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Showing 1–25 of 56 items
Build confidence in inferential statistics using Python to estimate population values and test hypotheses with real-world data.
Learn Python from scratch and build your first programs using simple instructions—no math or coding experience required.
Explore networks and connections using Python’s NetworkX library to measure centrality, evolution, and structure in social systems.
Apply machine learning techniques in Python to build, validate, and optimize predictive models using scikit-learn.
Use SQL and Python to gather, store, and visualize data, including building web crawlers and working with databases.
Apply your Python skills in a final project to retrieve, process, and visualize data using real-world datasets.
Learn to create meaningful data visualizations in Python using matplotlib and design principles for clarity and insight.
Master user-defined functions, dictionaries, and file handling to perform text analysis and compute sentiment from social media data.
Begin coding with Python 3 by learning control structures, data types, and visual programming with Turtle graphics.
Learn to design and use Python classes, inheritance, and automated testing to build structured and reusable code.
Create a portfolio-ready software engineering project using Python libraries for image recognition and manipulation.
Learn Python and Rhino scripting to create computational design workflows and generate geometric forms through coding and procedural design.
Learn to code visually with Python through dynamic shapes and data structures using the Processing platform.
Master Python fundamentals and creative coding skills to automate tasks, tell stories, and build expressive digital projects.
Use Python data structures and object-oriented design to enhance creative projects and develop computational thinking for visual design.
Use Python to create generative art and dynamic visual designs with project-based coding in Processing.
Learn how to integrate Meta’s Llama 2 into Python workflows using prompting, quantization, and open-source LLMs for generative AI.
Apply Python and scientific libraries like NumPy and SciPy to solve statistical problems and explore probability, distributions, and relationships in data.
Apply debugging strategies and data science tools to analyze real-world datasets and document your coding process in a capstone project.
Learn structured debugging techniques in Python using loops, control structures, and the OILER framework to write and troubleshoot code effectively.
Use machine learning and NLP to extract meaningful patterns from free-text data, including names, locations, and complex real-world entities.
Discover how to use unsupervised learning techniques to find patterns in data, including clustering, topic modeling, and dimensionality reduction.
Use Python and NetworkX to analyze complex systems like epidemics and social media using network theory and diffusion models.
Learn to extract patterns from real-world datasets using data mining principles and Python for business and social insights.
Learn to access, parse, and work with web data using Python, including APIs, HTML, XML, and JSON formats.
