Business Analyst Course Syllabus

An in-depth, tool-agnostic Business Analyst Master’s Program that equips you with end-to-end analytics skills through hands-on projects and expert instruction. This 148-hour program spans 25 weeks with a blend of live sessions and self-paced learning, covering essential tools from Excel to Python, SQL, Tableau, and Power BI. You’ll progress from foundational data analysis to advanced visualization and modeling, culminating in real-world applications and project work. Lifetime access to course materials ensures flexible, ongoing learning.

Module 1: Advanced MS Excel 2016 Certification Training

Estimated time: 16 hours

• Advanced formulas and functions
• Pivot tables and data summarization
• Power Query for data transformation
• Macros and automation
• Interactive dashboard creation

Module 2: Statistics Essentials for Analytics

Estimated time: 10 hours

• Descriptive statistics and data distributions
• Probability fundamentals
• Hypothesis testing
• Linear regression basics

Module 3: Microsoft SQL Server Certification Training

Estimated time: 30 hours

• SQL DDL and DML commands
• Joins, subqueries, and filtering
• Indexing and query optimization
• Transactions and database management
• Azure SQL fundamentals

Module 4: Data Science with Python Certification Course

Estimated time: 26 hours

• Python basics for data analysis
• Data manipulation with Pandas and NumPy
• Data visualization using Matplotlib
• Introductory machine learning concepts

Module 5: Tableau Certification Training Course

Estimated time: 36 hours

• Tableau Prep for data cleaning
• Advanced charting and LOD expressions
• Interactive dashboard design
• Multi-source data integration

Module 6: Microsoft Power BI Certification Training Course

Estimated time: 30 hours

• Power BI Desktop and data modeling
• DAX calculations and measures
• Report publishing and data refresh
• Row-level security configuration

Module 7: Elective Self-Paced Courses

Estimated time: Self-paced

• SAS programming fundamentals
• Data warehousing and BI concepts
• R programming for analytics
• Informatica data integration
• Software development basics

Prerequisites

• Familiarity with basic spreadsheet operations
• Basic understanding of databases
• Willingness to learn programming concepts

What You'll Be Able to Do After

• Build dynamic financial models and dashboards in Excel
• Perform statistical analysis and hypothesis testing
• Write and optimize complex SQL queries
• Conduct data analysis and visualization using Python
• Create interactive reports in Tableau and Power BI