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
- Present 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