Business Analytics Specialization Course Syllabus

This specialization provides a comprehensive introduction to business analytics, designed for professionals seeking to leverage data for strategic decision-making. Comprising five core courses and a capstone project, the program spans approximately 20 weeks with a recommended commitment of 3-5 hours per week. Learners will explore analytics in customer management, operations, human resources, and accounting, using industry-standard tools like Excel, R, and Tableau. Each course combines foundational theory with hands-on analysis using real-world datasets, culminating in a capstone project where learners solve a simulated business challenge by applying integrated analytics techniques.

Module 1: Customer Analytics

Estimated time: 12 hours

• Customer segmentation and targeting
• Customer lifetime value (CLV) modeling
• Measuring customer retention and churn
• Analyzing customer data with Excel and R

Module 2: Operations Analytics

Estimated time: 12 hours

• Introduction to queueing theory
• Inventory management using data analysis
• Demand forecasting techniques
• Optimizing operational efficiency with analytics

Module 3: People Analytics

Estimated time: 12 hours

• Workforce performance metrics
• Employee retention analysis
• Hiring effectiveness and talent acquisition analytics
• Using R for HR data interpretation

Module 4: Accounting Analytics

Estimated time: 12 hours

• Financial ratio analysis
• Forecasting earnings with historical data
• Fraud detection using analytical methods
• Interpreting financial statements for business insights

Module 5: Business Analytics Tools and Applications

Estimated time: 15 hours

• Data visualization with Tableau
• Advanced Excel modeling for business scenarios
• Introduction to R for data analysis
• Integrating tools across business functions

Module 6: Final Project

Estimated time: 20 hours

• Define a business problem across marketing, operations, HR, or finance
• Apply descriptive, predictive, and prescriptive analytics techniques
• Deliver a data-driven solution using Excel, R, and Tableau

Prerequisites

• Basic familiarity with Excel
• Introductory knowledge of statistics (helpful but not required)
• Basic coding exposure recommended for R usage

What You'll Be Able to Do After

• Analyze customer data to inform marketing and retention strategies
• Optimize operational workflows using forecasting and queueing models
• Apply people analytics to improve hiring and employee retention
• Interpret financial data to detect risks and support strategic decisions
• Use Excel, R, and Tableau to deliver actionable business insights