AI Trading Bot with Python: Machine Learning & Backtest 2026
Master AI Trading systems. Build a Python bot proven to scale from 1K to 4K in backtested market cycles.
Lo que serás capaz de hacer
Master AI Trading: Build a Production-Grade Machine Learning Bot Take your trading from intuition to automated science. This course provides a comprehensive, step-by-step framework for building a fully autonomous AI Trading Bot —moving from raw market data ingestion to high-performance execution on Binance or Kraken. IMPORTANT: This course treats trading as a Quantitative Science, not a game of chance. The Core Case Study: Engineering a 4x Return We don't just write code; we validate performance. Using a backtested starting capital of 1,000, we demonstrate how to scale a systematic account toward 4,000 using advanced Machine Learning models. This strategy is backed by institutional-grade metrics, ensuring that growth is driven by risk-adjusted logic, not luck. What you’ll learn: Ingest & Engineer Financial Data: Automate the collection, cleaning, and scaling of real-time 15-minute Bitcoin data for algorithmic use. Master Quantitative Preprocessing: Apply advanced time-series techniques, including stationarity testing and multi-dimensional feature engineering. Architect Deep Learning Models: Design and train high-performance AI Trading models using Conv1D and LSTM neural networks. Deploy Ensemble Strategies: Combine multiple predictive models to reduce variance and ensure more stable, robust performance in volatile markets. Build an Autonomous Trading Bot: Implement a production-grade Python system that executes real-time trades on major exchanges via API. Validate with Rigorous Backtesting: Evaluate your strategies using historical data to ensure high-probability outcomes before deploying capital. Optimize for Risk-Adjusted Returns: Understand the science of the Sharpe Ratio and drawdowns to turn trading into a systematic enterprise. Who this course is for: Software Engineers & Python Developers: Those looking to transition into Fintech or bridge the gap between backend engineering and quantitative finance. Quantitative Traders & Analysts: Professionals who want to evolve from manual or rule-based trading to autonomous, AI-driven systems. Data Science Professionals: Learners looking for a production-grade, end-to-end project that applies Deep Learning (LSTM/Conv1D) to volatile, real-world time-series data. Finance & Investment Professionals: Individuals seeking to understand the "Black Box" of AI Trading through a transparent, science-first approach. Computer Science Students: Anyone with a Python foundation who wants to build a portfolio-ready Automated Trading System. By the end of this course, you’ll have a working trading bot , a deep understanding of the machine learning pipeline for trading , and the confidence to experiment with your own ideas in crypto markets.
- Apply backtesting techniques to evaluate trading strategies, turning 1K into 4K
- Develop a fully automated trading bot that runs 24/7 on Binance or Kraken
- Go straight to the heart of Machine Learning by applying it directly to Bitcoin price prediction
- Implement a complete end-to-end Machine Learning pipeline
- Build and train deep learning models (Conv1D, LSTM, and hybrid architectures) to predict market movements
- Useful tips and tricks in Machine Learning to boost model performance
Temario
UNIDAD 1 - Introduction · 7 leccionesUNIDAD 1 - Introduction
UNIDAD 1 - Introduction
- Introduction
- Learning approach
- Setup Google Colab
- Understanding the dataset
- Stationary data
- Stationary data transformation
- Quiz #1
UNIDAD 2 - Preparing Data for Machine Learning · 2 leccionesUNIDAD 2 - Preparing Data for Machine Learning
UNIDAD 2 - Preparing Data for Machine Learning
- Preprocess data into train/test
- Quiz #2
UNIDAD 3 - Feedforward Neural Network · 6 leccionesUNIDAD 3 - Feedforward Neural Network
UNIDAD 3 - Feedforward Neural Network
- Neural Network fundamentals
- Loss function
- How a Neural Network learns
- Dot product
- Activation function
- Quiz #3
UNIDAD 4 - Building & Training Models in PyTorch · 12 leccionesUNIDAD 4 - Building & Training Models in PyTorch
UNIDAD 4 - Building & Training Models in PyTorch
- Build the model
- Build the model (part 2)
- Initializations
- Learning rate
- Batch size
- Train and test losses
- Epoch
