IBM: SQL for Data Science course Syllabus

Full curriculum breakdown — modules, lessons, estimated time, and outcomes.

Overview: This beginner-friendly course introduces the fundamentals of SQL for data science, designed by IBM to equip learners with essential skills for data analysis. Through hands-on practice, you'll learn to query databases, manipulate data, and perform real-world analysis tasks. The course spans approximately 8–10 weeks with a weekly commitment of 3–5 hours, combining theory, exercises, and a final project to solidify your skills.

Module 1: Introduction to Databases and SQL

Estimated time: 8 hours

  • Understand what databases are and their role in data science
  • Learn core database concepts: tables, rows, columns, and keys
  • Write basic SELECT statements to retrieve data
  • Explore the role of SQL in analytics and data-driven decision-making

Module 2: Filtering, Sorting, and Aggregating Data

Estimated time: 10 hours

  • Use WHERE clause to filter query results
  • Sort data using ORDER BY and limit output with LIMIT
  • Apply aggregate functions: COUNT, SUM, AVG, MIN, MAX
  • Group data using GROUP BY and filter groups with HAVING

Module 3: Working with Multiple Tables

Estimated time: 12 hours

  • Understand table relationships and primary/foreign keys
  • Perform inner joins to combine related tables
  • Use left joins to retain unmatched records
  • Write subqueries for nested data retrieval

Module 4: SQL for Data Analysis

Estimated time: 12 hours

  • Analyze real-world datasets using SQL queries
  • Perform descriptive data analysis directly in databases
  • Prepare and transform data for visualization and reporting

Module 5: Applying SQL in Data Science Scenarios

Estimated time: 10 hours

  • Solve practical data science problems using SQL
  • Integrate SQL skills into analytics workflows
  • Build foundational knowledge for data analyst and data science roles

Module 6: Final Project

Estimated time: 15 hours

  • Query a real-world relational database
  • Perform multi-step data analysis using joins and aggregations
  • Generate insights and present findings from raw data

Prerequisites

  • Familiarity with basic computer operations
  • No prior programming or database experience required
  • Interest in data analysis or data science careers

What You'll Be Able to Do After

  • Write and execute SQL queries to retrieve and manipulate data
  • Analyze data stored in relational databases
  • Combine data from multiple tables using joins and subqueries
  • Perform descriptive analytics using aggregate functions and grouping
  • Apply SQL skills to real-world data science and analytics challenges
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