ARTIFICIAL INTELLIGENCE (AI) DATA SPECIALIST

HIGHER APPRENTICESHIP

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The Level 7 Artificial Intelligence Data Specialist apprenticeship programme is designed to enable learners to develop a deep technical knowledge that allows the discovery and creation of these new data-driven AI solutions.

These solutions should help to automate and optimise business processes and to support, augment and enhance human decision-making.

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Summary

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About this course

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Careers

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Modules

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Learner support

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Entry requirements

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Fees & finance

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Fees

This programme is fully funded by your employer through the Apprenticeship Levy

Level Of Study

Level 7

Award

Artificial Intelligence (AI) Data Specialist Higher Apprenticeship

Apprenticeship Standard

Level 7 Artificial Intelligence (AI) Data Specialist

Apprenticeship Certificate

ESFA

Entry Requirements

An honours degree (2:2 or above)

English Language Requirements

GCSE at Grade C

Mode Of Study

Part-Time, Blended and Work-based Learning

Duration

15 months + EPA, typically 6 months

Assessment Methods

Research-informed assignments and work-based projects, weekly quizzes, End Point Assessment

Start Date

October, January, April and July

Locations

Live online learning (face to face for closed cohorts only, dependent upon numbers and location - London, Birmingham, Manchester, Leeds)

Course overview

This programme is delivered by QA with the apprenticeship certificate awarded by British Computer Society.

PLEASE NOTE: To be eligible for one of our Degree or Higher Apprenticeship programmes, learners must:
(1) be currently in full-time employment and based in the UK
(2) be interested in completing a Degree or Higher Apprenticeship with their current employer

You will be equipped to work in a range of Machine Learning and AI jobs. These include:

  • AI strategy manager
  • AI Engineer
  • AI specialist
  • Director AI
  • Machine Learning Engineer
  • Machine Learning Specialist

All modules are core and worth 20 credits unless otherwise stated.

AI Modules

Data Science Principles

This is the first module of the programme and provides the foundation. Data Science is about using data to create knowledge which will advance business or society. Its subject area comprises an intersection of mathematic/statistics, computing, and domain knowledge. As such it is broad.

In this module we overview all areas in data science from data sourcing through data architecture and organisation through statistical analysis to machine learning. The main focus though is on data architecture and statistical analysis. You will learn how to identify, organise, and analyse an organisation’s data assets and you will implement a data-driven project idea that advances the organisation’s knowledge base.

AI and Data Science Professional Practice

A key element of your journey towards becoming an AI Data Specialist is your ongoing skills development. This module requires you to engage in a recognised CPD (Continuing Professional Development) programme and reflect upon how such learning can be embedded back into the workplace. To enable this we consider the following areas:

  • Identification of a relevant skills need and subsequent CPD programme which will be followed as part of this module.
  • Design of a journal to log your professional development whilst on this programme.
  • Strategies to embed learning from your CPD into practice including developing ideas and plans for work-based projects.

Programming for Artificial Intelligence

In this module, you will develop knowledge and skills in programming methods for AI. The module combines both theoretical and practical application approaches, enhancing the skills required to engage in Data Science problems in current and realistic business environments. The programming language used is Python. While exploring relevant libraries, you will learn about algorithms and methods for data preparation, statistical analysis, and machine learning with a focus also on the mathematics behind them. You will practice and learn about supervised and unsupervised learning algorithms as well as gaining knowledge on how to optimise, apply metrics and evaluate models produced.

Machine Learning using Cloud Computing

In this module you will develop knowledge and skills that will enable you to tackle a realistic machine learning problem, using advanced machine learning techniques. You will also learn how to implement machine learning based solutions using the cloud and how to evaluate their performance. The major cloud providers have advanced platforms for machine learning. You will select one of these platforms to explore. The main topics covered in this module include deep learning using various types of neural network , reinforcement learning, optimisation techniques, ensemble techniques, scalable infrastructures, high performance architecture, and cloud services and platforms for AI.

