PROJECT / 01
NIFTY VWAP Trading Bot
Build a rule-based intraday trading system, backtest it on historical data and analyze its performance.
PythonBacktestVWAPIndian Markets
Learn to build production trading systems
BUILD. BACKTEST. AUTOMATE.
Learn how to turn your trading ideas into automated trading systems — from strategy development and backtesting to API integration and live deployment.
Python · APIs · Docker · Cloud· Practical projects, not just theory
Trading IdeaInsight
StrategyRules
PythonCode
BacktestingValidate
Broker APIConnect
Trading BotExecute
CloudDeploy
Positioning
Learn by Building Real Systems
This isn't another course of slides and screencasts. Every module is a system you build, break, fix and understand — the same way engineers ship production software. You leave with working code, running deployments and a mental model that transfers to whatever you build next.
Strategy developmentPythonMarket dataBacktestingRisk managementBroker APIsAutomationDockerCloud deploymentMonitoring
bot.py — vwap-strategy — live
$ python bot.py --backtest --symbol NIFTY --tf 5m
[DATA] loaded 1,240 candles — 2024-01-02 → 2024-12-31
[STRAT] rule: enter long when price > vwap and rsi < 65
[RISK] stop = 0.8% · target = 1.6% · max trades/day = 3
[RUN] simulating trades...
✔ backtest complete · win_rate=54% · pf=1.31 · maxdd=6.2%
[EXPORT] wrote reports/backtest_2025.html
$ ▍
Curriculum
What You Will Learn
Nine focused modules that take you from a trading idea to a monitored, deployed system running in the cloud.
01
Strategy Development
Turn a trading idea into clearly defined rules.
02
Market Data
Understand candles, indicators, APIs and historical market data.
03
Backtesting
Test strategies against historical data before considering deployment.
04
Python
Build trading logic and automation using Python.
05
Broker APIs
Connect strategies to trading platforms and APIs.
06
Automation
Build systems that can monitor markets and execute predefined rules.
07
Deployment
Deploy trading systems to cloud servers such as AWS EC2.
08
Monitoring
Monitor bots, logs, errors and system health.
Hands-on
Build Real Projects
You don't learn systems by watching them. You learn them by shipping them — one project at a time.
PROJECT / 02
Trading Signal Bot
Build a system that processes trading signals and sends automated alerts through Telegram.
TelegramWebhooksSignalsAutomation
PROJECT / 03
Crypto Trading Bot
Connect a trading strategy to exchange APIs and build an automated execution workflow.
Binance APIRESTAsyncOrder Management
PROJECT / 04
Cloud Trading System
Deploy a trading application using Docker and AWS EC2 with monitoring and automated processes.
DockerAWS EC2SystemdLogs
Roadmap
From Idea to Deployed System
A structured path — nine focused steps that stack on each other. Each step is deliberate; nothing is filler.
- STEP 01
Trading Strategy
Define rules, entries, exits and risk parameters before writing a single line of code.
- STEP 02
Data
Fetch historical and live market data via APIs. Understand candles, ticks and timeframes.
- STEP 03
Python
Structure your codebase, use libraries like pandas and numpy, and prepare for automation.
- STEP 04
Backtesting
Simulate strategies on historical data. Track PnL, drawdown, win-rate and edge decay.
- STEP 05
Risk Management
Position sizing, stop-losses, daily loss caps and circuit-breakers — the boring but critical layer.
- STEP 06
API Integration
Connect to broker or exchange APIs. Handle auth, rate limits, order lifecycle and reconciliation.
- STEP 07
Automation
Turn scripts into event-driven services that monitor markets and respond in real time.
- STEP 08
Deployment
Containerize with Docker. Deploy to AWS EC2. Configure systemd, logs and restart policies.
- STEP 09
Monitoring
Health checks, dead-man alerts, drift monitors and clean shutdowns. Sleep better at night.
Live Workshop
Learn to Build Your First Trading Bot
A practical live workshop where we go from trading idea to working automated system. You'll leave with running code and a clear picture of the full stack.
- Live instruction
- Practical coding
- Strategy development
- Backtesting
- API integration
- Q&A
- Course resources
Reserve a seatLimited seats
₹999/ seat
Includes live session, working code and follow-up resources.
Reserve Your SeatPayment gateway integration is being prepared. For now, register your interest and we'll email you the payment link.
Program
Algorithmic Trading & Bot Building
A structured program that walks you through the full stack, one module at a time.
Full Course
Coming soonAlgorithmic Trading & Bot Building
Everything the workshop covers, plus deep-dives on backtesting frameworks, order management, monitoring and deployment.
MODULE 01Strategy development
MODULE 02Python for trading
MODULE 03Market data
MODULE 04Backtesting
MODULE 05Broker APIs
MODULE 06Automation
MODULE 07Deployment
MODULE 08Monitoring
View Course
Pricing and enrolment details will be announced with launch.
Teaching philosophy
Why Learn Here
A short list of ideas we take seriously. If any of these resonate, this program will feel like home.
01
Build instead of just watching.
Every module ends with something you actually ship — not another lecture to nod along to.
02
Understand the system behind the strategy.
Strategies live inside systems: data pipes, order flows, retries, monitors. You'll see all of it.
03
Backtest before deploying.
We treat backtests as evidence, not marketing. You'll learn where they lie and where they help.
04
Learn the technology stack.
Python, APIs, Docker, systemd, cloud. The same tools engineers use to run production software.
05
Deploy and monitor real systems.
A strategy on your laptop isn't a system. You'll deploy, watch it live, and fix things when they break.
06
Focus on process, not promises.
No performance guarantees. Just the practice of turning ideas into testable, deployable systems.
AW
PHOTO PLACEHOLDER
instructor · available
About the InstructorPractitioner first.
Practitioner first.
Teacher second.
I've spent years building trading and automation systems — from backtesting frameworks and broker integrations to deployment pipelines and monitoring stacks. This program distils that experience into a practical curriculum that meets you where you are and takes you to a system you actually understand.
Focus areas
FinanceAutomationPythonTrading systemsData analysisCloud deployment
Questions
Frequently Asked
Straight answers. Nothing dressed up.
Some familiarity with any programming language helps, but the course starts from Python basics and builds up. If you can write a small script, you can follow along.
Yes. The material is designed for people new to algorithmic trading and to trading automation. We go slowly through the fundamentals before touching live systems.
Not to complete the coursework. Most projects run on historical data or exchange sandboxes. A live account is only needed if you choose to deploy a real bot later.
Yes. Every project includes reference code, sample datasets and step-by-step build notes so you can reproduce and extend the projects yourself.
Yes. We cover concepts that apply to Indian equity and derivative markets, including how to connect to broker APIs commonly used in India.
Yes. A full module walks through packaging a bot with Docker and deploying it to AWS EC2 with logs, monitoring and automatic restarts.
No. The course teaches technology, strategy development, backtesting and automation. Trading involves risk and no strategy or system can guarantee profits.
Your Trading Idea Could Be Your Next Automation Project.
Learn the technology needed to turn systematic trading ideas into testable and deployable systems.