Mathew K AnalyticsFinance and Stock Market Analytics
A free 16-lesson course. Every lesson has a video walkthrough and a Jupyter notebook you can download or open in Google Colab; 4 lessons include real datasets. Tools covered: pandas, yfinance, NumPy, Matplotlib, datetime, seaborn.
23 minLesson 1
Introduction to Technical Analysis for Finance and Stock Market Analytics
35 minLesson 2
Understanding Financial Markets and Instruments: Key Concepts and Analytics
24 minLesson 3
Types of Financial Data: OHLCV, Fundamentals, and Sentiment Explained
26 minLesson 4
Financial Analytics Workflow Using Python: Step-by-Step Training for Beginners
24 minLesson 8
Numerical Analysis with NumPy for Financial Data: Training and Applications
20 minLesson 9
Introduction to Pandas for Stock Data Analysis
24 minLesson 11
Structure of Stock Market Datasets for Analytical Training
24 minLesson 12
Understanding OHLCV Data in Finance: Open, High, Low, Close, and Volume Explained
23 minLesson 15
Assessing Financial Data Quality: Techniques and Best Practices for Accurate Analysis
23 minLesson 20
Preparing Clean Financial Datasets for Analysis: Step-by-Step Data Cleaning Guide
25 minLesson 44
Scheduling Financial Data Updates for Automated Analytics
23 minLesson 46
Introduction to Time Series in Finance: Key Concepts and Applications
28 minLesson 49
Moving Averages and Smoothing Techniques in Stock Market Analysis
23 minLesson 50
Seasonal Patterns in Financial Markets: Understanding Recurring Trends
22 minLesson 57
Designing Financial Analytics Dashboards: Principles, Tools, and Best Practices
28 minLesson 60