This course dives into real-world data sourcing, including making web requests, web scraping, and integrating diverse data types from APIs, files, and databases. You'll learn to parse and structure data in formats like XML and JSON, and leverage object-oriented programming to create robust data models. By the end of the course, you’ll be equipped to efficiently acquire, transform, and prepare data for advanced analysis.
Data Science Fundamentals Part 1: Unit 2
Data Science Fundamentals Part 1: Unit 2
本课程是 Data Science Fundamentals, Part 1 专项课程 的一部分
位教师：Pearson
包含在 
中
您将学到什么
Master the ETL (Extract, Transform, Load) process for seamless data acquisition and integration.
Acquire practical skills in sourcing data from APIs, web scraping, and managing data lineage.
Parse and transform diverse data formats (XML, JSON) for structured analysis.
Build and apply data models using object-oriented programming to streamline data workflows.
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最近已更新！
August 2025
作业
2 项作业
授课语言：英语（English）
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
本课程是 Data Science Fundamentals, Part 1 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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该课程共有1个模块
This module guides learners through the foundational steps of the data science process, focusing on data acquisition and transformation. Starting with methods for sourcing and extracting data from various platforms, students learn to manage data lineage and perform web requests. The module then covers parsing and structuring diverse data formats, such as XML and JSON, emphasizing the importance of data transformation and modeling. Through practical exercises, including working with APIs and relational databases, learners gain essential skills in the Extract, Transform, and Load (ETL) pipeline, preparing them for effective data exploration and analysis.
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