What will I learn in the Level 7 Diploma in Artificial Intelligence?

The Level 7 Diploma in Artificial Intelligence is a comprehensive programme that equips students with a broad range of skills in artificial intelligence, software development, and project management. This 120 credits diploma, awarded by the OTHM , covers key modules such as Web Designing, Database & SQL Programming, Cloud Computing & DevOps, Agile Project Management, Software Programming Principles and Practices in Java I, and Security Engineering.

• Foundational knowledge in programming principles and practices is established through modules like Software Programming Principles and Practices in Java I.
• Technical skills are developed through modules such as Database & SQL Programming and Cloud Computing & DevOps, providing students with a solid understanding of data management and cloud-based technologies.

If "What will I learn in the Level 7 Diploma in Artificial Intelligence?" is shaping your shortlist, use the points below to decide whether the Level 7 Diploma in Artificial Intelligence is the right next move.

• Align the credit value with any top-up, MBA, or professional route you already have in mind.
• Check that OTHM recognition matches what your employer or next university expects.
• Map the Level 7 Diploma in Artificial Intelligence outcomes to the role title or promotion you want in the next 12–24 months.

Core modules and themes from the Level 7 Diploma in Artificial Intelligence:

• Introduction to Artificial Intelligence — This unit aims to provide learners with a comprehensive introduction to the field of Artificial Intelligence (AI), covering both classical and modern approaches. Learners will explore the fundamental concepts, techniques, and philosophies underlying AI, including knowledge representation, reasoning, machine learning (including an overview of neural networks, the biological basis of neural networks as models of neurons in the brain, and non-linear activations analogous to spiking), and search algorithms. The unit also examines the ethical and philosophical implications of AI, as well as its future challenges. By completing this unit, learners will gain the foundational knowledge necessary to engage with more specialized AI topics in advanced studies.
• Artificial Intelligence and Sustainability — This unit aims to explore the intersection of Artificial Intelligence (AI) and sustainability, focusing on how AI can contribute to achieving the United Nations Sustainable Development Goals (UNSDGs). Learners will examine the role of AI in promoting resource efficiency, reducing environmental impacts, and supporting sustainable development. The unit will cover key concepts related to sustainable AI practices, such as energy efficiency, bias mitigation, and trustworthy AI, alongside practical applications of AI in areas like clean energy, waste management, and smart manufacturing.
• Ethics, Fairness and Explanation in Artificial Intelligence — This unit explores the ethical, fairness, and explanatory dimensions of artificial intelligence (AI), which are increasingly critical as AI systems become more integrated into various aspects of society. The module is divided into three main areas: the ethics of AI focusing on philosophical and ethical challenges such as the alignment problem, explainability in Large Language Models (LLMs), and responsibility attribution; fairness and bias in machine learning, examining the concepts of algorithmic fairness, bias detection, and mitigation strategies; and explainable AI (XAI), which addresses the need for transparency in AI decisions to ensure they are justifiable and understandable. By the end of this unit, learners will be equipped to critically engage with these issues, apply fairness measures, and implement explainable AI solutions using practical tools.
• Deep Learning — This unit aims to provide learners with a deep understanding of the fundamental concepts and advanced methodologies in deep learning. Learners will explore the theoretical underpinnings of modern deep learning techniques and their practical applications across various domains such as computer vision, natural language processing, and graph-based tasks. The module will enable learners to evaluate different deep learning approaches, understand their limitations, and apply these techniques to solve real-world problems. By the end of the unit, learners will have the knowledge and skills necessary to engage in deep learning research and practice.
• Intelligent Agents — This unit provides a broad introduction to the rapidly expanding field of agent-based computing. Learners will explore the key concepts and models involved in developing individual intelligent agents and their interactions in a multi-agent environment. A strong focus in this unit is placed on rational decision-making under uncertainty, automated negotiation, cooperation, and competitive behaviour in computational markets such as online auctions. Learners will gain practical experience by programming a trading agent in Python, which will compete in a class tournament within a simulated trading environment. The unit may also touch upon Large Language Models (LLMs) as agents to understand their growing role in intelligent systems.
• Research Methods — The aim of this unit is to develop learners’ ability to prepare for various types of academically based management research through the development and design of a research proposal. Learners will develop a critical understanding of the philosophical, practical and ethical concepts of research within the context of a relevant environment.

Check you are a strong match before you apply:

• The Level 7 qualification has been designed to be accessible without artificial barriers that restrict access and progression. Learners will be expected to hold the following:
• Level 6 Qualification or an Undergraduate Honour’s Degree or an equivalent international qualification OR
• Learners who have work experience and demonstrate drive and ambition to start their own business, or work in business development; OR
• Learners who possess a first degree in another discipline and want to develop their own business or shift careers. In certain circumstances, learners with considerable experience but NO FORMAL QUALIFICATION may be considered, subject to interview and being able to demonstrate their ability to cope with the demands of the programme. The qualification is offered in English.

1. Apply online — open enrolment for the Level 7 Diploma in Artificial Intelligence and complete your details.
2. Pay the £10 application fee — reserves your application and unlocks the next steps.
3. Upload documents and start — once accepted, access the learner portal and begin your modules.

Everything you need to decide is on this page — when you are ready, enrol above or use the application button at the bottom.