课程信息

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中级
完成时间大约为35 小时
英语(English)
字幕:英语(English)

您将学到的内容有

  • ​Develop a project proposal and select your data

  • ​Perform descriptive statistics as part of your exploratory analysis

  • Develop metrics and perform advanced techniques in SQL

  • P​resent your findings and make recommendations

您将获得的技能

Presentation SkillsData AnalysisSQLcreating metricsExploratory Data Analysis
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
中级
完成时间大约为35 小时
英语(English)
字幕:英语(English)

提供方

加州大学戴维斯分校 徽标

加州大学戴维斯分校

教学大纲 - 您将从这门课程中学到什么

1

1

完成时间为 9 小时

Getting Started and Milestone 1: Project Proposal and Data Selection/Preparation

完成时间为 9 小时
12 个视频 (总计 48 分钟), 4 个阅读材料, 1 个测验
12 个视频
Milestone 1 Introduction1分钟
The Proposal Process3分钟
Import of Elon Musk Data5分钟
Initial Feature Exploration / Hypotheses8分钟
Entity Relationship Diagram (ERD) for Analysis2分钟
Data Models, Part 1: Thinking About Your Data5分钟
Data Models, Part 2: The Evolution of Data Models3分钟
Data Models, Part 3: Relational vs. Transactional Models5分钟
SQL in Notebooks3分钟
Import Data2分钟
Introduction of Data of Unknown Quality1分钟
4 个阅读材料
A Note from UC Davis10分钟
Choose Your Client/Dataset30分钟
Connecting to Mode Analytics20分钟
Welcome to Peer Review Assignments!10分钟
2

2

完成时间为 8 小时

Milestone 2: Descriptive Stats & Understanding Your Data

完成时间为 8 小时
7 个视频 (总计 39 分钟), 1 个阅读材料, 1 个测验
7 个视频
Importance of Understanding Your Data2分钟
Foundational Stats in SQL/Sheets9分钟
Pandas Teach on Stats5分钟
Visualization with raw graphics.io6分钟
Impact of Findings on Hypotheses5分钟
Statistics Refresher (Optional)8分钟
1 个阅读材料
Additional Resources20分钟
3

3

完成时间为 8 小时

Milestone 3: Beyond Descriptive Stats (Dive Deeper/Go Broader)

完成时间为 8 小时
5 个视频 (总计 28 分钟)
5 个视频
TF-IDF for Word Frequency / Theme Analysis7分钟
Text Analysis of Elon Musk Tweets5分钟
Create a New Metric5分钟
Analyze Results7分钟
4

4

完成时间为 10 小时

Milestone 4: Presenting Your Findings (Storytelling)

完成时间为 10 小时
12 个视频 (总计 61 分钟), 7 个阅读材料, 1 个测验
12 个视频
Sample Output / Presentation7分钟
Module Introduction1分钟
Working with Text Strings7分钟
Working with Date and Time Strings5分钟
Date and Time Strings Examples5分钟
Case Statements7分钟
Views6分钟
Data Governance and Profiling5分钟
Using SQL for Data Science, Part 15分钟
Using SQL for Data Science, Part 26分钟
Course Summary57
7 个阅读材料
Resources on the Who, What, Why, and How20分钟
Resources on Audience30分钟
Dashboard and Storytelling with Data10分钟
Finding the Story10分钟
Prioritizing, Optimizing and Designing the Data Story10分钟
Tell the Story of Your Data10分钟
Additional SQL Resources to Explore15分钟

审阅

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关于 Learn SQL Basics for Data Science 专项课程

This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, and more. These topics will prepare you to apply SQL creatively to analyze and explore data; demonstrate efficiency in writing queries; create data analysis datasets; conduct feature engineering, use SQL with other data analysis and machine learning toolsets; and use SQL with unstructured data sets....
Learn SQL Basics for Data Science

常见问题

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