

Udacity - Artificial Intelligence for Trading nd880 v1.0.0

WEBRip | English | MP4 | 1280 x 720 | AVC ~170 Kbps | 30 fps

AAC | 126 Kbps | 44.1 KHz | 2 channels | 39:34:27 | 7.32 GB

Genre: Video Tutorial WEBRip | English | MP4 | 1280 x 720 | AVC ~170 Kbps | 30 fpsAAC | 126 Kbps | 44.1 KHz | 2 channels | 39:34:27 | 7.32 GBGenre: Video Tutorial

https://www.udacity.com/course/ai-for-trading--nd880

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In this program, you’ll analyze real data and build financial models for trading. Whether you want to pursue a new job in finance, launch yourself on the path to a quant trading career, or master the latest AI applications in quantitative finance, this program offers you the opportunity to master valuable data and AI skills.01 - Welcome to the Nanodegree Program02 - Get Help from Peers and Mentors03 - Get Help with Your Account04 - Stock Prices05 - Market Mechanics06 - Data Processing07 - Stock Returns08 - Momentum Trading09 - Project 1 Trading with Momentum01 - Quant Workflow02 - Outliers and Filtering03 - Regression04 - Time Series Modeling05 - Volatility06 - Pairs Trading and Mean Reversion07 - Project 2 Breakout Strategy01 - Stocks, Indices, Funds02 - ETFs03 - Portfolio Risk and Return04 - Portfolio Optimization05 - Project 3 Smart Beta and Portfolio Optimization01 - Factors02 - Factor Models and Types of Factors03 - Risk Factor Models04 - Time Series and Cross Sectional Risk Models05 - Risk Factor Models with PCA06 - Alpha Factors07 - Alpha Factor Research Methods08 - Advanced Portfolio Optimization09 - Project 4 Alpha Research and Factor Modeling02 - Intro to Natural Language Processing03 - Text Processing04 - Feature Extraction05 - Financial Statements06 - Basic NLP Analysis07 - Project 5 NLP on Financial Statements01 - Introduction to Neural Networks02 - Training Neural Networks03 - Deep Learning with PyTorch04 - Recurrent Neural Networks05 - Embeddings Word2Vec06 - Sentiment Prediction RNN07 - Project 6 Sentiment Analysis with Neural Networks01 - Overview02 - Decision Trees03 - Model Testing and Evaluation04 - Random Forests05 - Feature Engineering06 - Overlapping Labels07 - Feature Importance08 - Project 7 Combining Signals for Enhanced Alpha01 - Strengthen Your Online Presence Using LinkedIn02 - Optimize Your GitHub Profile01 - Intro to Backtesting02 - Optimization with Transaction Costs03 - Attribution04 - Project 8 Backtesting01 - Why Python Programming02 - Data Types and Operators03 - Control Flow04 - Functions05 - Scripting01 - Introduction02 - Vectors03 - Linear Combination04 - Linear Transformation and Matrices01 - Jupyter Notebooks02 - NumPy03 - Pandas01 - Descriptive Statistics - Part I02 - Descriptive Statistics - Part II03 - Admissions Case Study04 - Probability05 - Binomial Distribution06 - Conditional Probability07 - Bayes Rule08 - Python Probability Practice09 - Normal Distribution Theory10 - Sampling distributions and the Central Limit Theorem11 - Confidence Intervals12 - Hypothesis Testing13 - Case Study AB tests01 - Linear Regression02 - Naive Bayes03 - Clustering04 - Decision Trees05 - Introduction to Kalman Filters01 - Introduction to Neural Networks01 - Intro to Computer Vision01 - Intro to NLPHOmepage:Extract files with WinRar 5 or Latest !