Financial Analytics (30-Day Plan)

1. Module 1: Introduction to Financial Analytics (2 Days)

2. Module 2: Excel for Financial Analysis (4 Days)

3. Module 3: Financial Statements and Data Interpretation (4 Days)

4. Module 4: SQL for Financial Data Analysis (3 Days)

5. Module 5: Python for Financial Analytics (4 Days)

6. Module 6: Statistical Analysis and Financial Modeling (4 Days)

7. Module 7: Data Visualization for Financial Insights (3 Days)

8. Module 8: Risk Management and Decision Making (3 Days)

9. Module 9: Final Wrap-Up (3 Days)

Syllabus in Detail for 30 Days

Module 1: Introduction to Financial Analytics (2 Days)

Overview

• What is Financial Analytics?

• Importance and Applications of Financial Analytics

• Role of a Financial Analyst in Modern Business

Core Concepts

• Types of Financial Data: Internal vs. External

• Overview of Key Financial Metrics and Ratios

Module 2: Excel for Financial Analysis (4 Days)

Excel Basics

• Spreadsheet Navigation and Formatting

• Using Functions: SUM, AVERAGE, COUNT, etc.

Advanced Excel

• Financial Functions: PV, NPV, IRR, XIRR

• Data Sorting, Filtering, and Validation

• Creating Dashboards and Visualizations

• What-If Analysis and Scenario Planning

• Pivot Tables and Power Query

Module 3: Financial Statements and Data Interpretation (4 Days)

Financial Statements Overview

• Income Statement: Key Components and Analysis

• Balance Sheet: Understanding Assets, Liabilities, and Equity

• Cash Flow Statement: Cash Flow from Operations, Investing, and Financing

Financial Ratios

• Liquidity Ratios: Current Ratio, Quick Ratio

• Profitability Ratios: Gross Margin, ROE, ROA

• Efficiency Ratios: Asset Turnover, Inventory Turnover

Case Studies and Exercises

• Analyzing Financial Statements of Real Companies

Module 4: SQL for Financial Data Analysis (3 Days)

SQL Fundamentals

• Understanding Databases and Tables

• Writing Queries: SELECT, WHERE, ORDER BY

Advanced SQL

• Joins: INNER, LEFT, RIGHT, FULL OUTER

• Aggregate Functions: SUM, AVG, COUNT, GROUP BY

• Subqueries and Common Table Expressions (CTEs)

• Case-Based Conditions in SQL

Practical Applications

• Extracting Financial Data from Databases

Module 5: Python for Financial Analytics (4 Days)

Python Basics

• Syntax, Data Types, and Functions

• Libraries for Financial Analytics: Pandas, NumPy, Matplotlib

Advanced Python

• Time Series Analysis

• Automating Financial Calculations

• Forecasting and Trend Analysis

Hands-On Exercises

• Building Financial Models with Python

Module 6: Statistical Analysis and Financial Modeling (4 Days)

Statistics Basics

• Descriptive Statistics: Mean, Median, Mode, Standard Deviation

• Probability Distributions and Hypothesis Testing

Financial Modeling

• Building Forecast Models (Revenue and Expense Projections)

• Sensitivity Analysis

• Monte Carlo Simulation

Applications

• Stock Valuation Models (DCF, Multiples Approach)

Module 7: Data Visualization for Financial Insights (3 Days)

Visualization Tools

• Introduction to Tableau/Power BI for Financial Analytics

• Key Financial Dashboards: Profit/Loss, Budget vs. Actual, Cash Flow

Best Practices

• Storytelling with Financial Data

• Choosing the Right Charts for Financial Insights

Module 8: Risk Management and Decision Making (3 Days)

Risk Management Basics

• Types of Financial Risks (Market, Credit, Operational)

• Risk Assessment Techniques

Decision-Making Models

• Scenario and Sensitivity Analysis

• Game Theory in Financial Decision-Making

Module 9: Final Wrap-Up (3 Days)

Capstone Project

• End-to-End Financial Analytics Project

• Data Cleaning, Analysis, and Visualization

Mock Interviews

• Common Financial Analytics Interview Questions

• Resume Preparation and Industry Tips

Job Application Assistance

• Guidance for Financial Analyst Roles

Highlights of the Curriculum

• Practical and Hands-On Training: Real-world case studies and projects

• Multi-Tool Exposure: Excel, SQL, Python, Tableau/Power BI

• Industry-Relevant Applications: Financial statement analysis, risk management, and financial modeling

This curriculum ensures a comprehensive understanding of financial analytics, providing both theoretical knowledge and practical skills for career advancement.