Lesson 0.1 — Welcome to AI Literacy for Professionals

Estimated study time: 20 minutes  |  Type: Orientation (ungraded)

Learning objectives

  • Describe the purpose, scope, and audience of this course.
  • Navigate the modules, lessons, quizzes, and assignments confidently.
  • Explain how certificate eligibility is earned.
  • Locate technical support and understand the non-degree status of this course.

Executive summary

This course builds a practical, critical, and responsible foundation for using artificial intelligence in professional, academic, institutional, and public-sector work. It is not a programming course. It is designed to help you understand what modern AI is, judge what it can and cannot do, work effectively with generative systems, verify their output, protect sensitive information, and design responsible AI-assisted workflows — without surrendering human judgment.

Welcome

Welcome to KBA13 Academy and to the School of Artificial Intelligence. Over the next 8–10 hours of study, spread across roughly two to four weeks at your own pace, you will move from a general awareness of AI to a working professional competency. The course takes a deliberately balanced stance: it avoids both exaggerated technological optimism and uninformed fear. AI is treated as a powerful but limited tool whose value depends on the judgment of the person using it.

How this course is organised

The course contains seven modules. Module 0 orients you and establishes the ground rules. Modules 1 through 5 build knowledge and skills, each combining written lessons, professional examples, case studies, exercises, quizzes, and at least one applied assignment. Module 6 is a final project in which you design and document a responsible AI-assisted workflow for a real task from your own professional life.

Course map

  • Module 0 — Start Here: orientation, responsible-use rules, baseline self-assessment.
  • Module 1 — What Artificial Intelligence Is: concepts, how generative AI works, capabilities and limits.
  • Module 2 — Working Effectively with Generative AI: task framing, prompting, iteration, tool selection.
  • Module 3 — Verification, Risk, and Responsible Use: hallucinations, verification, privacy, bias, integrity.
  • Module 4 — Professional Applications: writing, research, planning, teaching, communication.
  • Module 5 — Human Judgment and Institutional Readiness: oversight, risk classification, governance.
  • Module 6 — Final Project: Responsible AI Workflow Blueprint and a 30-day action plan.

How to use readings, quizzes, and assignments

Each lesson is complete on its own: the essential knowledge lives in the written text, never only in a video. Read actively, attempt each exercise, and use the reflection questions to connect ideas to your own work. Module quizzes allow up to three attempts and require 70% to pass; they exist to reinforce learning, not to trick you. Assignments and the final project are where the real competency is demonstrated and are marked against clear rubrics.

How certificate eligibility works

A Certificate of Completion is earned, not given for merely opening pages. You must complete at least 80% of lessons, attempt all module quizzes with a 70% average, score at least 70% on the final assessment and final project, submit required assignments, and accept the academic-integrity declaration. Certificates carry a unique number and a verification URL.

Technical support & course status

If something does not load, first refresh and try another browser; persistent issues can be reported through the School of AI student-services contact route. Please note: this is non-degree professional learning. It does not confer academic credit, SKS, ECTS, a diploma, or a university degree.

Reflection question

What professional task do you most want AI to help you perform better? Keep your answer in mind — you will return to it in the final project.

Completion checklist for this lesson

  • I understand the course purpose and audience.
  • I know how to navigate modules and assessments.
  • I understand how the certificate is earned.
  • I have noted my target professional task.

Key terms

Non-degree professional learning, self-paced, certificate of completion, academic integrity.

Optional media asset — production pending

Narration script (3–4 min): a short welcome introducing the course philosophy of “AI as a tool, judgment as the profession”. Slide outline (6 slides): (1) Welcome; (2) What this course is/is not; (3) Course map; (4) How you’ll learn; (5) How the certificate is earned; (6) Your first reflection. OPTIONAL MEDIA ASSET — PRODUCTION PENDING.

Content status: DRAFT · AI-assisted, pending human academic review · v1.0 · References: none required for orientation.

Slide deck

A ten-slide HTML presentation summarising this lesson. It prints, translates and reads on any device.

A ten-slide presentation of this lesson. Every slide is plain HTML, so it prints, translates and reads on any device.

Slide 1 of 10

What this course is

An introduction to ai literacy for professionals, taught within the School of Applied Artificial Intelligence.

Analytical, evidence-led and assessed by human markers.

AI-F01 · Lesson 0.4KBA13 Academy

Slide 2 of 10

Why the subject matters

  • Decisions in this area are consequential and contested
  • Evidence is usually incomplete at the moment of decision
  • Institutions, interests and accident all shape outcomes
  • Professional judgement has to be defensible, not merely confident

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Slide 3 of 10

The eight modules

  • Module 0 — Start Here
  • Modules 1–2 — Concepts and frameworks
  • Modules 3–4 — Evidence and analysis
  • Modules 5–7 — Cases, assessment and the final project

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Slide 4 of 10

Every lesson has the same shape

  • Objectives and key terms
  • Written lesson and worked example
  • Ten-slide HTML deck
  • Activity, self-check and references

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Slide 5 of 10

Core concepts you will meet

  • supervised and unsupervised learning
  • representation and embeddings
  • retrieval-augmented generation
  • agentic workflows

Module 1 defines each of these precisely.

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Slide 6 of 10

Frameworks you will use

  • The transformer architecture
  • Retrieval-augmented generation
  • The NIST AI Risk Management Framework
  • Model cards and datasheets

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Slide 7 of 10

Evidence you will work with

  • benchmark suites and leaderboards
  • held-out test sets
  • red-team and adversarial probes
  • production telemetry and drift monitors

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Slide 8 of 10

How you will be assessed

  • Knowledge checks across the modules
  • An analytical brief and a design artefact
  • An evaluation report and an implementation plan
  • A final capstone submission

Pass mark: 70 per cent. Marked by a human assessor.

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Slide 9 of 10

Working method

  • Two or three short sessions a week beats one long one
  • Attempt the self-check before reading the answer
  • Reference everything; use the real sources listed
  • Declare any use of generative AI

AI-F01 · Lesson 0.4KBA13 Academy

Slide 10 of 10

Start here

Move to Module 1 and write your own definitions of the key terms before you read ours.

The gap between your definition and ours is where the learning is.

AI-F01 · Lesson 0.4KBA13 Academy

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