Python Quantitative Finance & Stock Analysis Course (Pandas, NumPy, SciPy) 🐍
Master Python for Stock Analytics: From Data Download to Custom Analysis Tools
5.0
(1)
14 learners
What you'll learn
- Analyze and filter stock data using Python and Pandas.
- Download and manage historical stock data in CSV format.
- Visualize stock performance with plots and correlation matrices.
- Create and install a custom stock analysis library with Python.
This course includes
- 1.5 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 15 lessons • 1.5 hours of video
Comprehensive Python Finance: Stock Analysis & Visualization
15 lessons
• 1.5 hours
Comprehensive Python Finance: Stock Analysis & Visualization
15 lessons
• 1.5 hours
- **Python Stock Tickers: Download ALL Exchange Data (API to Pandas DataFrame) Part 1** 🐍 05:34
- Python Data Curation: Filter Stock Tickers by S&P 500 & Sector with Pandas | Part 2 📊 06:53
- Python Download Historical Stock Data & Save to CSV (eod Library & Pandas) | Part 3 💾 11:25
- Python Aggregate Stock Data: Combine Multiple Price CSV Files into One Pandas DataFrame | Part 4 🛠️ 06:44
- Python Financial Analysis: Returns, Correlation Matrix, & Performance Plots | Part 5 📈 07:21
- Python: Calculate Stock Returns & Save to Multi-Sheet Excel File (Pandas) | Part 6 📊 05:25
- Python Matplotlib: Plot Performance Grid of Multiple Stocks with Dynamic Subplots | Part 7 🖼️ 04:35
- Python Financial Events: Find Stocks Announcing Earnings or Dividends (EOD API) | Part 8 📅 05:37
- Python Stock Screener: Calculate Close to 52-Week High Ratio (EOD API & Pandas) | Part 9 🔎 07:37
- Python OOP for Finance: Building a Stock Analysis Class to Manage Individual Securities | Part 10 🛠️ 07:03
- Python Class: Calculate Log Returns, Rolling Volatility, & Plot Distribution | Part 11 📊 05:06
- Python Matplotlib: Visualize Returns, Volatility Scatter, & Relative Performance | Part 12 📈 05:05
- Python Pandas: Filter Time Series Data by Option Expiration & Low Volatility Duration | Part 13 📅 06:02
- Python Package Guide: Create, Publish & Install a Custom Stock Analysis Library with Pip | Part 14 📦 10:57
- Basic Monte Carlo Simulation of a Stock Portfolio || Python Programming 13:57
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