Explore comprehensive technical tutorials, programming guides, and insights from live coding sessions. Learn Python, data science, and modern web development.
Compare Python's top visualization libraries: Matplotlib, Seaborn, and Plotly. Learn when to use each library, their strengths, limitations, and best practices for different visualization needs.
Learn to integrate Machine Learning models into investment strategies and evaluate their performance using backtesting.py. Build, test, and optimize ML-based trading strategies with real market data.
Automate Spanish electrical grid analysis using the ESIOS API with Python. Download, process, and visualize over 10,000 real-time indicators from Red Eléctrica de España.
Detect anomalies in time series data using Isolation Forest and other ML algorithms with Python. Build robust anomaly detection systems for financial, energy, and operational data.
Automate the download and analysis of Federal Reserve Economic Data (FRED) using Python. Access thousands of economic indicators, create visualizations, and build automated reporting pipelines.
Automate trading strategies by programming buy and sell orders with Alpaca's API in Python. Build algorithmic trading bots, implement risk management, and execute trades programmatically.
Master the EIA API to automate US energy data collection and analysis with Python. Access real-time electricity demand, generation data, and build powerful energy market analytics.
Build a normalized database to efficiently query and analyze historical energy programming data from the Spanish electrical system. Learn database design, normalization, and optimization for energy market analysis.
Access and analyze FDA's Adverse Event Reporting System (FAERS) data for drug safety surveillance. Learn to download, process, and interpret pharmacovigilance data for post-market drug monitoring.
Automate European energy market analysis using the ENTSO-E API with Python. Access cross-border flows, electricity prices, and generation data across all European countries.
Master data visualization techniques using Python's most popular libraries: Matplotlib, Seaborn, and Plotly. Create stunning charts, interactive dashboards, and publication-ready visualizations.