BeginnerUpdated January 2025

SQL for Data Analysis

Master SQL for Data Analysis and Business Intelligence

4.7(4,187 reviews)
31,200 students
7 weeks total
84 lectures

Course Structure

14
Live Teacher Sessions
14
Homework Sessions
28
Total Sessions
7
Weeks Duration
SQL QueriesData AggregationWindow FunctionsCTEsData CleaningBusiness Analytics

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Course Overview

Master SQL for data analysis and business intelligence

This comprehensive course follows a structured learning approach with 14 live teacher sessions and 14 homework sessions, ensuring you get both expert guidance and plenty of hands-on practice.

Prerequisites

  • Basic computer knowledge required
  • No programming experience necessary
  • Understanding of basic mathematics
  • Access to SQL database system
  • Basic spreadsheet knowledge helpful
  • Analytical thinking and curiosity

What You'll Learn

SQL Fundamentals & Database Design Principles
Advanced Querying & Data Filtering Techniques
Data Aggregation & Statistical Analysis
Complex Joins & Multi-Table Analysis
Subqueries & Common Table Expressions (CTEs)
Window Functions & Advanced Analytics
Data Cleaning & Transformation Techniques
Time Series Analysis & Trend Calculations
Business Intelligence & KPI Development
Query Optimization & Performance Tuning

Course Projects

E-commerce Analytics Dashboard

Build a comprehensive e-commerce analytics system with SQL

SQLWindow FunctionsCTEsAdvanced Analytics
Duration: Final 2 weeks
Features: 5 components
Key Features:
  • Sales analytics
  • Customer segmentation
  • Product performance
  • Trend analysis
  • Executive reporting

Financial Performance Analysis System

Create a financial analysis and reporting system

SQLTime SeriesStatistical FunctionsBusiness Intelligence
Duration: Week 6-7
Features: 5 components
Key Features:
  • Revenue analysis
  • Growth calculations
  • Comparative reporting
  • KPI tracking
  • Forecasting preparation

Certificate of Completion

Upon successful completion, you'll receive a verified certificate to showcase your achievement.

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SQL for Data Analysis

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