Become a Data Analyst: Python, SQL, Excel, Power BI Course Syllabus

Overview: This comprehensive course is designed to take you from beginner to job-ready data analyst using Python, SQL, Excel, and Power BI. With a structured, hands-on approach, you'll gain practical experience through guided projects, real-world case studies, and interactive labs. The curriculum spans approximately 15–20 hours, combining foundational concepts with applied learning to ensure you build portfolio-ready skills. Ideal for aspiring data analysts, this course emphasizes real-world applications and industry best practices.

Module 1: Development Environment & Tools

Estimated time: 2 hours

• Review of tools and frameworks commonly used in data analysis
• Setting up Python and SQL environments
• Introduction to Excel and Power BI interfaces
• Configuring development tools for data workflows

Module 2: Core Programming Concepts

Estimated time: 3 hours

• Introduction to key programming concepts in Python
• Writing clean and maintainable code
• Using variables, data types, and control structures
• Applying core logic in data analysis tasks

Module 3: Data Structures & Algorithms

Estimated time: 4 hours

• Working with lists, dictionaries, and arrays in Python
• Efficient data manipulation using pandas
• Understanding algorithmic thinking for data tasks
• Interactive lab: Building practical data solutions

Module 4: Application Architecture

Estimated time: 1.5 hours

• Understanding data pipeline structures
• Case study analysis with real-world examples
• Best practices in organizing analytical code

Module 5: Testing & Quality Assurance

Estimated time: 3.5 hours

• Implementing testing strategies for data workflows
• Validating data accuracy and integrity
• Debugging and optimizing data processes

Module 6: Deployment & DevOps

Estimated time: 2.5 hours

• Introduction to key concepts in deployment & DevOps
• Sharing Power BI dashboards and Excel reports
• Automating data workflows and publishing results

Prerequisites

• Basic computer literacy
• Familiarity with spreadsheets (no coding experience required)
• Willingness to learn programming fundamentals

What You'll Be Able to Do After

• Analyze data using Python and pandas
• Write efficient SQL queries for data extraction
• Visualize insights using Excel and Power BI
• Build end-to-end data analysis projects
• Apply best practices in data quality and reporting