From Spreadsheets to Repeatable Code
Turn recurring calculations into scripts that can be checked and rerun.
Why professionals choose AAFM® India
The American Academy of Financial Management® has set standards in financial certification since 1996. AAFM® India brings these international standards to Indian professionals, with a curriculum built for Indian markets, regulation, and clients.
Recognized in 151 countries
Conferred under AAFM® international standards, with certification issued from the USA.
300,000+ global alumni
Join a worldwide community of certified wealth managers, planners, and private bankers.
Faculty who practice
Instructors hold CA, CFA, FRM, CFP, and CWM® designations with current industry experience.
A curriculum for this decade
AI in portfolio management, alternative funds, international tax, behavioral finance - updated continuously.
Who this is for
Built for Finance Learners Who Want to Build
Use Python to make financial analysis more repeatable and reporting less manual.
Finance Students and Graduates
Translate investment and financial concepts into working Python exercises.
Investment Analysts
Process price data, analyse portfolios and generate repeatable performance reports.
Risk and Quantitative Teams
Explore simulation, value-at-risk, expected shortfall and scenario analysis.
Finance Operations Professionals
Automate recurring data preparation, reporting and monitoring tasks.
Why choose AAFM India?
Learn Python for Finance. By Building With It.
Move beyond syntax with finance-focused exercises, practical models and repeatable automation workflows.
01
Finance-First Python Learning
Learn programming concepts through financial data, returns, portfolios, risk and reporting instead of isolated coding examples.
02
Structured 24-Chapter Path
Progress from Python foundations and data handling to financial modelling, visualisation, APIs and automation.
03
Hands-On Financial Projects
Apply concepts through practical builds such as performance analysis, portfolio optimisation, risk analysis and dashboards.
04
Build Repeatable Workflows
Turn recurring finance tasks into scripts and processes that can be rerun, checked and improved.
05
Data, Models & Risk
Work with NumPy, pandas, time series, simulations, option pricing and portfolio risk analytics.
06
Automation Beyond Spreadsheets
Connect files, APIs, charts, Excel or PDF outputs and scheduled scripts into practical reporting pipelines.
Your learning goal
Build Finance Tools That Work Beyond One Spreadsheet
Convert a financial requirement into a readable, tested and repeatable script or data workflow.
Python Foundations
Use core data types, functions, classes, error handling and testing for finance problems.
Financial Data
Import, clean, transform and store market, portfolio and transaction datasets.
Returns & Risk
Calculate performance, price options, simulate scenarios and assess portfolio risk.
Reporting Workflows
Build charts, reports, scheduled scripts and data pipelines from APIs.
Program Overview
Learn Python by Solving Finance Problems
Move from your first financial script to analysis you can rerun, explain and improve.
Based on AAFM India’s 24-chapter study material, the lab begins with Python foundations and develops skills in NumPy, pandas, financial time series, statistics and data cleaning. It then applies code to financial calculations, simulation, option pricing, portfolio construction, optimisation and risk. The final chapters bring the work together through visualisation, APIs, scheduled scripts and automated reports.
From a First Script to an Automated Portfolio Report
Start with programming concepts and good development practice. Use NumPy, pandas and time series tools to prepare financial data. Then calculate time value of money, returns and risk; explore Monte Carlo simulations, options, portfolio construction and optimisation.
Finish by creating charts and dashboards, collecting data through files or APIs, and combining the steps in a scheduled reporting pipeline.
01
Foundations
Python data types, classes and code quality.
02
Financial Data
Numerical analysis, statistics, files and storage.
03
Models and Risk
Returns, simulation, options and portfolios.
04
Delivery
Visualisation, reporting, APIs and capstone automation.
Faculty
◆Learn from practitioners, not presenters
AAFM INDIA
From manual effort to repeatable analysis
Make Financial Work Easier to Check and Rerun
From Raw Files to Analysis-Ready Data
Clean missing values, dates and formats before using financial data.
