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Showing 26–50 of 52 items
Use machine learning and NLP to extract meaningful patterns from free-text data, including names, locations, and complex real-world entities.
Use built-in Python data structures to perform increasingly complex data analysis and elevate your programming skills.
Use SQL and Python to gather, store, and visualize data, including building web crawlers and working with databases.
Learn to fit statistical models using Python and apply regression, Bayesian, and mixed-effects methods to real data.
Learn Python and Rhino scripting to create computational design workflows and generate geometric forms through coding and procedural design.
Build foundational Python skills for data analysis, web applications, and practical computing tasks.
Develop data science skills in Python, including data wrangling, visualization, machine learning, and applied analytics.
Learn Python 3 programming fundamentals for problem-solving, software development, and automation.
Use Python to perform statistical analysis, test hypotheses, and interpret real-world data effectively.
Use Python for creative coding projects that blend programming, visual art, interactivity, and computational thinking.
Strengthen Python programming with data structures, problem-solving strategies, and effective debugging techniques.
Advance Python data science skills with deeper machine learning, text mining, and applied analytics techniques.
Learn to write and understand object-oriented programs in Python using real-world modeling and creative coding projects.
Learn to use Python in Rhino 3D to create complex geometric forms through procedural logic and design computation.
Deepen your understanding of C programming and build portable, efficient algorithms using types, operators, recursion, and preprocessing.
Learn to use AI tools like ChatGPT to analyze, visualize, and interpret data for real-world applications and projects.
Learn NumPy and pandas to manipulate arrays and write efficient Python code for numerical computing and data analysis.
Use logistic regression and Python to model and predict sports outcomes while examining analytics in gambling and society.
Apply machine learning techniques to real sports data to analyze, predict outcomes, and enhance performance analytics.
Learn web application fundamentals using Django, covering HTTP, HTML, MVC, and live deployment techniques.
Analyze athletic performance and recovery using wearable tech, physiological principles, and Python programming on sports datasets.
Dive into the C programming language and its legacy while comparing syntax and structures with Python.
Master debugging techniques using tools and unit testing to quickly identify, fix, and prevent programming errors in Python.
Learn how Django uses models and ORM to interact with databases, while building skills in SQL, data relationships, and object-oriented programming.
Learn to gather, manage, and visualize data using Python and SQL to answer high-level questions and draw meaningful insights.
