Course Overview:
SQL is a fundamental skill for data analysts, data scientists, and professionals in data-related roles. With the growing reliance on data for decision-making, SQL proficiency is highly sought after in the job market. This course is designed to equip participants with the essential skills needed to manipulate and analyze data using SQL (Structured Query Language). The course covers foundational SQL concepts as well as advanced data retrieval techniques and data analysis strategies tailored for data science applications. Participants will engage in hands-on exercises and real-world case studies to ensure they can effectively utilize SQL to drive insights and support data-driven decision-making.
Duration
10 Days
Who Should Attend
This course is suitable for individuals with a basic understanding of data science concepts who want to strengthen their SQL skills. Data analysts, data scientists, machine learning engineers, and anyone working with large datasets will benefit from this training.
Course Level: IntermediateCourse Objectives
By the end of this course, participants will be able to:
- Understand the fundamentals of SQL and its role in data science.
- Write complex SQL queries to extract and manipulate data from relational databases.
- Utilize advanced SQL functions for data aggregation, filtering, and transformation.
- Implement techniques for data analysis and reporting using SQL.
- Apply best practices for database design and optimization.
- Solve real-world data science problems using SQL through practical exercises and projects.
Course Outline:
Module 1: Introduction to SQL
- Overview of databases and data structures
- Introduction to SQL syntax and commands
- Setting up the database environment
Module 2: Basic SQL Queries
- SELECT statements
- Filtering data with WHERE clause
- Sorting data with ORDER BY
Module 3: Advanced Querying Techniques
- Joins (INNER, LEFT, RIGHT, FULL)
- Subqueries and nested queries
- Working with multiple tables
Module 4: Data Aggregation and Grouping
- Using GROUP BY for aggregation
- Aggregate functions (COUNT, SUM, AVG, MAX, MIN)
- HAVING clause for filtered groups
Module 5: Data Manipulation
- INSERT, UPDATE, DELETE operations
- Understanding transactions and data integrity
- Managing constraints
Module 6: Functions and Expressions
- String functions and date functions
- Mathematical functions
- Using CASE statements for conditional logic
Module 7: Database Design Principles
- Understanding normalization and denormalization
- Keys and indexes in database design
- Best practices for schema design
Module 8: SQL for Data Science
- Introduction to data analysis concepts in SQL
- Handling missing data and duplicates
- Data transformation techniques
Module 9: Practical Case Studies
- Real-world case studies to apply SQL skills
- Analyzing a dataset using SQL
Module 10: Final Project and Review
- Review of key concepts and Q&A session
- Feedback and course wrap-up