From One-Off Charts to Useful Dashboards
Present returns, risk and portfolio patterns in clear visuals.
From Manual Reports to a Pipeline
Connect data collection, calculations, output files and scheduling.
Industry-relevant skills
Skills You Will Build
Python Development
Build readable scripts and reusable components with basic testing and error handling.
Financial Data Analysis
Use NumPy and pandas to work with tables, arrays and time series.
Performance & Valuation
Calculate returns, ratios, time value of money and illustrative option prices.
Portfolio & Risk Analytics
Apply portfolio weights, optimisation, VaR, expected shortfall and stress scenarios.
Financial Visualisation
Create price charts, correlation heatmaps and portfolio dashboards.
Workflow Automation
Work with files, APIs, scheduled jobs and generated Excel or PDF reports.
Career relevance
Use Python Across Finance and Analytics Roles
Programming skills can strengthen work that depends on data, financial models and recurring reports.
Investment Analysis
Clean market data and compare assets, portfolios and performance.
Risk Analytics
Calculate risk measures and test portfolio scenarios.
Finance Operations
Automate data checks, routine calculations and reporting workflows.
FinTech and Data Teams
Build reproducible datasets, visualisations and API-based pipelines.
The curriculum: 24 units, two levels, one integrated framework
Python for Finance and Automation Lab
Python for Finance and Automation Lab 71 Lessons 00:00:00
Chapter -1 Why-Python-for-Finance.pptx
3 Lessons
00:00:00 Hours
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E-book Why Python for Finance
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Why-Python-for-Finance.pptx
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Chapter-2 Core-Python-Data-Types-for-Financial-Data.pptx
3 Lessons
00:00:00 Hours
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E-book Core Python Data Types for Financial Data
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Core-Python-Data-Types-for-Financial-Data
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Chapter-3 Object-Oriented Programming for Finance.pptx
3 Lessons
00:00:00 Hours
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E-book Object-Oriented Programming for Finance
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Object-Oriented Programming for Finance.pptx
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Chapter- 4 Python Development Best Practices
3 Lessons
00:00:00 Hours
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E-book Python Development Best Practices
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Python Development Best Practices
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Chapter -5 Numerical Computing Numpy.pptx
3 Lessons
00:00:00 Hours
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E-book Numerical Computing with NumPy
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Numerical Computing Numpy.pptx
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Chapter-6 Data-Analysis-with-pandas.pptx
3 Lessons
00:00:00 Hours
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E- book Data Analysis with pandas
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Data-Analysis-with-pandas.pptx
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Chapter-7 Mathematical-and-Statistical-Tools.pptx
3 Lessons
00:00:00 Hours
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E-book Mathematical and Statistical Tools
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Mathematical-and-Statistical-Tools.pptx
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Chapter-8 Financial Time Series Analysis.pptx
3 Lessons
00:00:00 Hours
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E-book Financial Time Series Analysis
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Financial Time Series Analysis.pptx
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Chapter-9 Reading and Writing Financial Data Files.pptx
3 Lessons
00:00:00 Hours
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E-book Reading and Writing Financial Data Files
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Reading and Writing Financial Data Files.pptx
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Chapter-10 Data-Cleaning-and-Preprocessing.pptx
3 Lessons
00:00:00 Hours
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E-book Data Cleaning and Preprocessing
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Data-Cleaning-and-Preprocessing.pptx
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Chapter-11 Data-Transformation-and-Feature-Engineering.pptx
3 Lessons
00:00:00 Hours
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E-book Data Transformation and Feature Engineering
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Data-Transformation-and-Feature-Engineering.pptx
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Chapter - 12 Database and HDF5 Storage for Large Financial Datasets.pptx
3 Lessons
00:00:00 Hours
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E-book Database and HDF5 Storage for Large Financial Datasets
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Database and HDF5 Storage for Large Financial Datasets.pptx
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Chapter -13 Time-Value-of-Money-Calculators.pptx
3 Lessons
00:00:00 Hours
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E-book Time Value of Money Calculators
