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From 1K To 4K Build A Bitcoin Trading Bot With Python - Printable Version +- Nice1 Community Forum (https://talk.nice1.org) +-- Forum: Nice1 Community (https://talk.nice1.org/forumdisplay.php?fid=3) +--- Forum: Media (https://talk.nice1.org/forumdisplay.php?fid=9) +--- Thread: From 1K To 4K Build A Bitcoin Trading Bot With Python (/showthread.php?tid=614) |
From 1K To 4K Build A Bitcoin Trading Bot With Python - Courses2025 - 09-19-2025 ![]() Free Download From 1K To 4K: Build A Bitcoin Trading Bot With Python Published 9/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 920.04 MB | Duration: 3h 9m A hands-on guide to data, machine learning, and trading bot development with real results. What you'll learn Understand how to prepare and engineer features from raw market data to make it suitable for machine learning models Build and train deep learning models (Conv1D, LSTM, and hybrid architectures) to predict market movements Apply backtesting techniques to evaluate trading strategies and measure risk/reward performance Develop a fully automated trading bot that runs 24/7 on Binance Futures Gain hands-on experience turning a $1,000 backtest into $4,000 equity, learning how to scale strategies responsibly Requirements Basic Python knowledge (for example: writing simple loops, functions, and classes) No prior experience in machine learning or trading required A computer with an internet connection (Windows, Mac, or Linux) Description Do you want to build your own AI-powered Bitcoin trading bot from scratch?This course takes you step by step from raw market data all the way to a fully automated trading system running on real-time data.Starting with 1,000 USD, our goal is to grow the account toward 4,000 USD (Sharpe Ratio: 4.91 annualized, 0.0316 unannualized) using deep learning and systematic trading strategies. Along the way, you'll gain practical experience in Python, data preprocessing, Conv1D, LSTM, ensembling methods, and backtesting.What you'll learn:Collect, clean, and scale real 15-minute Bitcoin dataUnderstand stationarity, feature engineering, and time series preprocessingBuild predictive models using Conv1D and LSTMEnsemble multiple models for more stable performanceDesign and implement a live trading bot that runs every 15 minutesBacktest strategies to evaluate performance before going liveWho this course is for ython developers who want to apply their skills in trading and financeTraders who want to upgrade to systematic, AI-driven approachesData science and machine learning learners looking for a real-world projectAnyone curious about how AI can be applied in cryptocurrency tradingBy 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.Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Learning approach Lecture 3 Setup Google Colab Lecture 4 Understanding the dataset Lecture 5 Stationary data Lecture 6 Stationary data transformation Section 2: Preparing Data for Machine Learning Lecture 7 Preprocess data into train/test Section 3: Feedforward Neural Network Lecture 8 Neural Network fundamentals Lecture 9 Loss function Lecture 10 How a Neural Network learns Lecture 11 Dot product Lecture 12 Activation function Section 4: Building & Training Models in PyTorch Lecture 13 Build the model Lecture 14 Build the model (part 2) Lecture 15 Initializations Lecture 16 Learning rate Lecture 17 Batch size Lecture 18 Train and test losses Lecture 19 Epoch Lecture 20 Create mini batches Lecture 21 Training loop Lecture 22 Test step Section 5: Backtest (Trading simulation) Lecture 23 Backtest (part 1) Lecture 24 Backtest (part 2) Lecture 25 Add new features (to improve performance) Lecture 26 Scale the data Lecture 27 Reproducibility Lecture 28 Save the training process Section 6: Advanced Model Architectures Lecture 29 Convolutional Neural Networks (Conv1D theory) Lecture 30 Conv1D implementation in PyTorch (code & training) Lecture 31 LSTM theory Lecture 32 LSTM implementation in PyTorch (code & training) Lecture 33 Ensemble method (part 1) Lecture 34 Ensemble method (part 2) Section 7: Trading Bot Lecture 35 Introduction to trading bot Lecture 36 Loading scalers file Lecture 37 Loading models file Lecture 38 bot.py (part 1) Lecture 39 bot.py (part 2) Lecture 40 bot.py (part 3) Lecture 41 Launch the trading bot Beginners in machine learning who want to apply AI to real-world finance,Aspiring algorithmic traders who want to build their own trading bot from scratch,Python learners who want a practical project that goes beyond theory,Anyone curious about how to use AI in financial markets - from data preprocessing to live trading,Traders who want to move from manual strategies to automated, AI-driven systems Homepage Code: https://www.udemy.com/course/from-1k-to-4k-build-a-bitcoin-trading-bot-with-python/Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live | FileHost -> Rapidgator | Rapidgator Recommend Download Link fyezj.From.1K.To.4K..Build.A.Bitcoin.Trading.Bot.With.Python.rar.html fyezj.From.1K.To.4K..Build.A.Bitcoin.Trading.Bot.With.Python.rar.html FreeDL fyezj.From.1K.To.4K..Build.A.Bitcoin.Trading.Bot.With.Python.rar.html No Password - Links are Interchangeable |