Topics covered in this course include :

Module 1: SQL Fundamentals and Data Structures

• Understand SQL concepts, data types, and database structures.
• Create, modify, and query databases and tables effectively.
• Learn to work with different data types and data structures.
  
   

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 data science analysis by transforming and formatting it appropriately.
  
   

Module 4: Window Functions and Subqueries

• Explore advanced SQL concepts like window functions and subqueries.
• Use these techniques to perform complex calculations and data analysis.
  
   

Module 5: SQL for Machine Learning

• Understand how to prepare data for machine learning models using SQL.
• Extract features and create datasets suitable for machine learning algorithms.
  
   

Module 6: Case Studies and Practical Exercises

• Work on real-world data science projects to apply your SQL skills.
• Solve practical problems and gain hands-on experience with data analysis.
  
   

Module 7: 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 the confidence and skills to extract valuable insights from your data using SQL. You'll be well-prepared to pursue data science roles and contribute to data-driven decision making.