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Showing 1–25 of 31 items
Learn how to apply AI in healthcare diagnostics while understanding ethical, clinical, and technical considerations in medical decision-making.
Use built-in Python data structures to perform increasingly complex data analysis and elevate your programming skills.
Create relational database models using PostgreSQL, practicing data modeling, SQL commands, and schema creation through hands-on exercises.
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.
Gain essential knowledge of generative AI applications, benefits, and risks, from societal impacts to legal and ethical concerns.
Explore governance strategies and global regulatory frameworks to ensure generative AI is deployed ethically and transparently in organizations.
Explore generative AI essentials, ethical use, authorship, and regulation through expert insights on AI’s impact on society and work.
Learn statistical fundamentals, including study design, data visualization, and inference, while using Python tools like Pandas and Matplotlib to analyze data.
Explore networks and connections using Python’s NetworkX library to measure centrality, evolution, and structure in social systems.
Explore how PostgreSQL handles full-text search, JSON data, and inverted indexing for advanced natural language processing.
Learn to create meaningful data visualizations in Python using matplotlib and design principles for clarity and insight.
This Teach-Out introduces learners to artificial intelligence and explains how large language models and chatbots like ChatGPT work. You will better understand the ethical use of artificial intelligen
Learn to use AI tools like ChatGPT to analyze, visualize, and interpret data for real-world applications and projects.
Use Python and sports datasets to explore team performance and become a hands-on producer of sports analytics.
This Teach-Out introduces learners to artificial intelligence (AI) and explains how large language models and generative AI tools, like ChatGPT, work. Explore the ethical use of artificial intelligenc
Compare ACID and BASE databases, explore PostgreSQL performance, and implement NoSQL search capabilities with Deno.
Strengthen critical thinking and decision-making by using generative AI to analyze ideas, uncover assumptions, and evaluate information from diverse sources.
Master text cleaning, classification, and topic modeling using Python and NLP to extract meaning from large text datasets.
Apply machine learning techniques in Python to build, validate, and optimize predictive models using scikit-learn.
Use AI tools to think more strategically, streamline workflows, and become a more confident problem-solver.
Examine the ethical implications of big data, privacy, fairness, and algorithmic accountability in modern data science practice.
Develop practical skills to support sustainability, climate action, and a more just environmental future.
Master the full data science lifecycle by applying machine learning and computational methods to solve real-world problems through a human-centered lens that prioritizes ethics and social good.
Design AI solutions with users, not just for users.
