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Financial Engineering and Artificial Intelligence in Python

#artificialintelligence

Preview this course - GET COUPON CODE Have you ever thought about what would happen if you combined the power of machine learning and artificial intelligence with financial engineering? Today, you can stop imagining, and start doing. This course will teach you the core fundamentals of financial engineering, with a machine learning twist. We will cover must-know topics in financial engineering, such as: Exploratory data analysis, significance testing, correlations, alpha and beta Time series analysis, simple moving average, exponentially-weighted moving average Holt-Winters exponential smoothing model Efficient Market Hypothesis Random Walk Hypothesis Time series forecasting ("stock price prediction") Modern portfolio theory Efficient frontier / Markowitz bullet Mean-variance optimization Maximizing the Sharpe ratio Convex optimization with Linear Programming and Quadratic Programming Capital Asset Pricing Model (CAPM) Algorithmic trading (VIP only) Statistical Factor Models (VIP only) Regime Detection with Hidden Markov Models (VIP only) In addition, we will look at various non-traditional techniques which stem purely from the field of machine learning and artificial intelligence, such as: Classification models Unsupervised learning Reinforcement learning and Q-learning ***VIP-only sections (get it while it lasts!) You will learn exactly why their methodology is fundamentally flawed and why their results are complete nonsense.


Financial Engineering and Artificial Intelligence in Python

#artificialintelligence

Have you ever thought about what would happen if you combined the power of machine learning and artificial intelligence with financial engineering? Today, you can stop imagining, and start doing. This course will teach you the core fundamentals of financial engineering, with a machine learning twist. We will learn about the greatest flub made in the past decade by marketers posing as "machine learning experts" who promise to teach unsuspecting students how to "predict stock prices with LSTMs". You will learn exactly why their methodology is fundamentally flawed and why their results are complete nonsense.


Financial Engineering and Artificial Intelligence in Python

#artificialintelligence

Have you ever thought about what would happen if you combined the power of machine learning and artificial intelligence with financial engineering? Today, you can stop imagining, and start doing. This course will teach you the core fundamentals of financial engineering, with a machine learning twist. We will learn about the greatest flub made in the past decade by marketers posing as "machine learning experts" who promise to teach unsuspecting students how to "predict stock prices with LSTMs". You will learn exactly why their methodology is fundamentally flawed and why their results are complete nonsense.


Financial Engineering and Artificial Intelligence in Python

#artificialintelligence

Financial Engineering and Artificial Intelligence in Python Getting Started Financial Analysis, Time Series Analysis, Portfolio Optimization, CAPM, Algorithmic Trading, Q-Learning, and MORE! Get Udemy Course New What you'll learn Forecasting stock prices and stock returns Time series analysis Holt-Winters exponential smoothing model Efficient Market Hypothesis Random Walk Hypothesis Exploratory data analysis Distributions and correlations of stock returns Modern portfolio theory Mean-Variance Optimization Efficient frontier, Sharpe ratio, Tangency portfolio CAPM (Capital Asset Pricing Model) Q-Learning for Algorithmic Trading Have you ever thought about what would happen if you combined the power of machine learning and artificial intelligence with financial engineering? Today, you can stop imagining, and start doing. This course will teach you the core fundamentals of financial engineering, with a machine learning twist. We will cover must-know topics in financial engineering, such as: Exploratory data analysis, significance testing, correlations, alpha and beta Time series analysis, simple moving average, exponentially-weighted moving average Holt-Winters exponential smoothing model Efficient Market Hypothesis Random Walk Hypothesis Time series forecasting ("stock price prediction") Modern portfolio theory Efficient frontier / Markowitz bullet Mean-variance optimization Maximizing the Sharpe ratio Convex optimization with Linear Programming and Quadratic Programming Capital Asset Pricing Model (CAPM) In addition, we will look at various non-traditional techniques which stem purely from the field of machine learning and artificial intelligence, such as: Have you ever thought about what would happen if you combined the power of machine learning and artificial intelligence with financial engineering?


Python & Machine Learning for Financial Analysis

#artificialintelligence

Python & Machine Learning for Financial Analysis - Master Python Programming Fundamentals and Harness the Power of ML to Solve Real-World Practical Applications in Finance Created by Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, Mitchell BouchardPreview this Course - GET COUPON CODE Are you ready to learn python programming fundamentals and directly apply them to solve real world applications in Finance and Banking? If the answer is yes, then welcome to the "The Complete Python and Machine Learning for Financial Analysis" course in which you will learn everything you need to develop practical real-world finance/banking applications in Python! Python is ranked as the number one programming language to learn in 2020, here are 6 reasons you need to learn Python right now! 1. #1 language for AI & Machine Learning: Python is the #1 programming language for machine learning and artificial intelligence. This course is unique in many ways: 1. The course is divided into 3 main parts covering python programming fundamentals, financial analysis in Python and AI/ML application in Finance/Banking Industry.