Alternative Data Analysis
Learn to source, process, and model non-traditional data sources like satellite imagery, GPS data, and web scraped data for trading signals.
78 courses
Learn to extract data from any website and automate repetitive web tasks using Python, BeautifulSoup, and Selenium through clear, step-by-step written guides.
Analyze and visualize location-based data to create insightful maps using GeoPandas and modern Python libraries.
Learn how to collect, structure, and analyze web data using both visual scraping tools and simple code to automate your research and data gathering.
Learn to automate data collection from static and dynamic websites by building custom scrapers with Python, BeautifulSoup, and Selenium.
Master Python web scraping to extract data from any website using BeautifulSoup, Selenium, Scrapy, and AI-powered parsing techniques.
Build scalable web crawlers and extract structured data from complex websites using the powerful Scrapy framework for Python.
Create interactive maps and perform client-side spatial analysis using modern JavaScript libraries.
Learn to retrieve, analyze, and visualize planetary-scale satellite imagery and location data using Python APIs, geopandas, and modern geospatial data science workflows.
Learn to build responsive, interactive, and data-rich web maps using Leaflet JS, from basic markers to advanced custom plugins and event handling.
Build a portfolio of data extraction projects and learn to automate data collection from the web using Beautiful Soup.
Develop and deploy custom interactive web maps and spatial databases using GeoDjango, PostGIS, GeoServer, and Leaflet.
Build the skills to map and analyze global pipelines, power grids, and international energy corridors using Python, GeoPandas, and modern geospatial libraries.
Build automated spiders to collect web data and store it in professional databases using Python and the Scrapy framework.
Learn to organize, process, and analyze spatial data using core algorithms and indexing structures tailored for geoinformatics applications.
Learn to extract data from modern, dynamic websites using Scrapy, Selenium, and other essential Python libraries.
Learn how to extract valuable data from websites using Python and BeautifulSoup, starting from absolute basics to building your first automated data-gathering scripts.
Create dynamic web-based maps by applying R programming techniques to spatial datasets for clear and engaging data visualization.
Learn to design and execute an independent geographic information systems project from initial data sourcing to final spatial presentation.
Learn the core concepts of spatial data and map creation using open-source tools in this comprehensive guide for beginners.
Learn to extract, clean, and structure data from the web using Python, BeautifulSoup, and Scrapy through clear, step-by-step written explanations and practical code exercises.
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