- Create mini batches
- Training loop
- Test step
- Choosing Your Timeframe
- Quiz #4
UNIDAD 5 - Backtest (Trading simulation) · 7 leccionesUNIDAD 5 - Backtest (Trading simulation)
UNIDAD 5 - Backtest (Trading simulation)
- Backtest (part 1)
- Backtest (part 2)
- Add new features (to improve performance)
- Scale the data
- Reproducibility
- Save the training process
- Quiz #5
UNIDAD 6 - Advanced Model Architectures · 8 leccionesUNIDAD 6 - Advanced Model Architectures
UNIDAD 6 - Advanced Model Architectures
- Convolutional Neural Networks (Conv1D theory)
- Conv1D implementation with PyTorch (code & training)
- LSTM theory
- LSTM implementation with PyTorch (code & training)
- Avoiding CUDA Out-of-Memory Errors in LSTM Forward Propagation
- Ensemble method (part 1)
- Ensemble method (part 2)
- Quiz #6
UNIDAD 7 - Core Trading Concepts Every Bot Developer Must Know · 2 leccionesUNIDAD 7 - Core Trading Concepts Every Bot Developer Must Know
UNIDAD 7 - Core Trading Concepts Every Bot Developer Must Know
- Order Execution Mechanics Explained
- Trading Fees and Cost Structure
UNIDAD 8 - Trading Bot · 19 leccionesUNIDAD 8 - Trading Bot
UNIDAD 8 - Trading Bot
- Trading Bot Workflow
- Start coding
- Loading scalers file
- Loading models file
- Binance Futures Trading Bot - Part 1
- Binance Futures Trading Bot - Part 2
- Binance Futures Trading Bot - Part 3
- Futures trading bot on Binance - Finished
- Testing and Running the Bot live
- Margin trading bot on Binance - Part 1
- Margin trading bot on Binance - Part 2
- Margin trading bot on Binance - Part 3
- Margin trading bot on Binance - Part 4
- Margin trading bot on Binance - Finished
- Margin Trading Bot on Kraken
- Quiz #7
- How to Download Historical Data for Any Coin
- What Happens If We Change the Interval from 15 Minutes to 1 Hour (or Longer)?
- Binance vs Kraken — Which Crypto Exchange Is Better?
UNIDAD 9 - Risk Management in Algorithmic Trading · 3 leccionesUNIDAD 9 - Risk Management in Algorithmic Trading
UNIDAD 9 - Risk Management in Algorithmic Trading
- Stop-Loss: Theory and Core Concepts
- Implementing Stop-Loss in Backtesting
- Implementing Stop-Loss in the Live Trading Bot
Tu certificado lo emite la SEP, no solo una plataforma
Al demostrar la competencia recibes un certificado emitido por la Secretaría de Educación Pública a través del Gobierno del Estado de México: un documento oficial que puedes presentar con confianza ante cualquier empleador o institución.
Tu certificado con INEC
- Lo emite la Secretaría de Educación Pública (SEP), a través del Gobierno del Estado de México
- Documento oficial con folio verificable en línea
- Lo otorga la Universidad Tecnológica Fidel Velázquez
Otras plataformas en línea
- Constancia privada emitida por la misma plataforma
- Solo acredita horas cursadas o asistencia
- Sin respaldo de una autoridad educativa
Tu itinerario, de la inscripción al certificado
- 1
Inscripción con pago único
Pagas $2,800 MXN una sola vez y entras de inmediato al curso.
- 2
Estudias a tu ritmo
9 unidades con videos, lecturas y actividades, disponibles 24/7 durante 12 meses.
- 3
Cuestionarios por unidad
7 cuestionarios para comprobar lo aprendido.
- 4
Certificado
Emitido por la SEP a través del Gobierno del Estado de México, con folio verificable.
Un certificado oficial de la SEP
Muestra · verificable por folio y QR
- Emitido por la Secretaría de Educación Pública (SEP), a través del Gobierno del Estado de México. No es una constancia privada: es un documento oficial, y ese respaldo marca la diferencia frente a otras plataformas en línea.
- Contenido impartido por The Inspiring Trader.
- Folio y QR verificables para compartirlo con quien te contrate.
Empieza hoy, a tu ritmo
Un solo pago y acceso inmediato al curso completo durante 12 meses.
- 9 unidades · 66 lecciones · 45 h
- 12 meses de acceso
- 7 cuestionarios de evaluación
- Certificado emitido por la SEP (Gob. del Estado de México) con folio verificable
Sobre tu inscripción
¿Cómo es el pago?
Un solo pago de $2,800 MXN. No hay mensualidades ni cargos recurrentes.
¿Cuánto tiempo tengo acceso?
12 meses desde tu inscripción, 24/7, para avanzar a tu ritmo.
¿Quién imparte el contenido?
El curso es impartido por The Inspiring Trader; INEC gestiona tu inscripción, evaluación y certificado.
¿Qué pasa cuando vence mi acceso?
Puedes renovar tu cuenta tú mismo desde la plataforma, sin trámites ni esperas.
