 1

本课程是 Data Science Fundamentals, Part 2 专项课程的一部分

位教师：Pearson

包含在中

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1个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

8 小时完成

灵活的计划

自行安排学习进度

1个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

8 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Gain a foundational understanding of Exploratory Data Analysis (EDA) and its historical context.
Develop practical skills in Python data visualization using matplotlib and seaborn.
Learn to identify and interpret relationships and correlations within datasets using advanced charting techniques.
Recognize and avoid common pitfalls in data analysis, including mixed effects and Simpson’s Paradox.

您将获得的技能

您将学习的工具

Seaborn

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

1 项作业

授课语言：英语（English）

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Data Science Fundamentals, Part 2 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

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获得对主题或工具的基础理解
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该课程共有1个模块

This course teaches how to ask the right questions and extract meaningful insights from complex datasets. Through hands-on lessons, you’ll master industry-standard Python libraries such as matplotlib and seaborn, enabling you to create compelling visualizations like histograms, boxplots, and scatter plots. You'll learn to uncover patterns, relationships, and correlations within your data, and develop a critical eye for interpreting results. You'll also learn about the pitfalls of data interpretation, including the impact of mixed effects and the nuances of Simpson’s Paradox, ensuring you can navigate and communicate findings with confidence. Whether you’re a beginner or looking to deepen your analytical toolkit, this course will empower you to transform raw data into actionable knowledge.

This module introduces Exploratory Data Analysis (EDA), emphasizing its historical context and importance in asking the right questions of data. Learners will use Python’s matplotlib and seaborn libraries to visualize and analyze data, starting with single-variable plots like histograms and boxplots, then advancing to multi-dimensional visualizations such as scatter plots. The module also covers identifying relationships and correlations between variables, and concludes with a discussion of statistical pitfalls like Simpson’s Paradox, highlighting the need for careful interpretation of data.

涵盖的内容

20个视频1个作业

20个视频总计423分钟

Specialization Introduction 7分钟
Topics 1分钟
Introduction to the pandas Library, Part 1 50分钟
Introduction to the pandas Library, Part 2 23分钟
Introduction to the pandas Library, Part 3 23分钟
Data Manipulation with Pandas 32分钟
Grouping and Summarizing Data with Pandas 16分钟
Exploratory versus Explanatory Visualization, Part 1 8分钟
Exploratory versus Explanatory Visualization, Part 2 21分钟
Visualizing One Dimension: Histograms and Boxplots 30分钟
Visualizing Two Dimensions: Bars, Lines, and Scatterplots 9分钟
Multivariate Visualization: Facets, Small Multiples, and Dashboards, Part 1 14分钟
Multivariate Visualization: Facets, Small Multiples, and Dashboards, Part 2 11分钟
Visualizing One Dimension: Histogram and KDE, Part 1 30分钟
Visualizing One Dimension: Histogram and KDE, Part 2 27分钟
Visualizing One Dimension: Comparing Distributions, Part 1 29分钟
Visualizing One Dimension: Comparing Distributions, Part 2 28分钟
Visualizing One Dimension: Comparing Distributions, Part 3 7分钟
Visualizing Two Dimensions: Line Charts and Scatter Plots 41分钟
Mixed Effects and Simpson's Paradox 16分钟

1个作业总计30分钟

Exploring Data--Analysis and Visualization Quiz 30分钟

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位教师

Pearson

268 门课程 48,070 名学生

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常见问题

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

Data Science Fundamentals Part 2: Unit 1

Data Science Fundamentals Part 2: Unit 1

您将学到什么

您将获得的技能

您将学习的工具

要了解的详细信息

了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识

该课程共有1个模块