Databases & SQL for Data Science with Python
 
Databases & SQL for Data Science with Python is a practical, hands-on course designed to provide learners with the essential SQL and database skills required for data science, analytics, and modern application development. This course bridges foundational database concepts with real-world Python integrations, giving you the tools to query, analyze, and manipulate data efficiently.
 
Through guided SQL exercises, Python-based data workflows, and real datasets, you’ll learn how to extract insights, clean and transform data, join multiple tables, and perform analytical queries. You’ll also explore how Python libraries connect to databases, enabling seamless data retrieval and processing for machine learning, reporting, and automation tasks.
 
What You’ll Learn
Core SQL concepts: queries, filtering, sorting, joins, grouping, and aggregation
Working with relational databases such as MySQL, PostgreSQL, or SQLite
Data modeling, table design, and normalization fundamentals
Using Python to interact with databases via libraries like sqlite3, SQLAlchemy, and pandas
Query optimization basics and best practices
Building analytical queries for data science workflows
Importing, cleaning, and transforming data with SQL and Python
Integrating SQL results into Python-based dashboards, ML models, and visualizations
 
Who This Course Is For
Aspiring data scientists, analysts, and machine learning practitioners
Python developers looking to strengthen SQL and database skills
Students entering data-driven roles across business, tech, or research
Anyone needing SQL proficiency to work with structured data
 
Course Outcomes
By the end of this course, you will be able to:
Write SQL queries to retrieve, filter, join, and analyze data
Build and manage relational database schemas
Use Python to connect to databases and automate data workflows
Apply SQL skills directly to data science and analytics projects
Combine SQL and Python for end-to-end data manipulation and insight generation