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Quant-AI Trading Lab powered by Quant Astra Pvt. Ltd.

Learn to trade
the right way.
From day one.

Skip the trial-and-error phase. Learn backtesting, validation, and systematic deployment — whether you’re a fresher, a struggling trader, or an experienced one ready to automate.

View course details View curriculum
Python for trading
Backtesting frameworks
Strategy validation
Live deployment
Risk management systems
Automation & algo trading
Market phase analysis
Quant strategy development
Python for trading
Backtesting frameworks
Strategy validation
Live deployment
Risk management systems
Automation & algo trading
Market phase analysis
Quant strategy development
Why this course

Most traders learn trading
the hardest possible way.

Trial and error. Real money. Emotional decisions. Years of losses before any clarity. This course reverses that process entirely — you build the evidence first, then trade.

Backtest before you risk money
Every strategy gets validated on historical data with realistic assumptions before a single rupee goes live. You trade with evidence, not hope.
Skip the 3-year learning curve
What takes most traders 3 years of painful trial and error to discover, this course condenses into a structured, systematic learning path.
Build systems, not instincts
Learn to replace gut decisions with data-driven systems. Your strategies become replicable, improvable, and automatable — not locked in your head.
Launching Soon

Quantitative Research
& Backtesting

This course is designed for aspiring traders, investors, and finance enthusiasts who want to learn how to build, test, and evaluate systematic trading strategies using Python. Starting with the fundamentals of Python programming, participants will gain hands-on experience in working with market data, creating trading logic, and performing data-driven strategy research through backtesting.

Prerequisites

No prior programming experience is required. Basic knowledge of financial markets is helpful but not mandatory.

Course Curriculum
MOD 01
Python Fundamentals
· Foundation
+
Python basics for trading applications
Data types, variables, and data structures
Loops, conditional statements, and functions
MOD 02
Working with Market Data
· Data handling
+
Importing and handling historical price data
Data cleaning and preprocessing
Understanding OHLCV data
MOD 03
Building Trading Strategies
· Strategy development
+
Developing rule-based trading systems
Implementing trading logic using Python
Practical examples and strategy development
MOD 04
Performance Analysis
· Evaluation
+
Understanding key backtesting metrics
Evaluating returns, drawdowns, win rate, and risk
Interpreting strategy performance
MOD 05
Strategy Backtesting
· Core skill
+
Testing strategies across multiple parameters
Comparing different configurations
Identifying robust trading systems
MOD 06
Data Visualization
· Presentation
+
Visualizing price action and trading signals
Plotting performance metrics
Presenting backtesting results effectively
Learning Outcome

By the end of this course, participants will be able to write Python code for trading applications, work with historical market data efficiently, build and test rule-based trading strategies, analyze and interpret backtesting results, and visualize strategy performance to support research and decision-making.

What you’ll learn to use

The professional trading tech stack

Every tool you learn in this course is used by professional quant traders. No toy examples — real tools, real data, real markets.

Language
Python 3.x
The primary language for all strategy development, backtesting, and automation in this course.
Data
Pandas & NumPy
Core libraries for price data manipulation, return calculation, and statistical analysis.
Backtesting
VectorBT
High-performance vectorised backtesting for rapid strategy iteration and parameter studies.
Data Source
NSE / Yahoo Finance
Indian market data from NSE directly and Yahoo Finance for historical OHLCV data.
Broker API
Zerodha Kite API
Live order execution, real-time market data feed, and position management via Python.
Broker API
Dhan
Alternative broker APIs for live trading with WebSocket real-time data support.
Visualisation
Plotly / Matplotlib
Interactive strategy performance charts, drawdown visualisation, and trade analysis plots.
The difference

How most traders learn
vs how you will.

The old way

×Open account, deposit money, start trading
×Learn by losing real capital
×Follow tips, signals, and YouTube gurus
×Trade on intuition and “chart feel”
×No idea if your strategy actually has an edge
×Panic when markets move against you
×Change strategy after every losing streak
×3–5 years of pain before any clarity

The Quant-Astra way

✓Backtest first, validate, then go live
✓Learn on historical data — zero capital at risk
✓Build your own edge based on your own data
✓Trade with rules your system follows automatically
✓Know your edge, its limits, and when it fails
✓Your risk system controls position size, not fear
✓Drawdowns are expected and planned for in advance
✓Structured path from idea to live systematic trading
What you’ll build

Graduate with real deliverables

The course ends with live projects you actually built — not certificates, not theory. Things you can deploy immediately.

