Start Here
Welcome to QuantML.
This isn’t just another AI blog. I’m building a complete, hands-on learning platform for finance professionals who want to move beyond spreadsheets and start building real automations, models, and tools — using Python, machine learning, and large language models (LLMs).
Whether you're in FP&A, consulting, asset management, or you're just tired of manually dragging formulas in Excel — this course is for you.
This is a project for finance professionals who want to ditch repetitive work, stop dragging Excel formulas, and start building with Python, machine learning, and automation tools like GPT. and Look cool in office. Your manager likes you and ask you to PUT AI to the work 😀
I’m building a complete AI + ML in Finance course — topic by topic — and sharing everything here on QuantML. This page is your roadmap.
🧠 What You’ll Learn
You’ll go from:
“I kinda know Excel”
to
“I built a forecasting model and automated my monthly P&L reporting”
This course is hands-on, practical, and finance-specific. You’ll learn how to:
Clean and analyze messy financial data with Python
Automate reports, dashboards, and business reviews
Forecast revenue using machine learning
Analyze stock market data and test quant strategies
Build GPT-powered financial tools (no fluff — real use cases)
🧱 How It Works
This is a work-in-progress master course, and I'm building it module by module — in public.
Each module will include:
🧪 A step-by-step tutorial
💻 Live code in Python (Jupyter or Colab)
📹 (Optional) YouTube walkthrough
🧰 Practical projects with real data
I'll release new modules weekly. You can start from the top and work your way down — or just jump into what’s most relevant.
🎓 Who This Is For
This course is for:
FP&A professionals and Finance consultants
ERP and EPM Consultants
CFA, MBA, and finance students
Business analysts, Excel power users, and data-curious folks
Anyone who’s ever said “There has to be a better way to do this…”
🔗 Current Modules Available
✅ Module 0 – Setup & Orientation
Python, Jupyter/Colab setup, GitHub basics
✅ Module 1 – Python Basics for Finance
Variables, functions, CSV/Excel handling, pandas essentials
✅ Module 2 – Financial Analysis with Python
Ratio analysis, CAGR, pivot tables, automated dashboards
✅ Module 3 – Data Visualization & Reporting
Matplotlib, Seaborn, Streamlit, exporting dashboards
🟡 Module 4 – Machine Learning for Forecasting (in progress)
Linear regression, risk scoring, sales forecasts
🔜 Upcoming Modules (Releasing Weekly)
Module 5: Time Series Forecasting (ARIMA, Prophet, revenue prediction)
Module 6: Indian Stock Market (NSE data, sentiment, screeners)
Module 7: GPT + LLMs in Finance (commentary generation, analysis automation)
Module 8: AI for FP&A (automated reporting, rolling forecasts, GPT commentary)
Module 9: ML Use Cases (churn, fraud, pricing)
Module 10: Automation & Streamlit Apps
Module 11: Advanced Quant/ML (backtesting, simulations)
Module 12: Capstone Project
🧠 Elective Tracks (Coming Soon)
ERP & BI Integration: Python + SAP/Oracle/Tableau automation
Behavioral Finance + NLP: Reddit/forum scraping + anomaly detection
Resume Booster Projects: Build a portfolio that actually impresses recruiters
👇 Get Started
Subscribe to get updates when new lessons go live.
You’ll also get real-world finance automations, code samples, and GPT tools — straight to your inbox.
Or, if you’re the type who scrolls LinkedIn during meetings:
Follow on X • Watch on YouTube • Connect on LinkedIn
Written and built by Krishna Singh — finance pro, AI nerd, and the human behind QuantML.