SQL for Data Science Capstone Project

Description

In this course, you will :

• 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

Syllabus :

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

• The Proposal Process
• Import of Elon Musk Data
• Initial Feature Exploration / Hypotheses
• Entity Relationship Diagram (ERD) for Analysis
• Data Models, Part 1: Thinking About Your Data
• Data Models, Part 2: The Evolution of Data Models
• Data Models, Part 3: Relational vs. Transactional Models
• SQL in Notebooks
• Import Data
• Introduction of Data of Unknown Quality

2. Descriptive Stats & Understanding Your Data

• Importance of Understanding Your Data
• Foundational Stats in SQL/Sheets
• Pandas Teach on Stats
• Visualization with raw graphics.io
• Impact of Findings on Hypotheses

3. Beyond Descriptive Stats (Dive Deeper/Go Broader)

• TF-IDF for Word Frequency / Theme Analysis
• Text Analysis of Elon Musk Tweets
• Create a New Metric
• Analyze Results

4. Presenting Your Findings (Storytelling)

• Sample Output / Presentation
• Module Introduction
• Working with Text Strings
• Working with Date and Time Strings
• Date and Time Strings Examples
• Case Statements
• Views
• Data Governance and Profiling
• Using SQL for Data Science