Introduction to Business Forecasting & Analytics

This course provides students with an understanding of the tools and techniques used to predict future business trends and make data-driven decisions. This course covers key topics such as time series analysis, regression models, and predictive analytics. Students will learn how to analyze historical data to forecast sales, market trends, and business performance. Emphasis is placed on the practical application of forecasting methods using statistical software and data visualization tools. Through case studies and projects, students will gain hands-on experience in applying analytics to real-world business challenges.

Upon successful completion of this course, students will be able to:

• Understanding Forecasting Techniques: Students will develop a solid understanding of various forecasting methods, including time series analysis, moving averages, exponential smoothing, and regression models.
• Data-Driven Decision-Making: Gain the ability to use business analytics to make informed decisions by interpreting historical data and identifying patterns that influence future trends.
• Application of Predictive Models: Learn to apply predictive models and analytics tools to forecast key business metrics such as sales, demand, and financial performance, ensuring data-driven strategies.
• Use of Analytical Software and Visualization: Develop proficiency in using statistical software (e.g., Excel, R, Python) and data visualization tools to communicate forecasting results and insights to stakeholders effectively.

These outcomes are designed to equip students with the knowledge and skills to perform accurate business forecasting and analytics, helping organizations make better strategic decisions in dynamic markets.