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Course Modules
Each QuantHub module can be mapped directly to your course goals—offering a flexible, ready-to-use foundation for AI and data skills education.
ID
Title
Category
Module 2367
Integrating AI into academic workflows
AI Foundations
Module 2367
Leveraging AI for evidence-based performance analysis
AI Foundations
Module 2358
Leveraging AI to create a comprehensive project plan
AI Foundations
Module 2214
Craft a research question for a time-series task Case Studies in Community
Data Research
Module 2216
Calculate a moving average and plot it on a Case line chart in atime-series task
Case Studies in Community Data Research
Module 2217
Make an observation about the pattern of variability in a quantitative variable over time
Case Studies in Community Data Research
Module 2218
Build a narrative around a time-series chart
Case Studies in Community Data Research
Module 2263
Aggregate a datetime variable
Case Studies in Community Data Research
Module 2264
Aggregate a datetime variable with Excel
Case Studies in Community Data Research
Module 2271
Calculate a moving average and plot it in Excel
Case Studies in Community Data Research
Module 2272
Use slicers and timelines in Excel to analyze time-series data
Case Studies in Community Data Research
Module 2273
Create and present a time-series narrative in Excel
Case Studies in Community Data Research
Module 2285
Organizing workspace components in Excel
Case Studies in Community Data Research
Module 2286
Formatting cells by data types and presentation requirements
Excel for Business Analytics
Module 2287
Calculating descriptive statistics with Excel functions
Excel for Business Analytics
Module 2288
Applying Excel workspace efficiency tools
Excel for Business Analytics
Module 2289
Configuring absolute and relative cell references in Excel formulas
Excel for Business Analytics
Module 2290
Analyzing datasets using COUNT, COUNTA, and COUNTIF(S) functions
Excel for Business Analytics
Module 2291
Transforming raw data into structured and pivot tables
Excel for Business Analytics
Module 2292
Applying MEDIAN and PROB functions in Excel
Excel for Business Analytics
Module 2293
Creating appropriate charts in Excel
Excel for Business Analytics
Module 2294
Creating nested logical functions for automated decision-making in Excel
Excel for Business Analytics
Module 2295
Implementing advanced Excel functions for conditional data analysis
Excel for Business Analytics
Module 2356
Leveraging AI for concise, data-backed analyses
Marketing in the Age of AI
Module 2360
Differentiating prompting from traditional computing interactions
Marketing in the Age of AI
Module 2361
Synthesizing prompt components for effective AI communication
Marketing in the Age of AI
Module 2362
Evaluating influence techniques on AI response quality
Marketing in the Age of AI
Module 2363
Analyzing complex problems and synthesizing reasoning approaches
Marketing in the Age of AI
Module 2364
Comparing multimodal prompting strategies across media types
Marketing in the Age of AI
Module 2177
Create a frequency/relative/cumulative frequency table to analyze survey results
Conducting a survey and summarizing data with Excel
Module 2178
Make a recommendation based on the modal category
Conducting a survey and summarizing data with Excel
Module 2179
Select charts to communicate a modal category and and summarizing data with Excel
Conducting a survey and summarizing data with Excel
Module 2268
Create a frequency table in Excel
Conducting a survey and summarizing data with Excel
Module 2269
Format a frequency table in Exce
Conducting a survey and summarizing data with Excel
Module 2335
Understanding the history and current state of AI
Conducting a survey and summarizing data with Excel
Module 2336
Understanding AI systems’ fundamental characteristics and mechanisms
AI Foundations
Module 2337
Explaining basic prompt engineering techniques for generative AI
AI Foundations
Module 2338
Identifying generative AI use cases in professional workflows
AI Foundations
Module 2352
Understanding business challenges and AI applications
AI Foundations
Module 2353
Understanding ethical and security considerations for AI users
AI Foundations
Module 2359
Leveraging generative AI as a learning partner
AI Foundations
Exploratory, Self-paced Learning
Course Modules
Self-paced and accessible, modules provide flexible, foundational learning.
ID
Title
Category
Module 1818
Becoming data literate
Becoming data literate introduces you to the world of literate data and helps you understand why data literacy is relevant to you in your everyday life.
Module 1957
Introduction to reading charts
Discusses the importance of learning how to read charts and what steps to take to read charts.
Module 1937
Introduction to visual literacy
Introduction to visual literacy introduces you to the purpose and process of data visualization.
Module 2073
Introduction to malware
Learn about malicious software’s origins, types, and impacts. Understand detection, prevention strategies, and the importance of cybersecurity in combating malware threats
Module 2075
Introduction to password security
Discover the principles of strong password creation and management. Understand threats to password security and learn about technologies that enhance password protection, such as two-factor authentication.
Module 2074
Introduction to phishing
Explore the mechanics of phishing attacks, identifying common tactics, and the psychological tricks used by attackers. Learn protective measures to safeguard personal and organizational information.
Module 2087
Applying cyber security to AI
This skill introduces the principles of cybersecurity as they apply to AI systems, covering key strategies for protecting AI models, data, and infrastructure from potential threats.
Module 2263
Introduction to machine learning
Introduction to machine learning is an overview of machine learning; what it is, its types and subtypes, how it works, and how it is applied to solve real-world problems.
Module 1858
Preparing data for for machine learning
Preparing data for machine learning is the ability to gather for machine learning required data and clean, transform, and select features models.
Module 2085
Generative AI and multimedia development
This skill explores the use of generative AI in multimedia focusing on how to create and enhance development images, audio, video, and other digital content using AI-driven tools and techniques.
Module 2086
This skill focusing on techniques to optimize AI-generated text content for clarity, accuracy, and desired outcomes.
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