01
A validated, bias-free backtest
A strategy backtest you can actually trust — walk-forward validated, bias-corrected, stress-tested with Monte Carlo, and phase-mapped across market conditions.
02
A working Python trading toolkit
A screener, alert system, pre-market script, trade logger, and performance dashboard — tools built in Python that you’ll actually use daily.
03
A live-deployed automated strategy
Your strategy connected to a broker API, running on a VPS, with real-time monitoring, automatic risk controls, and Telegram notifications. Running 24/7 without you.
04
A professional risk framework
A position sizing model, drawdown rules, daily loss limits, and a personal risk dashboard — all coded so your system enforces discipline automatically.
05
A strategy tearsheet
A professional performance report including Sharpe, Sortino, max drawdown, win rate, regime breakdown, and capacity analysis. The kind hedge funds use internally.
06
A research pipeline
A repeatable process for ideating, backtesting, validating, and deploying new strategies. So you never stop improving — even after the course ends.
Your Instructor
Shashank Khatri
Shashank Khatri
CEO @ Quant Astra
CFA Level III Cleared

8+ years building and deploying automated trading systems in Indian equity and derivatives markets.

What I Do

Live trading: Systematic options strategies, stock selection, derivatives execution
Systems: API-driven multi-broker execution frameworks using Python
Research: Quantitative analysis of market cycles, volatility behavior, greeks, and strategy robustness
Teaching: Courses in quantitative trading, systematic validation, and live strategy deployment

Why I Teach

“Most traders lose money not because they lack discipline—they lose because they lack clarity. Their backtests lie. Their strategies work in one phase and fail in another. They don’t know why.”

I created Quant AI Trading Lab to close this gap. Every trader deserves to understand the five hidden biases destroying their live returns. Every strategy deserves honest validation before live capital is deployed.

Credentials & Certifications

CFA Program: Level III cleared | 90+ percentile in Level II
EPAT Certificate: QuantInsti algorithmic trading (Python, backtesting, quantitative techniques)
NISM Series VIII: Equity derivatives certified
8 Years Trading: 3 years building automated systems | Active proprietary trader

Currently: Running proprietary trading desk + Training serious traders in systematic validation and deployment.

Launching Soon

Register your interest.

Quantitative Research & Backtesting is launching soon. Leave your details and we’ll notify you as soon as batch dates and seats open up.

Launching Soon
Quant Research Course
Quantitative Research & Backtesting
For aspiring traders, investors, and finance enthusiasts who want to build, test, and evaluate systematic trading strategies using Python.
✓6 structured modules
✓Python from the fundamentals
✓Hands-on market data & backtesting
✓Performance analysis & visualization
✓No prior programming experience required
Register interest →
Questions

Frequently asked questions

Do I need prior coding or trading experience?+
No prior programming experience is required — we start from Python fundamentals. Basic knowledge of financial markets is helpful but not mandatory.
Are the sessions live or pre-recorded?+
All sessions are live — you attend in real time, ask questions, and work on problems interactively. Recordings of every session are provided so you can revisit anything at any time. There is no pre-recorded-only option.
Which broker API will I learn to use?+
Primary focus is on Zerodha Kite API, which is the most widely used in India. We also cover Fyers and Upstox APIs. The concepts transfer to any broker API — once you learn one, the others follow the same patterns.
Will I actually deploy a live strategy by the end?+
Yes — that is the capstone of every track. You will have a validated strategy connected to a broker API, running on a VPS with monitoring and risk controls. The capstone is done on paper trading first, then you control when to switch to live capital.
How long is the course and what is the time commitment?+
The full course runs 10–14 weeks depending on the track. Sessions are typically 2–3 times per week. Expect 4–6 hours per week for sessions and project work. The pace is designed to fit around working hours — most students are employed or running businesses.
Is this focused on Indian markets specifically?+
Yes. All examples use NSE equities, NIFTY futures, and Indian options contracts. Broker API integrations are all India-focused (Zerodha, Fyers, Upstox). The regulatory context, taxes, and market microstructure are all Indian — not adapted from US courses.
Enroll now · Limited batch size

Stop learning trading
the expensive way. Start here.

Backtest first. Validate rigorously. Deploy with confidence. Whether you’re a fresher or a seasoned trader — this is the right starting point.

Call or WhatsApp to enquire & enroll
8076899852
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Quant AI Trading Lab  ·  Quant-Astra Pvt Limited  ·  From Data to Strategy
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