Coursera
Building a Real-World Data Science Solution
Coursera

Building a Real-World Data Science Solution

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
3 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
3 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 Data Analysis 领域的专业知识

本课程是 Python, SQL, Tableau for Data Science 专业证书 专项课程的一部分
在注册此课程时,您还会同时注册此专业证书。
  • 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
  • 通过 Coursera 获得可共享的职业证书

该课程共有5个模块

Welcome to the foundation of building real-world data science solutions, where business understanding meets technical implementation. In this essential first module, you'll learn to bridge the gap between business challenges and data science solutions while mastering the fundamental AWS services needed for scalable implementations. Working with TicketWise's support ticket routing challenge, you'll learn to analyze business requirements, configure cloud environments, and establish the data management infrastructure that will support your end-to-end solution. Through hands-on experience with AWS S3 and Python integration, you'll develop the crucial skills needed to transform business problems into well-structured data science projects.

涵盖的内容

3个视频7篇阅读材料1个作业1个非评分实验室2个插件

Discover how to transform raw support ticket data into actionable insights. In this module, you'll analyze TicketWise's ticket patterns and prepare data for modeling success. Through exploratory data analysis and systematic preprocessing, you'll uncover key insights about resolution times, customer segments, and routing patterns while ensuring data quality. Using Python libraries and AWS integration, you'll create a clean, well-structured dataset that will form the foundation of your routing solution.

涵盖的内容

2个视频1篇阅读材料3个作业2个非评分实验室2个插件

Ready to turn your prepared data into predictive power? In this module, you'll build and evaluate machine learning models that automatically route TicketWise's support tickets. Through feature engineering, model development, and systematic evaluation, you'll create a solution that makes intelligent routing decisions. Using both traditional techniques and AI assistance, you'll learn to select the right models, measure their effectiveness, and document your approach for production deployment.

涵盖的内容

6个视频2篇阅读材料2个作业2个非评分实验室2个插件

From automated pipelines to clear documentation, this module transforms individual ML components into a production-ready system. Using TicketWise's support ticket routing solution as a practical example, you'll learn to build automated data pipelines, deploy models in AWS SageMaker, create insightful visualizations, and generate comprehensive documentation. Through hands-on labs and real-world scenarios, you'll master the skills needed to turn promising models into valuable business solutions, using both traditional techniques and AI assistance to ensure your work is scalable, maintainable, and well-documented.

涵盖的内容

6个视频5篇阅读材料2个作业4个非评分实验室2个插件

In this culminating module, you'll demonstrate your mastery of end-to-end data science solutions. Through component integration scenarios and a comprehensive final assessment, you'll show how different tools and techniques work together effectively. Using TicketWise's support ticket routing system as context, you'll showcase your ability to design integrated solutions while considering business impact. Through guided reflection, you'll also identify growth opportunities and prepare for your next steps as a data science professional.

涵盖的内容

2个视频2篇阅读材料2个作业2个插件

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常见问题

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。