Target Participants: Undergraduate students, postgraduate students, and finance professionals

Course Overview:

This intensive 15-hour course is designed to upskill participants in financial forecasting and business valuation, equipping them with hands-on experience in Excel, R, and Python forecasting tools. The session will cover key valuation methodologies and forecasting techniques used in investment decision-making, corporate finance, and strategic planning.

Learning Objectives:

By the end of the course, participants will:
✅ Understand the fundamentals of financial forecasting and valuation techniques.
✅ Apply time-series forecasting methods using Excel, R, and Python.
✅ Learn to build financial models for valuation (DCF, relative valuation, and multiples approach).
✅ Gain insights into forecast accuracy and model evaluation.

Course Outline:

1️⃣ Introduction to Financial Forecasting

• Importance in investment and corporate finance
• Common forecasting challenges and best practices

2️⃣ Forecasting Tools & Techniques

• Excel: Trend analysis, regression models
• R: Time-series forecasting (ARIMA, exponential smoothing)
• Python: Machine learning in forecasting (random forest, neural networks)

3️⃣ Business Valuation Methods

• Discounted Cash Flow (DCF) Method
• Relative Valuation (P/E, EV/EBITDA multiples)
• Asset-Based Valuation

4️⃣ Case Study & Hands-on Session

• Practical implementation of forecasting models
• Live demonstration of valuation techniques using real-world datasets

Who Should Attend?

📌 Students looking to enhance their financial modelling skills
📌 Professionals seeking practical exposure to forecasting tools
📌 Analysts and consultants involved in business valuation

Mode of Delivery:

💻 Online – live demonstrations and interactive Q&A

Pre-requisites:

• Basic knowledge of finance and statistics
• Familiarity with Excel (no prior coding experience needed for R/Python)