Professional Program In Financial Modeling Using Analytics

Course Curriculum:

• Module 1 Problem Solving in Excel
  • Problem identification & solving approach
  • Descriptive statistics
  • Excel basics
  • Excel functions & Financial Math
  • Excel visualization
  • Storytelling with data
  • Learning Outcome
    • Know what types of business problems can emerge
    • › Break-down a problem to component parts
    • › Collect data and describe the problem
    • › Compute and present a solution
• Module 2 Financial Statement Analysis
  • Introduction to FSA
  • Income statements
  • Balance sheet
  • Cash ?ow
  • Ratio analysis
  •  Learning Outcomes
    • Attribute transactions
    • Create an Income statement, a Balance Sheet and a Cash Flow statement
    • Calculate ratios from Financial Statements
    • Interpret ratios
• Module 3 Corporate Finance
  • Time Value of Money and IRR
  • Cost of Capital
  • Sources and used of Capital
  • Build your first model
  • Learning Outcomes
    • Understand what metrics are required to take financial decisions
    • Evaluate a financial opportunity
    • Make a project finance model
• Module 4 Equity Modeling
  • Introduction to valuation
  • Souring historical data
  • Forecasting costs and revenues
  • Forecasting BS and CFS
  • DCF & Relative valuation
• Module 5 – Risk Management
  • Risk management practices
  • Compliance and regulatory reporting
  • Clearing process
  • Settlement process
  • Investor grievances and arbitration
  • Other services provided by brokers
• Module 6 Power BI
  • Business Intelligence (BI) Concepts
  • Microsoft Power BI (MSPBI) Introduction
  • Connecting Power BI with Different Data Sources
  • Power Query for Data Transformation
  • Data Modelling in Power BI
  • Reports in Power BI
  • Reports & Visualization Types in Power BI
  • Dashboards in Power BI
• Module 7 R program
  • R Introduction
  • R Basics
  • R Statements
  • R Loops
  • R Functions
  • R Data Structures
  • R Functions
  • R Advance
  • Data Interfaces
  • Data Visualization
  • R Regression
  • R Statistics