Prerequisites

• Basic computer literacy
• Fundamental mathematics skills
• Understanding of basic statistics
• Spreadsheet software knowledge
• Basic programming concepts (optional)
• Computer with minimum 8GB RAM

Course Syllabus

Week 1: Foundations of Business Analytics

• Introduction to business analytics
• Data types and structures
• Basic statistical concepts
• Business intelligence fundamentals
• Analytics ecosystem overview
• Decision-making frameworks
• Technology integration strategies

Week 2: Data Management and SQL

• Database fundamentals
• Advanced SQL techniques
• Data extraction methods
• ETL (Extract, Transform, Load) processes
• Data cleaning techniques
• Database optimization
• Query performance strategies

Week 3: Statistical Analysis

• Descriptive statistics
• Inferential statistics
• Hypothesis testing
• Regression analysis
• Probability theory
• Statistical modeling
• Experimental design principles

Week 4: Data Visualization

• Visualization techniques
• Tableau and Power BI fundamentals
• Dashboard creation
• Data storytelling
• Interactive reporting
• Visual communication strategies
• KPI representation methods

Week 5: Predictive Analytics

• Machine learning fundamentals
• Predictive modeling techniques
• Classification algorithms
• Regression models
• Decision trees
• Ensemble methods
• Model evaluation metrics

Week 6: Advanced Analytics

• Multivariate analysis
• Time series forecasting
• Neural network basics
• Advanced machine learning
• Clustering techniques
• Feature engineering
• Model optimization strategies

Week 7: Business Intelligence Tools

• Business intelligence platforms
• Advanced analytics software
• Tool selection strategies
• Integration techniques
• Performance measurement
• Comparative platform analysis
• Practical implementation workshops

Week 8: Marketing and Customer Analytics

• Customer segmentation
• Behavioral analytics
• Marketing performance measurement
• Customer lifetime value analysis
• Personalization strategies
• Predictive customer insights
• Campaign effectiveness evaluation

Week 9: Financial and Risk Analytics

• Financial modeling
• Risk assessment techniques
• Investment analytics
• Financial performance analysis
• Fraud detection strategies
• Economic forecasting
• Quantitative financial analysis

Week 10: Big Data and Cloud Technologies

• Big data fundamentals
• Cloud computing integration
• Distributed computing concepts
• Scalable data solutions
• Advanced analytics platforms
• Data governance
• Emerging technological trends

Week 11: Business Analytics Ethics

• Ethical data usage
• Privacy considerations
• Algorithmic bias detection
• Responsible AI development
• Compliance frameworks
• Ethical decision-making
• Regulatory landscape understanding

Week 12: Capstone Project and Career Preparation

• End-to-end analytics project
• Portfolio development
• Industry best practices
• Implementation strategies
• Professional networking
• Career guidance
• Final project presentations

Learning Outcomes

• Advanced analytics skill development
• Comprehensive business intelligence expertise
• Strategic decision-making capabilities
• Professional analytics tool proficiency
• Ethical data management understanding
• Practical implementation knowledge
• Industry-ready business analytics skills

Certification

Students receive a comprehensive Business Analytics certification upon successful course completion.

Note: Course content may be dynamically updated to reflect emerging industry trends and technological advancements.