Computer science
How people design algorithms, software, data, networks, and computing systems to solve problems.
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Mississippi AI Collaborative
Learn what matters.
Know what to do next.
Begin with a plain-language foundation or choose a pathway shaped around your classroom, work, technical practice, creative goals, or community.
AI in plain language
What AI is—and where generative AI fits.
AI is part of computer science. People design the goal, collect or choose the data, build the system, test it, and decide how its output will be used.
Artificial intelligence
Approaches for problems involving perception, language, reasoning, planning, prediction, generation, or action.
Machine learning
Models learn patterns from examples or experience instead of following only hand-written rules.
Generative AI
Most current systems use machine-learning models to produce new text, images, audio, video, or code from patterns in training data.
Perceive
Recognize speech, images, sounds, or sensor data.
Reason & search
Represent knowledge, compare possibilities, and plan.
Learn & predict
Find patterns and estimate what may happen next.
Generate
Create a new response, image, sound, model, or recommendation.
Act
Control a process, tool, robot, or software agent.
PeopleChoose a goal and examples
→SystemFinds patterns or follows rules
→OutputPredicts, recommends, or creates
→PeopleCheck, decide, and stay accountable
A useful test
Ask: What task is the system doing? What data, representations, rules, or models shape it? How was it tested? What can go wrong? Who checks the result? Who is affected?
This MAIC explainer is informed by the ACM, IEEE Computer Society, and AAAI Computer Science Curricula 2023, the 2026 CSTA PK–12 Standards, and UNESCO’s AI Competency Framework for Students. It is a learning aid, not an official standards graphic.
Choose a direction
Built around where
you’ll use AI.
There is no single right route for every person or place. Start with your work, your community, or the problem you want to solve—and adapt the pathway as you learn.
01
Start here · 5 courses
AI Basics
Build a practical foundation in generative AI, responsible use, and the ideas that power today’s tools.
02
Owners & founders · 6 courses
Business & Entrepreneurship
Use AI to improve marketing, customer service, productivity, decision-making, and organizational readiness.
03
Educators · 6 courses
Education
Apply AI to planning, personalized learning, classroom creativity, and responsible instruction.
04
Mission-driven teams · 6 courses
Nonprofit Leaders
Strengthen outreach, fundraising, strategy, and community services with responsible AI.
05
All learners · 3 courses
Ethics & Responsible AI
Learn the principles, risks, governance practices, and human impacts behind responsible AI.
06
Health innovators · 3 courses
Health & Telehealth
Explore patient care, health data, digital practice, telehealth, privacy, and bias.
07
Rural innovators · 6 courses
Agriculture & Sustainability
Apply AI, data, and digital systems to agriculture, sustainability, and rural enterprise.
08
Defenders · 3 courses
Cybersecurity & Digital Safety
Use AI-aware security practices to protect systems, data, organizations, and people.
09
Creators · 3 courses
Creative Arts & Media
Use generative AI thoughtfully across visual art, marketing, writing, and media projects.
10
Developers · 6 courses & labs
AI Development & On-Device Systems
Build, evaluate, and deploy AI applications—from machine-learning foundations and open models to agents and private on-device inference.
11
Curious minds & developers · 5 open learning steps
Quantum Computing: A Mississippi Introduction
Understand what quantum computing is, what it is not, and why Mississippi is building capacity in quantum research, data science, cybersecurity, and advanced computing.
12
Students & families · 6 courses
K–12 AI Explorers
Explore how AI works, question what it tells you, and build something useful through age-appropriate, hands-on learning.
Not sure yet?
Four strong places to begin.
IBM SkillsBuildMAIC starting point · IBM SkillsBuild
Introduction to Generative AI
Learn core generative AI concepts and earn an IBM digital badge.
View course details ↗Listing checked October 27, 2026 · Report a change
MAIC starting point · AWS Skill Builder
Building a Generative AI-Ready Organization
Prepare your organization to adopt and scale generative AI responsibly.
View course details ↗Listing checked October 27, 2026 · Report a change
MAIC starting point · Google & MIT RAISE
Generative AI for Educators
A two-hour course for personalizing instruction and creating classroom content.
View course details ↗Listing checked October 27, 2026 · Report a change
MAIC starting point · Mississippi AI Collaborative
AI Quest: Build Something That Helps Mississippi
A grade-adaptive, six-mission course aligned to Mississippi’s 2026 Computer Science Standards.
Listing checked October 27, 2026 · Report a change
Beyond courses
Turn learning into responsible action.
Use adaptable policy templates, community-built playbooks, task-based prompt guides, and decision directories—all connected to the learning pathways.
4 policy templates10 practical playbooks4 prompt guides6 decision directories
Ready to do more?
Connect learning to a MAIC program.
Move from an open course into educator support, applied project experience, workforce development, or a community conversation.