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AI Literacy · AI-101

Introduction to AI

Understand what artificial intelligence is, how it works, and where it appears in everyday life.

LEVELBeginner
LESSON TIMEAbout 5 hours
FORMAT6 self-paced lessons
PATHWAYCDAP required

Practice and the final project time is additional to the lesson estimate.

Check if it fits youSee the full syllabus

IS THIS COURSE FOR YOU?

What to expect from Introduction to AI

Anyone who wants a clear, non-technical introduction to artificial intelligence.

What you will learn

  • Explain what AI can and cannot do
  • Recognize common AI applications
  • Use AI with appropriate human judgment

LESSON OUTLINE SAMPLE

How AI learns from data

How AI learns from data is more than a term to remember: it is a practical skill that requires you to understand the situation, select an appropriate method, complete the work carefully, and verify the result. Use this study guide to connect the underlying ideas to the decisions you will make in the lesson activity.

This sample shows the lesson goals and selected takeaways. Enroll to access the complete lesson notes, activities, and assignments.

What this lesson covers

  • Explain the purpose and everyday value of Introduction to AI.
  • Recognize the core skills and safe practices introduced in this course.
  • Apply the introductory concepts to a realistic activity.

Selected takeaways

  • Artificial intelligence finds patterns in data and uses those patterns to classify, predict, recommend, or generate content. AI does not understand the world like a person and can produce confident errors. Useful AI practice combines a clear task, appropriate data, human review, and verification against reliable sources.
  • AI foundations: Understand what AI is and what it can and cannot do.
  • For Getting started with Introduction to AI, practice with sample information, verify the result, and record the safe process you followed.

COMPLETE SYLLABUS

3 modules · 6 lessons

6 follow-up assignments · 3 assessments
01
AI foundationsUnderstand what AI is and what it can and cannot do.
2 lessons
  1. 1.1How AI learns from data
  2. 1.2Recognize AI in daily life
02
Working with AIUse common AI systems with realistic expectations.
2 lessons
  1. 2.1Generative AI and its outputs
  2. 2.2Ask AI useful questions
03
Evaluate AI resultsCheck quality, accuracy, and appropriate use.
2 lessons
  1. 3.1Recognize errors and limitations
  2. 3.2Use AI with human judgment

FINAL COURSE PROJECT

Everyday AI Decision Guide

Submit a decision guide comparing three AI uses, their data needs, benefits, limits and human checkpoints, supporting evidence of your process, and a concise reflection. Do not include passwords, private records or confidential information.

Approximately 4 hours · Instructor reviewed

How success is evaluated

  • The project responds directly to the stated audience, purpose and scenario.
  • The submitted artifact demonstrates skills from multiple modules rather than one isolated lesson.
  • The learner provides evidence of testing, verification and revision.
  • The work addresses accuracy, transparency, privacy and appropriate human oversight.
  • The explanation is original, clear, well organized and suitable for instructor review.

GRADING AND CERTIFICATE POLICY

Progress by demonstrating mastery

This course is completed through verified evidence of learning—not by averaging every activity into a traditional grade. You can use feedback, revise your work, and resubmit when an instructor requests changes.

  1. Complete the lessonsFinish the required lessons and applied practice in the published course release.
  2. Pass knowledge checksMeet each assessment’s published passing score. Attempt limits and retry guidance are shown before starting.
  3. Demonstrate practical skillsSubmit required assignments using safe, non-confidential evidence and receive instructor approval.
  4. Pass the final projectComplete the course-specific project and satisfy its published marking rubric. Revise and resubmit when requested.
  5. Unlock the certificateThe certificate becomes eligible only after every required lesson, assessment, assignment approval, and final-project requirement is verified.
How grading decisions are made
  • Courses use mastery-based completion rather than an averaged GPA or assignment-category percentage.
  • Practice activities help learners improve and do not reduce a course grade.
  • The rubric displayed with the active assignment in My Learning is authoritative.
  • Accuracy, safety, privacy, accessibility, or ethical failures may require revision even when other work is strong.
  • Instructor feedback and earlier submissions remain visible when work is revised and resubmitted.

Published assessment requirements: AI foundations knowledge check: 75% passing score, up to 3 attempts · Working with AI knowledge check: 75% passing score, up to 3 attempts · Evaluate AI results knowledge check: 75% passing score, up to 3 attempts

Ready to begin?

Study at your pace and keep access to your learning record and feedback.

Introduction to AI