Category

Computing & AI

Level

Level 5

Qualification Number

610/6116/5

Total Credits

30

Course Overview

This two-unit, 30-credit qualification builds on the Level 4 Award and extends specific Artificial Intelligence knowledge and skills by requiring learners to get to grips with underpinning advanced statistics and natural language processing. This qualification would be particularly suited to learners with a background in maths and computing looking to upskill their knowledge and skills in this specific area.

Grading
Graded with Pass, Merit and Distinction.
ATHE Level 5 Certificate in Artificial Intelligence (30 credits)
Pass 90 – 107
Merit 108 – 134
Distinction 135
Advanced learner loans available in the UK – to check if funding is available see the latest Qualification Catalogue here.
For the progression routes visit our progression routes page.

Delivery Mode
This qualification can be delivered either in the classroom, via distance learning or blended.

Additional
This qualification is eligible for UCAS points. To find out how much points your qualification is worth, please visit the UCAS Tariff Calculator here.

Typical Age

These qualifications are designed for learners who are typically aged 18+.

Qualifications

The entry profile for learners is likely to include at least one of the following:

Prior study in computing or related subjects at Level 4 or above, or a Level 4 qualification, for example, an ATHE Level 4 Diploma/Extended Diploma in Computing; a Higher Technical Qualification (HTQ) in a computing-related subject
Other equivalent international qualifications
Language

For those whom English is not their first language we recommend the following standards of proficiency in English language skills or an approved equivalent for this qualification:

IELTs 5.5
Common European Framework of Reference (CEFR) B2
Cambridge English Advanced (CAE) 162 or above
Pearson Test of English (PTE) Academic 42-49

Details Unit Aims
Advanced Statistics for Data Science
Credits: 15
Mandatory: Yes
  1. Understand ways to evaluate the performance of algorithmic models
  2. Understand statistical prediction and regression
  3. Understand and apply traditional statistical machine learning algorithms
Foundations of Artificial Intelligence for Data and Language
Credits: 15
Mandatory: Yes
  1. Understand how machines learn from data
  2. Understand text mining algorithms
  3. Understand the challenges of implementing Generative AI Models
Menu
ATHE
Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.