Microsoft Azure Cloud Advocates 精心打造了一套 10 周的数据科学课程，共 20 个模块。通过结合前测、后测、详细指导、解答和实战项目，我们采用“边学边建”的教学方式，帮助你更有效地掌握数据科学知识。
梗概
教学理念：
- 项目为本： 让学生通过实践项目来学习数据科学。
- 频繁测验： 设置了课程前和课程后的测验，以强化学生的学习效果。
课程内容：
- 数据科学基础原理
- 伦理概念
- 数据准备
- 数据处理方法
- 数据可视化
- 数据分析
- 数据科学的实际应用案例
测验的作用：
- 课程前测验： 帮助学生明确学习目标。
- 课程后测验： 巩固学生的学习成果。
课程特点：
- 灵活性和趣味性： 课程可以整体或部分学习。
- 项目难度递增： 项目从简单到复杂，逐步提高难度。
课程资源：
- 可选资源： Sketchnote、补充视频。
- 课程内容： 课程前测验、书面课程、项目构建指导、知识检查、挑战、补充阅读、作业、课程后测验。
- 测验： 共 40 个测验，每个测验 3 题，可以在本地运行或部署到 Azure。
目录
| 序号 | 主题 | 课程分组 | 学习目标 | 课程链接 | 作者 |
|---|---|---|---|---|---|
| 01 | Defining Data Science | Introduction | Learn the basic concepts behind data science and how it’s related to artificial intelligence, machine learning, and big data. | lesson video | Dmitry |
| 02 | Data Science Ethics | Introduction | Data Ethics Concepts, Challenges & Frameworks. | lesson | Nitya |
| 03 | Defining Data | Introduction | How data is classified and its common sources. | lesson | Jasmine |
| 04 | Introduction to Statistics & Probability | Introduction | The mathematical techniques of probability and statistics to understand data. | lesson video | Dmitry |
| 05 | Working with Relational Data | Working With Data | Introduction to relational data and the basics of exploring and analyzing relational data with the Structured Query Language, also known as SQL (pronounced “see-quell”). | lesson | Christopher |
| 06 | Working with NoSQL Data | Working With Data | Introduction to non-relational data, its various types and the basics of exploring and analyzing document databases. | lesson | Jasmine |
| 07 | Working with Python | Working With Data | Basics of using Python for data exploration with libraries such as Pandas. Foundational understanding of Python programming is recommended. | lesson video | Dmitry |
| 08 | Data Preparation | Working With Data | Topics on data techniques for cleaning and transforming the data to handle challenges of missing, inaccurate, or incomplete data. | lesson | Jasmine |
| 09 | Visualizing Quantities | Data Visualization | Learn how to use Matplotlib to visualize bird data 🦆 | lesson | Jen |
| 10 | Visualizing Distributions of Data | Data Visualization | Visualizing observations and trends within an interval. | lesson | Jen |
| 11 | Visualizing Proportions | Data Visualization | Visualizing discrete and grouped percentages. | lesson | Jen |
| 12 | Visualizing Relationships | Data Visualization | Visualizing connections and correlations between sets of data and their variables. | lesson | Jen |
| 13 | Meaningful Visualizations | Data Visualization | Techniques and guidance for making your visualizations valuable for effective problem solving and insights. | lesson | Jen |
| 14 | Introduction to the Data Science lifecycle | Lifecycle | Introduction to the data science lifecycle and its first step of acquiring and extracting data. | lesson | Jasmine |
| 15 | Analyzing | Lifecycle | This phase of the data science lifecycle focuses on techniques to analyze data. | lesson | Jasmine |
| 16 | Communication | Lifecycle | This phase of the data science lifecycle focuses on presenting the insights from the data in a way that makes it easier for decision makers to understand. | lesson | Jalen |
| 17 | Data Science in the Cloud | Cloud Data | This series of lessons introduces data science in the cloud and its benefits. | lesson | Tiffany and Maud |
| 18 | Data Science in the Cloud | Cloud Data | Training models using Low Code tools. | lesson | Tiffany and Maud |
| 19 | Data Science in the Cloud | Cloud Data | Deploying models with Azure Machine Learning Studio. | lesson | Tiffany and Maud |
| 20 | Data Science in the Wild | In the Wild | Data science driven projects in the real world. | lesson | Nitya |
