LICQual Level 3 Diploma in Artificial Intelligence in Education and Learning

The LICQual Level 3 Diploma in Artificial Intelligence in Education and Learning is a high-level qualification designed for professionals who aim to lead innovation and digital transformation in educational settings. As artificial intelligence (AI) becomes increasingly integral to learning environments, this diploma equips participants with strategic, technical, and pedagogical expertise to design, implement, and evaluate AI-driven education solutions. It prepares learners to take on leadership roles in shaping the future of education through intelligent technologies.

This comprehensive program bridges advanced AI theory with real-world application in teaching, learning, and institutional planning. Learners will explore the use of AI in personalized learning systems, curriculum optimization, real-time learner analytics, and intelligent decision support. The LICQual Level 3 Diploma in Artificial Intelligence in Education and Learning also emphasizes ethical, inclusive, and sustainable practices, ensuring participants are capable of applying AI responsibly in diverse educational contexts.

The course includes topics such as strategic AI planning, KPI evaluation, cognitive computing, educational app development, and institutional AI pilot projects. Each unit offers a mix of theoretical knowledge, case-based analysis, and project-based assessments, empowering learners to develop practical AI solutions tailored to educational needs. The diploma also includes a capstone project, enabling participants to present an AI strategy aligned with institutional goals.

Upon completion, learners will be equipped to lead AI integration efforts, build AI-enhanced learning architectures, and collaborate with EdTech industry stakeholders. They will gain the skills to apply big data, predictive analytics, and automation in ways that improve learner outcomes, teaching practices, and administrative efficiency. The course also supports capacity building for digital leadership and prepares professionals to influence policy and digital transformation agendas at institutional, national, or international levels.

The LICQual Level 3 Diploma in Artificial Intelligence in Education and Learning is ideal for academic leaders, education managers, instructional designers, EdTech consultants, and policy advisors.

As the global education sector embraces AI to meet modern learning challenges, this diploma ensures professionals are equipped with the forward-thinking expertise required to lead confidently in an AI-powered education landscape. This qualification is a critical step for those committed to driving impactful and ethical change in the future of learning through artificial intelligence.

Course Overview


Qualification Title

LICQual Level 3 Diploma in Artificial Intelligence in Education and Learning


Total Units

6

Total Credits

60

GLH

240

Qualification #

LICQ2200511


Qualification Specification

Download Qualification Specification

To enroll in theLICQual Level 3 Diploma in Artificial Intelligence in Education and Learning applicants must meet the following criteria:

  • Age Requirement: Applicants must be at least 18 years old.
  • Educational Requirements:Applicants must hold a Level 2 Diploma or an equivalent qualification in education, information technology, or a related discipline to demonstrate readiness for advanced study in AI and education.
  • Experience: At least 2 years of professional experience in teaching, training, curriculum development, or education technology is recommended to engage effectively with the course content.
  • English Language Proficiency: Learners should have English proficiency at CEFR Level B2 or higher (such as IELTS 5.5 or equivalent) to comprehend technical materials and participate confidently in discussions and assessments.

Qualification#

Unit Title

Credits

GLH

LICQ2200511-1

Advanced Machine Learning and Deep Learning for Education

10

40

LICQ2200511-2

Development of AI Algorithms for Adaptive Curriculum Delivery

10

40

LICQ2200511-3

Research Methodologies for AI in Education

10

40

LICQ2200511-4

Regulatory Compliance and Governance in AI-Driven Learning Systems

10

40

LICQ2200511-5

Institutional Transformation through Artificial Intelligence

10

40

LICQ2200511-6

Research Dissertation: AI Innovation for Educational Equity and Excellence

10

40

By the end of this course,applicants will be able to:

1. Advanced Machine Learning and Deep Learning for Education

  • Analyze advanced machine learning and deep learning models and their relevance to personalized education.
  • Apply AI models to enhance adaptive learning, performance prediction, and intelligent tutoring systems.

2. Development of AI Algorithms for Adaptive Curriculum Delivery

  • Design AI-driven algorithms tailored for dynamic and adaptive curriculum frameworks.
  • Evaluate algorithm performance based on learner engagement, progress, and feedback mechanisms.

3. Research Methodologies for AI in Education

  • Apply qualitative and quantitative research methods to investigate AI applications in education.
  • Develop research proposals and data collection strategies aligned with AI-focused educational studies.

4. Regulatory Compliance and Governance in AI-Driven Learning Systems

  • Interpret legal, ethical, and institutional policies governing AI in education.
  • Assess the implications of data protection laws, algorithmic bias, and accountability in AI deployment.

5. Institutional Transformation through Artificial Intelligence

  • Formulate strategic AI integration plans for education systems at the institutional level.
  • Lead change initiatives that promote sustainable and scalable AI-driven transformation in learning environments.

6. Research Dissertation: AI Innovation for Educational Equity and Excellence

  • Conduct an independent research project addressing a critical issue in AI and education.
  • Present data-driven recommendations that support equity, inclusion, and innovation through AI solutions.

This diploma is ideal for:

  • Senior educators and academic leaders aiming to lead AI-driven educational transformation
  • Curriculum directors developing adaptive and data-driven instructional models
  • Education technology specialists involved in deploying machine learning systems in schools or universities
  • Instructional designers seeking advanced knowledge in AI-based curriculum delivery
  • Education policy makers shaping national or institutional AI frameworks
  • Researchers focusing on AI innovation, educational equity, and deep learning methodologies
  • Data analysts in education exploring the predictive potential of big data and AI tools
  • EdTech developers and solution architects designing intelligent educational platforms
  • Higher education administrators overseeing AI integration across departments
  • Corporate learning and development leaders implementing AI-based training systems
  • Education consultants advising organizations on strategic AI adoption and compliance
  • Quality assurance professionals evaluating the effectiveness of AI in teaching and learning
  • Project managers responsible for institutional AI transformation initiatives
  • NGO professionals working on AI-enhanced education programs for underserved communities
  • Government officials driving AI policy and digital innovation in the education sector
  • Professionals transitioning into educational AI roles from technology or research backgrounds
  • International education leaders focused on scaling AI for global learning equity and excellence

Assessment and Verification

All units within this qualification are subject to internal assessment by the approved centre and external verification by LICQual. The qualification follows a criterion-referenced assessment approach, ensuring that learners meet all specified learning outcomes.

To achieve a ‘Pass’ in any unit, learners must provide valid, sufficient, and authentic evidence demonstrating their attainment of all learning outcomes and compliance with the prescribed assessment criteria. The Assessor is responsible for evaluating the evidence and determining whether the learner has successfully met the required standards.

Assessors must maintain a clear and comprehensive audit trail, documenting the basis for their assessment decisions to ensure transparency, consistency, and compliance with quality assurance requirements.

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