Level
Level 3
Credits
60
Guided Learning
360
Total Qualification Time
600
Qualification overview
A simple summary of who this qualification is for and what learners can expect.
About this qualification
The Level 3 Diploma in Artificial Intelligence is an IQ Awards qualification at Level 3. It supports learners in developing knowledge, practical skills and professional behaviours in artificial intelligence.
The qualification is structured for clear delivery, assessment and quality assurance through approved centres.
Who is it for?
- Learners who are starting out in artificial intelligence and want to build a strong foundation.
- School leavers, new entrants or early-career learners seeking a recognised vocational qualification.
- Learners who want to progress into further study or employment.
Entry and assessment guidance
Centres should check learner suitability before registration.
Entry requirements
- Entry is at the discretion of the approved centre.
- Learners should normally have a good general education or equivalent experience.
- Learners should have an interest in artificial intelligence and be able to complete written and practical assessment tasks.
- Centres should confirm that learners have sufficient English language ability for the level of study.
Assessment approach
Assessment may include assignments, projects, practical evidence, workplace evidence, portfolios, presentations or other centre-devised assessment methods approved under IQ Awards quality assurance.
Language requirements
Centres should ensure learners have sufficient language competency to complete learning and assessment.
Qualification units
Jump to any unit below. Each unit opens with its own learning outcomes, criteria and content where available.
Unit 1 of 6
Introduction to Artificial Intelligence
IQA-L3-AI-U01
Learning outcomes
- LO1 Understand the basic concepts of artificial intelligence.
- LO2 Understand the role of AI in modern society.
- LO3 Understand common AI tools and applications.
- LO4 Understand ethical considerations in the use of AI.
Assessment criteria
- AC1.1 Define artificial intelligence and related terms.
- AC1.2 Explain the difference between AI, machine learning and automation.
- AC2.1 Describe how AI is used in education, business, healthcare and daily life.
- AC2.2 Explain the benefits and limitations of AI.
- AC3.1 Identify common AI tools and their functions.
- AC3.2 Explain how AI applications support decision-making.
- AC4.1 Describe key ethical issues linked to AI.
- AC4.2 Explain the importance of responsible AI use.
Unit aim
This unit introduces learners to the fundamental concepts, uses and ethical considerations of artificial intelligence.
Indicative content
Definition of AI, machine learning, automation, AI applications, chatbots, recommendation systems, image recognition, AI benefits, limitations, bias, privacy and responsible use.
Assignment brief
Learners are required to prepare a written report explaining the basic concepts of AI, its applications, benefits, limitations and ethical issues.
Unit 2 of 6
Digital Skills for Artificial Intelligence
IQA-L3-AI-U02
Learning outcomes
- LO1 Understand the digital skills required for AI-related work.
- LO2 Be able to use digital tools for research and productivity.
- LO3 Understand data handling basics.
- LO4 Be able to present digital information effectively.
Assessment criteria
- AC1.1 Identify key digital skills needed in AI environments.
- AC1.2 Explain the importance of digital literacy.
- AC2.1 Use online tools to collect relevant information.
- AC2.2 Use productivity tools to organise work.
- AC3.1 Explain basic data types and data sources.
- AC3.2 Describe safe and accurate data handling practices.
- AC4.1 Present information using suitable digital formats.
- AC4.2 Review the effectiveness of digital presentation methods.
Unit aim
This unit develops essential digital skills required to support learning and work in artificial intelligence-related areas.
Indicative content
Digital literacy, productivity tools, online research, data sources, spreadsheets, basic data handling, digital communication, presentation tools and cyber awareness.
Assignment brief
Learners must complete a practical portfolio showing use of digital tools for research, data organisation and presentation.
Unit 3 of 6
Data Fundamentals for Artificial Intelligence
IQA-L3-AI-U03
Learning outcomes
- LO1 Understand the importance of data in AI.
- LO2 Understand different types of data.
- LO3 Be able to collect and organise simple data.
- LO4 Understand data quality and privacy issues.
Assessment criteria
- AC1.1 Explain why data is important for AI systems.
- AC1.2 Describe how AI systems use data.
- AC2.1 Identify structured and unstructured data.
- AC2.2 Explain examples of data used in AI applications.
- AC3.1 Collect simple data from given sources.
- AC3.2 Organise data using a suitable format.
