Coursera
Python for Data Science (and Version Control with GitHub)

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Coursera

Python for Data Science (and Version Control with GitHub)

本课程是多个项目的一部分。

包含在 Coursera Plus

深入了解一个主题并学习基础知识。
初级 等级
无需具备相关经验
4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
深入了解一个主题并学习基础知识。
初级 等级
无需具备相关经验
4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

了解顶级公司的员工如何掌握热门技能

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

积累特定领域的专业知识

此课程作为 的一部分提供
在注册此课程时,您还需要选择一个特定的合作项目。
  • 向行业专家学习新概念
  • 获得对主题或工具的基础理解
  • 通过实践项目培养工作相关技能
  • 获得可共享的职业证书

该课程共有6个模块

In this module, you'll set up a powerful development environment, master essential Python syntax, and learn to leverage GitHub for seamless collaboration. By the module's end, you'll be equipped with the same foundational skills used by industry pros, including cutting-edge GenAI applications. Get ready to transform from a coding novice to a confident data explorer.

涵盖的内容

3个视频10篇阅读材料2个作业2个非评分实验室2个插件

In this module, you'll develop essential skills for transforming raw data into analysis-ready formats - a critical foundation for any data science workflow. You'll master techniques for importing data from diverse sources, manipulating complex datasets, and optimizing data structures for analysis. Working with real-world datasets from our EngageMetrics and MediTrack case studies, you'll build practical experience in data preparation that directly translates to professional scenarios.

涵盖的内容

4个视频2个作业1个编程作业4个非评分实验室2个插件

In this module, you'll learn to uncover and communicate insights through powerful data visualization techniques. You'll master both static and interactive visualization tools, from Matplotlib and Seaborn to Plotly, while conducting thorough exploratory data analysis. Using the EngageMetrics and MediTrack datasets, you'll develop the skills to transform complex data into compelling visual stories that drive decision-making.

涵盖的内容

3个视频2篇阅读材料2个作业1个编程作业3个非评分实验室1个插件

In this module, you'll elevate your analytical capabilities with advanced statistical methods and testing procedures. You'll learn to conduct hypothesis tests, design and analyze A/B tests, and automate analytical workflows. Working with real employee and medical data, you'll gain hands-on experience in applying sophisticated analytical techniques to solve complex business problems.

涵盖的内容

3个视频2篇阅读材料1个作业4个非评分实验室3个插件

In this module, you'll learn to implement professional data science workflows using GitHub, AI-assisted documentation, and strategic version control. Working with the EngageMetrics employee dataset, you'll develop essential skills for collaborative data science projects. You'll learn version control best practices for Jupyter notebooks and discover how to leverage AI tools for efficient documentation. Throughout the module, you'll practice effective branching strategies that help manage complex analyses. Through hands-on labs and real-world scenarios, you'll gain practical experience that directly translates to professional data science work. By the end of this module, you'll be prepared to manage collaborative projects using industry-standard version control practices.

涵盖的内容

3个视频1篇阅读材料2个作业3个非评分实验室

This final module combines hands-on practice and focused assessment to validate your data science capabilities. You'll first work through a comprehensive TrendWave Media analysis project, then demonstrate your mastery through a targeted assessment covering key data science concepts and skills.

涵盖的内容

1个视频3篇阅读材料1个作业1个非评分实验室

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位教师

Professionals from the Industry
43 门课程14,053 名学生

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¹ 本课程的部分作业采用 AI 评分。对于这些作业,将根据 Coursera 隐私声明使用您的数据。