Course Overview
Financial modeling is one of the most important tools used in investment and strategic decision-making, and with the development of artificial intelligence, financial models have become more accurate, faster, and more intelligent.
This course aims to enable participants to integrate artificial intelligence and machine learning techniques with traditional financial modeling methods to build advanced predictive models, analyze financial data with high efficiency, and support data-driven decision-making.
Target Audiences
| · Financial analysts and accountants
· Finance and strategic planning managers · Entrepreneurs and business owners · Banking and investment professionals · Data analysts and data scientists · Those interested in artificial intelligence applications in business |
Course Duration
- Total Hours: 25 training hours
- Number of Days: 5 days
- Hours per Day: 5 hours daily
Course Outline
| 📅 Day 1: Fundamentals and Building Understanding
🔹 Module 1: Fundamentals of Financial Modeling Understanding the concept of financial modeling and its importance in supporting managerial and investment decisions, along with a review of the types of financial models and their practical applications. 🔹 Module 2: Financial Statements and Understanding Their Components Understanding the main financial statements (income, balance sheet, and cash flow) and how to read and analyze them as a basis for building an accurate financial model. 🔹 Module 3: Introduction to Artificial Intelligence in Finance Understanding the concepts of artificial intelligence and machine learning, and how they can be applied to develop and improve financial processes. 📅 Day 2: Building the Financial Model 🔹 Module 4: Preparing and Analyzing Financial Data Learning methods for cleaning, organizing, and analyzing financial data to ensure its readiness for use in financial models and smart applications. 🔹 Module 5: Building an Integrated Financial Model A practical application of building an integrated financial model that professionally links the three financial statements. 🔹 Module 6: Fundamentals of Financial Forecasting Understanding traditional financial forecasting techniques as a foundation before moving on to forecasting using artificial intelligence. 📅 Day 3: Artificial Intelligence in Analysis and Forecasting 🔹 Module 7: Financial Forecasting Using Artificial Intelligence Using AI techniques to build predictive models that help estimate revenues, expenses, and cash flows with greater accuracy. 🔹 Module 8: Time Series Analysis Analyzing financial data over time to discover patterns and trends using AI tools. 🔹 Module 9: Advanced Financial Data Analysis Applying advanced analytical methods to extract performance indicators and make data-driven financial decisions. 📅 Day 4: Evaluation and Decision Making 🔹 Module 10: Valuing Companies Using Financial Models Learning methods to value companies and projects using models such as Discounted Cash Flow (DCF). 🔹 Module 11: Sensitivity and Scenario Analysis Studying the impact of changes in financial variables on results and building multiple scenarios to support decision-making. 🔹 Module 12: Using Artificial Intelligence in Risk Analysis Applying AI to predict financial risks and reduce uncertainty in investment decisions. 📅 Day 5: Practical Application and Automation 🔹 Module 13: Automating Financial Models and Reports Using artificial intelligence tools to automate financial processes and generate reports faster and more accurately. 🔹 Module 14: Building an Intelligent Financial Model (Practical Project) Completing a comprehensive practical project to build an AI-powered financial model that simulates a real-world business environment. 🔹 Module 15: Ethics of Using AI in Finance Understanding the ethical and legal aspects of using artificial intelligence and ensuring the responsible and safe use of these technologies. |
Course Outcomes
| By the end of the course, participants will be able to:
· Building professional financial models and linking financial statements · Using artificial intelligence in financial forecasting and data analysis · Developing accurate investment valuation models (DCFs) and others · Analyzing risks and making data-driven financial decisions · Automating financial processes and reports using AI tools · • Implementing modern technologies to enhance the efficiency of financial operations |