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Free Download Udemy - Stock Fundamentals And Portfolio Optimization App
Published: 3/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.30 GB | Duration: 4h 51m
Stock Analysis & Portfolio Optimization - Ratios, Screeners & Forecasting

What you'll learn
Analyze key financial ratios such as Debt to Equity, ROE, and PE Ratio for stock evaluation.
Build a stock screener by extracting and processing company financial data
Conduct market analysis using market cap, risk distribution, and sector-based analysis.
Implement portfolio optimization techniques for better investment decisions.
Train and evaluate machine learning models for stock selection and classification.
Apply deep learning (LSTM) for stock price forecasting and trend prediction.
Requirements
Python knowledge for Implementation
Description
Are you looking to master stock fundamentals and build a data-driven portfolio optimization app? This course, Stock Fundamentals and Portfolio Optimization App, is designed to help you analyze financial ratios, screen stocks, and apply machine learning models for stock selection and forecasting.Starting with key financial ratios such as Debt to Equity, ROE, PE Ratio, and Interest Coverage, you'll learn how to evaluate a company's financial health. You'll then progress to developing a stock screener, where you'll extract company financials, perform data cleaning, and integrate key financial metrics.The capstone project will guide you through building an end-to-end portfolio optimization application. You'll work with daily market data, perform exploratory data analysis (EDA), and filter relevant stocks using Python. Advanced topics include market cap analysis, risk rating distributions, and stock selection techniques.To enhance decision-making, the course covers data visualization techniques for understanding financial trends. You will also implement feature engineering and one-hot encoding to refine stock data before applying machine learning models. Classifier models, SHAP-based feature importance, and ROC curve evaluations will be used to select the best predictive models.Finally, you'll explore deep learning-based stock forecasting with LSTMs, helping you predict market trends and stock movements. By the end of this course, you'll have the skills to analyze stocks, optimize portfolios, and make data-driven investment decisions using Python. Whether you're a beginner or an experienced trader, this course will equip you with the tools needed to leverage data science for financial success.
Beginner to Intermediate Investors - If you are new to stock markets or want to improve your ability to analyze financial statements and ratios, this course will provide structured, hands-on learning.,Finance Professionals & Analysts - Enhance your skill set by integrating data-driven stock screening, market analysis, and risk assessment into your workflow.,Data Scientists & Machine Learning Enthusiasts - Learn how to apply ML models for stock selection, feature importance analysis, and stock price forecasting using financial data.,Students & Academics - If you're studying finance, economics, or data science, this course will help you understand how to apply quantitative techniques for investment strategies.,Algorithmic Traders & Quantitative Analysts - Gain insights into data preprocessing, financial data extraction, and predictive modeling for smarter trading decisions.,Python Developers Interested in Finance - If you have programming experience and want to explore financial data analytics and portfolio management, this course will teach you practical implementation techniques.

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