Use a suitable practice environment for the language or tool shown in the recordings. Earlier programming knowledge is useful for topic courses that build on variables, functions or data structures.
About this course
Study AI Literacy Fundamentals in this free English video course from Khan Academy. The classroom preserves all 6 published source recordings, totaling approximately 32m, with their original lesson titles and sequence. The selected curriculum focuses on program structure, reproducible examples and independent problem solving. Use the videos to follow an explanation, examine an example and develop a study output you can check independently. The course title describes this recorded subject or learning track; your study can extend beyond watching through the practical activities below.
Course at a glance
| Provider / Teaching team | Khan Academy |
|---|---|
| Platform | YouTube · Khan Academy |
| Access | Free Video |
| Level | Beginner |
| Language | English |
| Videos | 6 |
| Video duration | 32m · allow extra time for practice |
| Format | Self-paced recorded training |
| Certificate | Not included with video viewing |
What you’ll learn
- Follow the explanation and worked reasoning in “What is artificial intelligence”, then describe the main idea in your own words.
- Follow the explanation and worked reasoning in “AI in your life”, then describe the main idea in your own words.
- Follow the explanation and worked reasoning in “ChatGPTIntro”, then describe the main idea in your own words.
- Follow the explanation and worked reasoning in “Prompting basics”, then describe the main idea in your own words.
- Connect examples across AI Literacy Fundamentals by identifying the terms, assumptions and methods they use.
- Create a small independent practice output and check it against the relevant teaching explanation.
Skills you’ll gain
- AI literacy
- Conceptual reasoning
- AI terminology
- Example analysis
Course Overview
The source curriculum is presented as a complete recorded video edition of AI Literacy Fundamentals. Representative lessons include “What is artificial intelligence”, “ChatGPTIntro” and “Basics of AI approaches”. These recordings give concrete examples to revisit while building program structure, reproducible examples and independent problem solving. Their place in the lesson list is preserved, so you can return to a particular explanation without losing its source position. Introductions, demonstrations, examples, reviews and compilations remain included whenever they appear in the original playlist. Reading a lesson title is useful for locating a topic; working through its reasoning and checking a practice attempt is what makes the recording valuable for learning.
How to study the course
- Videos 1–1: this part of the source list includes “What is artificial intelligence” through “What is artificial intelligence”. State the intended input, operation and result. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
- Videos 2–3: this part of the source list includes “AI in your life” through “ChatGPTIntro”. Reproduce a demonstration before modifying it. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
- Videos 4–4: this part of the source list includes “Prompting basics” through “Prompting basics”. Trace behavior and investigate unexpected output. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
- Videos 5–6: this part of the source list includes “AI and bad math” through “Basics of AI approaches”. Check the example with a changed condition. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
Who is this for?
This course suits learners studying the specific programming or computing topic. It also provides a recorded reference for revisiting a topic after an earlier lesson or study attempt. Choose examples appropriate to your background and allow time to work through the method instead of judging understanding only by how familiar the terminology sounds.
Before you start
Use a suitable practice environment for the language or tool shown in the recordings. Earlier programming knowledge is useful for topic courses that build on variables, functions or data structures.
Put the lessons into practice
Build a small example using two techniques demonstrated in the recordings. State the intended result, run or trace the example and explain how its parts work together. Try a normal case and a changed input or condition. Record the difference between the expected and actual results, then correct one problem using the course’s debugging or reasoning approach. Keep the final example small enough that you can explain every important step. Finish with a short note on one improvement and the evidence that it worked.
This optional study activity is provided by WikiFree for independent practice. Keep your working notes and use the relevant classroom recording to check a step, definition or interpretation. It is not an instructor-marked assignment.
Certificate / Assessment
Watching the public videos and using WikiFree completion tracking does not award a certificate, academic credit, an examination voucher or instructor assessment. Use your practice output to review what you can explain and repeat independently. The recorded lessons provide study material; completion tracking records your progress through that material.
Related courses for your next step
- Related learningGoogle Introduction to Generative AI: Free Beginner Course
Focus: Generative AI vocabulary · AI and ML classification
Beginner - Related learningGoogle Gen AI: Unlock Foundational Concepts — Free Course
Focus: Generative AI vocabulary · Data awareness
Beginner - Related learningGoogle Responsible AI: Free AI Principles Course
Focus: Ethical issue spotting · Responsible innovation
Beginner
Compare course focus, level and study time
| Course | Level | Focus | Study time |
|---|---|---|---|
| This course — AI Literacy Fundamentals: Free Course | Beginner | AI literacy · Conceptual reasoning · AI terminology | 32m of video; practice time is additional |
| Google Introduction to Generative AI: Free Beginner Course | Beginner | Generative AI vocabulary · AI and ML classification · Model-type comparison | 45 minutes; official estimated study time, individual pace varies. |
| Google Gen AI: Unlock Foundational Concepts — Free Course | Beginner | Generative AI vocabulary · Data awareness · Foundation-model concepts | Google estimated course length: one hour; individual study pace varies. |
| Google Responsible AI: Free AI Principles Course | Beginner | Ethical issue spotting · Responsible innovation · AI governance awareness | About 2 hours; provider estimate |
Frequently asked questions
Is this course free to watch?
Yes. The public source videos are available in the WikiFree classroom. Video viewing does not include separately priced tools, hardware, memberships or a credential.
How long does the course take?
The 6 source video occurrences total approximately 32m. Allow additional time for pausing, notes, practice and revisiting an explanation.
What background do I need?
Use a suitable practice environment for the language or tool shown in the recordings. Earlier programming knowledge is useful for topic courses that build on variables, functions or data structures.
Does completing the videos award a certificate?
No. Video viewing and WikiFree progress tracking do not award a certificate, academic credit or an exam voucher.
Can I study on a phone?
Yes. The classroom supports a responsive player and searchable lesson list. A larger screen or a suitable practice environment can help with detailed calculations, diagrams and software examples.
Provider: Khan Academy. Videos play from the Khan Academy channel on YouTube.
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