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AIX

AIX Signature Programme

  • Introduction

APEX ED’s AIX Signature Programme provides an academic and practical design framework for learners in the field of Artificial Intelligence. The OTHM framework has been selected for its flexibility and Ofqual recognition; however, the programme is rigorous and extend well beyond the scope of the standard OTHM learning outcomes. The aim is to ensure that students graduate with the skills, certifications, and real-world experience to enter the AI job market globally. Ultimate graduation from the full programme will be contingent upon the successful completion of a broad final assessment process. This includes a comprehensive examination, demonstration of applied AI skills, effective communication, and professional competencies such as CV writing, LinkedIn profile development, and interview readiness.

  • Building career-Ready AI Skills | AIX Signature Programme
  • Programme Overview

The APEX ED AIX Signature Programme is uniquely designed in alignment with real-world employer demands. The programme is structured in 3 Blocks, starting with a 3-month preparatory Block covering IBM Python for Data Science, AI & Development and IBM Machine Learning with Python & Scikit-learn Professional Certificate. Those who complete Block 1, may proceed with Block 2 as the academic core consisting of a 9 month Ofqual-Accredited UK Level 7 Postgraduate Diploma. Professionals who are already in the industry and intend to acquire AI knowledge may only choose to complete Block 2 and opt out from participating in Block 3, the Practicum part of the programme. Block 3 builds upon the theoretical modules from Block 2 with practical, industry-recognised certifications from IBM, Microsoft, AWS, and Google Cloud, in addition to robust career-readiness components.

  • Programme Structure
  • Block 1 - Foundational Block (3 months)
  • IBM Python for Data Science, AI & Development
  • IBM Machine Learning with Python & Scikit-learn Professional Certificate
  • Block 2 - PGD Block (9 months)

Overview


The objective of the OTHM Level 7 Diploma in Artificial Intelligence is to equip learners with an in-depth understanding of contemporary Artificial Intelligence (AI) methodologies, practices, and the evolving technological landscape. This qualification aims to explore both the theoretical underpinnings and practical applications of AI, providing learners with the expertise to engage in discussions, research, and the development of AI systems across various domains.
Upon successful completion of this qualification, learners will possess the knowledge and skills required to work in roles related to AI research, development, and implementation. They will be equipped to pursue further studies or professional roles in sectors such as technology, healthcare, finance, sustainability, and public policy, contributing to the ongoing evolution of AI in society.

  • Entry Requirements
  • Be 21 years or older at the beginning of the course; or
  • Relevant Level 6 qualification. Normally an Honours degree (or equivalent) from a recognised institution.
  • Demonstration of relevant professional experience. Applicants should have at least 3 years professional experience in the field (learners must check with the delivery centre regarding this experience prior to registering for the programme).

    And must have an:

    – Understanding of Object Oriented Programming (OOP).
    – Ability to program in Python.
    – Understanding of two or more of the following mathematical and scientific Python libraries: 'numpy', 'pandas', 'scipy', and 'matplotlib'.

Equivalences

The OTHM Level 7 diplomas on the Regulated Qualifications Framework (RQF) are at the same level as master’s degrees. However, they are shorter (120 credits) and learners will have to proceed to the dissertation stage (60 credits) with university to achieve a full masters programme.

  • Qualification Structure

The OTHM Level 7 Diploma in Artificial Intelligence consists of 6 mandatory units, 120 credits, 1200 hours Total Qualification Time (TQT) and the recommended Guided Learning Hours (GLH) for this qualification is a minimum of 600 hours.

  • Mandatory Units And Credits

MODULECREDITSDURATION
(MONTHS)
Introduction to Artificial Intelligence202
Artificial Intelligence and Sustainability201
Ethics, Fairness and Explanation in Artificial Intelligence201
Deep Learning202
Intelligent Agents202
Research Methods201
Total Credits & Months1209
Introduction to Artificial Intelligence
Credits: 20
Duration: 2 Months
Artificial Intelligence and Sustainability
Credits: 20
Duration: 1 Month
Ethics, Fairness and Explanation in Artificial Intelligence
Credits: 20
Duration: 1 Month
Deep Learning
Credits: 20
Duration: 2 Months
Intelligent Agents
Credits: 20
Duration: 2 Months
Research Methods
Credits: 20
Duration: 1 Month
Total
Credits: 120
Duration: 9 Months
  • Block 3 - Practicum Block (6 months)

Block 3 will consist of Career Readiness Components and Micro-credentials

Career Readiness Components

  • Resume Building Workshops
  • LinkedIn Profile Optimisation
  • Interview Coaching and Mock Sessions
  • GitHub Portfolio with Capstone and Mini Projects
  • Targeted Job Roles and Micro-credentials
TRACK TARGETED ROLES INDUSTRY
MICRO-CREDENTIAL
TRACK A
Analyst 		AI / BI / Data Analyst Microsoft PL-300:
Power BI Data Analyst (Associate)
TRACK B
Applied ML* 		ML Engineer
Data Scientist 		Microsoft DP-100:
Azure Data Scientist

or

AWS Certified Machine Learning Engineer
TRACK C
ML Ops 		ML Engineer Google Cloud Professional Machine Learning Engineer

or

AWS Certified Machine Learning Engineer (Associate)

Track A – Analyst
Targeted Roles
  • AI Analyst
  • BI Analyst
  • Data Analyst
Industry Micro-Credential

Microsoft PL-300
Power BI Data Analyst (Associate)

Track B – Applied ML*
Targeted Roles
  • Machine Learning Engineer
  • Data Scientist
Industry Micro-Credential

Microsoft DP-100
Azure Data Scientist

OR

AWS Certified Machine Learning Engineer

Track C – ML Ops
Targeted Roles
  • Machine Learning Engineer
Industry Micro-Credential

Google Cloud Professional Machine Learning Engineer

OR

AWS Certified Machine Learning Engineer (Associate)

*The Applied ML Track consists of two credentials, one of which may be chosen based on the student’s preference. Students who wish to pursue a more ML-focused path may opt for the AWS certification.

Students will be given preparatory support for the final exams of these credentials through access to Cousera courses by the relevant vendor for exam and test preparation through platforms like Whizlabs, MeasureUp etc. Furthermore, students will receive portfolio building training including additional support to deploy their projects from the micro-credentials as portfolio projects.

  • Targeted Job Roles and Micro-credentials
TARGETED ROLE
TRACK
AI / BI / Data Analyst (Junior to Associate)
A
Data Scientist (Junior to Associate)
B
Machine Learning Engineer (Junior)
B & C
AI Ethics & Governance Officer
GENERAL
AI Project Coordinator or Research Assistant
GENERAL
  • Future-Proofing Careers in the Age of Artificial Intelligence
  • Key Facts
  • Location: Blended
  • Start dates: Every 3 months
  • Part time: 1 year+
  • Progression

The OTHM Level 7 Diploma in Artificial Intelligence enables learners to progress into or within employment and/or continue their further study.
As this qualification is approved and regulated by Ofqual (Office of the Qualifications and Examinations Regulation), learners may be eligible to progress to Master’s top-up at many universities in the UK and overseas with advanced standing.

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