- AC4.1 Explain common data quality issues.
- AC4.2 Describe basic data privacy and protection requirements.
Unit aim
This unit introduces learners to data concepts and explains how data supports artificial intelligence systems.
Indicative content
Role of data in AI, data types, datasets, structured data, unstructured data, data collection, data cleaning, data quality, privacy and data protection.
Assignment brief
Learners are required to collect, organise and review a simple dataset and explain its relevance to AI.
Unit 4 of 6
AI Tools and Applications
IQA-L3-AI-U04
Learning outcomes
- LO1 Understand common AI tools and platforms.
- LO2 Be able to use AI tools for simple tasks.
- LO3 Understand how AI supports productivity.
- LO4 Be able to review the output of AI tools.
Assessment criteria
- AC1.1 Identify common AI tools used in business and education.
- AC1.2 Describe the purpose of selected AI tools.
- AC2.1 Use AI tools to complete simple tasks.
- AC2.2 Demonstrate safe and appropriate use of AI tools.
- AC3.1 Explain how AI can improve productivity.
- AC3.2 Identify risks of over-reliance on AI tools.
- AC4.1 Review AI-generated outputs for accuracy.
- AC4.2 Suggest improvements to AI-generated outputs.
Unit aim
This unit enables learners to understand and use basic AI tools for productivity, communication and problem-solving.
Indicative content
Generative AI tools, chatbots, AI writing tools, AI image tools, productivity tools, prompt writing, output checking, accuracy, limitations and responsible use.
Assignment brief
Learners must demonstrate the use of AI tools for selected tasks and submit a short evaluation of the results.
Unit 5 of 6
Ethics and Responsible Use of AI
IQA-L3-AI-U05
Learning outcomes
- LO1 Understand ethical issues in AI.
- LO2 Understand bias and fairness in AI systems.
- LO3 Understand privacy and security concerns.
- LO4 Understand responsible AI practice.
Assessment criteria
- AC1.1 Describe ethical issues connected with AI.
- AC1.2 Explain why ethical AI is important.
- AC2.1 Explain bias in AI systems.
- AC2.2 Describe ways to reduce unfair outcomes.
- AC3.1 Identify privacy risks linked to AI.
- AC3.2 Explain the importance of data security.
- AC4.1 Describe principles of responsible AI use.
- AC4.2 Apply responsible AI principles to a simple scenario.
Unit aim
This unit develops learner understanding of ethical, legal and social issues linked to artificial intelligence.
Indicative content
AI ethics, fairness, bias, transparency, accountability, privacy, security, data protection, misinformation, academic integrity and responsible AI guidelines.
Assignment brief
Learners are required to analyse AI ethical issues through a case study and recommend responsible AI practices.
Unit 6 of 6
AI Project
IQA-L3-AI-U06
Learning outcomes
- LO1 Be able to plan a simple AI-related project.
- LO2 Be able to use AI tools to support a project.
- LO3 Be able to present project outcomes.
- LO4 Be able to review personal performance.
Assessment criteria
- AC1.1 Identify a suitable AI-related project topic.
- AC1.2 Produce a simple project plan.
- AC2.1 Use AI tools to support project activities.
- AC2.2 Record evidence of project development.
- AC3.1 Present project outcomes clearly.
- AC3.2 Explain how AI supported the project.
- AC4.1 Review strengths and weaknesses of the project.
- AC4.2 Identify areas for future improvement.
Unit aim
This unit allows learners to apply knowledge and skills gained from the programme through a simple AI-related project.
Indicative content
Project planning, AI tool selection, research, data use, problem-solving, presentation skills, reflection and improvement planning.
Assignment brief
Learners must complete a small AI-related project and submit a project report with evidence and reflection.
Progression routes
Typical routes after completing this qualification.
Progression
Progression to Level 4 study, further vocational learning or entry-level employment.
Learning outcomes summary
- LO1 Understand the basic concepts of artificial intelligence.
- LO2 Understand the role of AI in modern society.
- LO3 Understand common AI tools and applications.
- LO4 Understand ethical considerations in the use of AI.
- LO1 Understand the digital skills required for AI-related work.
- LO2 Be able to use digital tools for research and productivity.
- LO3 Understand data handling basics.
- LO4 Be able to present digital information effectively.
- LO1 Understand the importance of data in AI.
- LO2 Understand different types of data.