Topics covered in this course:
Module 1: SQL Fundamentals
•    Understand SQL concepts, data types, and database structures.
•    Create, modify, and query databases and tables effectively.
•    Learn essential SQL clauses like SELECT, FROM, WHERE, GROUP BY, and HAVING.
Module 2: Data Manipulation and Analysis
•    Master advanced SQL techniques for data manipulation and analysis.
•    Perform aggregation, filtering, and sorting operations on data.
•    Use JOINs to combine data from multiple tables.
Module 3: Data Cleaning and Preparation
•    Learn data cleaning techniques to handle missing values, outliers, and inconsistencies.
•    Prepare data for analysis by transforming and formatting it appropriately.
Module 4: Window Functions and Subqueries
•    Explore advanced SQL concepts like window functions and subqueries.
•    Use window functions for calculations across rows and subqueries for nested queries.
Module 5: Mathematical Functions and Statistical Analysis
•    Learn to use SQL's built-in mathematical functions for calculations and statistical analysis.
•    Calculate averages, standard deviations, correlations, and other statistical metrics.
Module 6: String Functions and Text Manipulation
•    Master SQL functions for working with text data, including concatenation, substring extraction, and pattern matching.
•    Clean and preprocess text data for analysis.
Module 7: Performance Tuning and Optimization
•    Understand query optimization techniques to improve query performance.
•    Create indexes and analyze query execution plans.
•    Optimize database design and configuration for efficient data access.
Module 8: Advanced Data Analysis Techniques
•    Explore advanced SQL techniques like common table expressions (CTEs), recursive queries, and pivot/unpivot operations.
•    Solve complex data analysis problems and extract valuable insights.
Module 9: Case Studies and Practical Exercises
•    Work on real-world data analysis projects to apply your SQL skills.
•    Solve practical problems and gain hands-on experience with data analysis.
Module 10: Integrating SQL with Data Science Tools
•    Learn how to integrate SQL with popular data science tools like Python and R.
•    Use SQL to extract and prepare data for analysis in these tools.

By completing this course, you'll gain a comprehensive understanding of SQL and its applications in data analysis. You'll be well-prepared to extract valuable insights from your data and contribute to data-driven decision making.