AI and Digital Innovation

This module will provide a general introduction to AI and digital innovation that centres on organisational examples such as business, finance, health, and energy. Successfully completing the module will provide you with an understanding of the application of AI and its role in digital innovation. We also highlight an innovative area currently gaining traction across sectors, that of generative AI and in particular the use of large language models and transformers. You will explore what innovations are possible through use of natural language processing (NLP) with or without the support of transformer technology. As well as reviewing general AI innovation, you will develop knowledge and skills in NLP and transformer technology as current examples of innovation.

Disruptive Leadership for Sustainable Strategy

This module is taken at the end of the learning period so serves to bring the technical learning together and highlight how the various methods can be harnessed as part of a sustainable data strategy. Leadership techniques and approaches are examined in the context of rapid, innovative, and radical change that is impacting industry ecosystems. You will consider how data operations can be streamlined for efficiency and agility as well as the key people roles and interactions that are needed for sustainable data strategy. You will investigate a detailed scenario and answer questions on how a particular AI project can be realised in the face of typical constraints that an organisation might face. Legal, social, and ethical considerations will also be explored.

Skills Coach

Your Skills Coach will be your primary, non-academic contact, supporting you in the successful progression and completion of your apprenticeship. Your coach will support you in reviewing your progress and collecting evidence of your practice at work to integrate into your module assessments and final endpoint project/assessment. They are also a point of contact for queries, concerns, or general support.

Your Coach can help you with:

  • Coaching and supporting work-based learning activities
  • Reviewing your progress with your apprenticeship portfolio progress
  • Help with achieving your EPA
  • Advice and guidance on mitigating (extenuating) circumstances processes and potential breaks in learning.

Workplace Mentor

A Workplace Mentor will be appointed by your employer and typically would be someone you work with. Your workplace mentor will be familiar with the apprenticeship programme and its workplace requirements. They will facilitate the workplace learning opportunities to enable you to meet the requirements of the higher apprenticeship standard.

ACE Team

They are the Academic Community of Excellence (ACE) Team, and amongst the team, have many years of experience providing academic guidance to students on subjects such as how to write in an academic style, how to read smarter rather than longer and how to reference accurately.

The ACE Team will provide you with support on academic matters outside of the classroom. You can also book 1-1 meetings (mainly online) with the ACE Team and get feedback on your academic style of writing, references and critical report writing.

How can the ACE Team support you?

  1. “Welcome to the World of Academia” online workshops: if you wish to have an introduction to or a review of the different aspects of academic life before starting your programme, then please do join their online workshops (non-obligatory – but much to be gained from joining!).
  2. One-to-one tutorials: you can book a virtual 30-minute tutorial to discuss your academic development skills, such as paraphrasing, referencing and academic writing.
  3. Online workshops: we offer ongoing support workshops on a variety of academic subjects such as structuring an argument, academic style and criticality.
  4. Our own-created range of learner materials: we have also developed a wide range of ACE Team created materials based on common questions and academic needs.

QA Welfare Services

Our Student Welfare Team is on hand to assist you throughout your studies. Some degree or higher apprenticeship learners have additional learning needs which the Welfare Team can assist with, or they might help you with personal circumstances that are affecting your studies.

Standard Entry Requirements

Applicants will usually have obtained: an honours degree (2:2 or above) in an appropriate discipline, or with the appropriate aptitude for a role in technology.

Non-standard entry with work experience

Relevant qualifications and/or work experience will be taken into consideration where the applicant has the judged potential to benefit from the programme. Requests will be considered on an individual basis where appropriate.

Informal Interviews

Informal interviews will be held where

  • The suitability of a candidate is in doubt and further evidence is sought.
  • The candidate presents an unusual set of qualifications taken or pending, and an appropriate conditional offer needs to be determined.
  • Candidates may need advice on the appropriateness of the programme.

Applicants invited for an informal interview will always be informed of its purpose.

There is no cost to you as an apprentice. Apprenticeships are fully funded through your employer.

If you are an employer, the maximum funding for this programme is £17,000. Expenses for travel to QA centres should be covered by the employer.

Find out how your organisation could benefit from the Apprenticeship Levy.

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