SQL & Advanced Analytics

Integration of SQL querying and statistical analysis within the Data Science workflow.

📋 Covered Topics:

• Relational Databases: Writing structured queries using SELECT statements.
• Complex Logic: Implementing Subqueries to handle multi-step data retrieval.
• Data Merging: Mastering various Join types to combine disparate datasets.
• Statistical Grouping: Using Aggregations to extract high-level metrics and insights.
• Experimental Design: Introduction to A/B testing methodology and result interpretation.

🛠 Tech Stack:

• Languages: SQL, Python
• Library: Pandas, SQLAlchemy (or similar connector used)
• Methodology: Hypothesis Testing, A/B Analysis