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Time-Value-of-Money-Calculators.pptx
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Chapter-14 Returns, Risk, and Performance Metrics.pptx
3 Lessons
00:00:00 Hours
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E-book Returns, Risk, and Performance Metrics
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Returns, Risk, and Performance Metrics.pptx
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Chapter-15 Stochastic Modelling And Monte Carlo Simulation.pptx
3 Lessons
00:00:00 Hours
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E-book Stochastic Modelling and Monte Carlo Simulation
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Stochastic Modelling And Monte Carlo Simulation.pptx
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Chapter-16 Options-and-Derivatives-Pricing.pptx
3 Lessons
00:00:00 Hours
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E-book Options and Derivatives Pricing
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Options-and-Derivatives-Pricing.pptx
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Chapter - 17 Portfolio-Construction-and-Return-Analysis.pptx
3 Lessons
00:00:00 Hours
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E-book Portfolio Construction and Return Analysis
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Portfolio-Construction-and-Return-Analysis.pptx
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Chapter-18 Mean-Variance Optimisation (Markowitz Framework).pptx
3 Lessons
00:00:00 Hours
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E-book Mean-Variance Optimisation (Markowitz Framework)
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Mean-Variance Optimisation (Markowitz Framework).pptx
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Chapter - 19 Risk-Management-and-Value-at-Risk.pptx
3 Lessons
00:00:00 Hours
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E-book Risk Management and Value-at-Risk
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Risk-Management-and-Value-at-Risk.pptx
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Chapter-20 Data Visualisation for Financial Analysis.pptx
3 Lessons
00:00:00 Hours
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E-book Data Visualisation for Financial Analysis
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Data Visualisation for Financial Analysis.pptx
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Chapter-21 Automation Fundamentals Scheduling and Scripting.pptx
3 Lessons
00:00:00 Hours
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E-book Automation Fundamentals Scheduling and Scripting
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Automation Fundamentals Scheduling and Scripting.pptx
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Chapter-22 Automated Financial Reporting.pptx
2 Lessons
00:00:00 Hours
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E-book Automated Financial Reporting
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Automated Financial Reporting.pptx
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Chapter 23- Web Scraping and API-Based Data Automation.pptx
3 Lessons
00:00:00 Hours
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E-book Web Scraping and API-Based Data Automation
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Web Scraping and API-Based Data Automation.pptx
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Chapter-24 Capstone Automation Project
3 Lessons
00:00:00 Hours
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E-book Capstone Automation Project
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Capstone Automation Project.pptx
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Frequently Asked Questions
The book begins with Python fundamentals and builds toward financial analysis and automation. Regular coding practice will be important.
The book covers NumPy, pandas, plotting tools, data files and databases, and tools for Excel reports, PDFs, web requests and APIs.
The book includes mini projects and practice assignments, such as a fund performance analyser, portfolio optimiser, risk analyser and portfolio dashboard, culminating in an automated portfolio report pipeline.
Yes. It includes return and performance metrics, Monte Carlo simulation, historical and parametric VaR, expected shortfall, stress testing and scenario analysis.
Yes. The book covers file and folder scripting, task scheduling, logs, Excel and PDF generation, APIs, and an end-to-end reporting capstone.
The supplied material describes an AAFM Python for Finance and Automation Lab certification. It does not specify an external examination format, passing score or contact hours; those details should be confirmed from the course offering.
Self-paced or live
◆Choose your Study Mode
Choose the study mode that works best for Python for Finance and Automation Lab. Your selected course access and applicable fees are shown below.
Study on your own schedule
₹11000
+ 18% GST
₹12980 payable today
- 24-chapter structured learning
- Python foundations
- Financial data analysis
- Portfolio and risk analytics
- APIs and visualisation
- Reporting automation
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Write the script. Validate the result. Automate the routine.
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