A comprehensive business analytics course is designed to provide students with the skills and knowledge needed to analyze business data effectively. Below is a sample syllabus for a business analytics course that can be adapted for various educational platforms, including online courses like those offered on Coursera.
Course Title: Introduction to Business Analytics
Course Description:
This course introduces the fundamental concepts of business analytics and the role of data in decision-making processes. Students will learn to apply various analytical techniques to real-world business problems, using tools such as Excel, SQL, and Python. The course emphasizes practical skills and hands-on experience through projects and case studies.
Course Objectives:
- Understand the importance of business analytics in modern organizations.
- Develop proficiency in data analysis tools and techniques.
- Learn to interpret and communicate analytical results effectively.
- Apply analytical methods to solve business problems.
Prerequisites:
- Basic knowledge of statistics
- Familiarity with Excel
- Basic programming knowledge (recommended but not required)
Course Outline:
Week 1: Introduction to Business Analytics
- Overview of business analytics
- Types of analytics: descriptive, predictive, and prescriptive
- Role of data in business decision-making
- Case studies of business analytics applications
Week 2: Data Collection and Cleaning
- Data sources and data types
- Data collection methods
- Data cleaning and preprocessing
- Handling missing data and outliers
Week 3: Descriptive Analytics
- Summary statistics
- Data visualization techniques
- Exploratory data analysis (EDA)
- Tools: Excel, Tableau
Week 4: Predictive Analytics
- Introduction to predictive modeling
- Regression analysis
- Classification techniques
- Time series forecasting
- Tools: Excel, R, Python
Week 5: Prescriptive Analytics
- Optimization techniques
- Decision analysis
- Simulation modeling
- Tools: Excel Solver, R, Python
Week 6: Data Visualization
- Principles of effective data visualization
- Creating dashboards and reports
- Tools: Tableau, Power BI
Week 7: Business Applications of Analytics
- Marketing analytics
- Financial analytics
- Operations analytics
- Human resources analytics
- Case studies and real-world applications
Week 8: Advanced Topics in Business Analytics
- Big data analytics
- Machine learning in business analytics
- Text and sentiment analysis
- Ethical considerations in data analytics
Week 9: Capstone Project
- Project planning and execution
- Data collection and analysis
- Presenting findings and recommendations
- Peer review and feedback
Week 10: Review and Final Exam
- Review of key concepts and techniques
- Practice problems and case studies
- Final exam
Course Materials:
- Textbook: “Business Analytics: Data Analysis & Decision Making” by Albright and Winston
- Software: Excel, Tableau, R, Python
- Additional readings and case studies provided by the instructor
Assessment and Grading:
- Weekly quizzes (20%)
- Assignments and projects (40%)
- Capstone project (20%)
- Final exam (20%)
Learning Resources:
- Online tutorials and videos
- Discussion forums for peer interaction and support
- Office hours for instructor assistance
Conclusion:
This sample syllabus outlines the structure and content of a typical business analytics course. By following this syllabus, students will gain a solid foundation in business analytics, preparing them for various roles in data analysis and decision-making in modern organizations.
