Category

Computing & AI

Level

Level 4

Qualification Number

610/6115/3

Total Credits

120

Course Overview

The Level 4 Extended Diploma in Computing and Artificial Intelligence (120-credit) builds on the broad Computing foundation offered by the Diploma and offers learners access to further and broader themes in Artificial Intelligence and Data Analysis. This qualification is aimed at those learners with interests in the relationship between Artificial Intelligence topics and Data Analysis.

Grading
Graded with Pass, Merit and Distinction.
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.

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:

A GCE Advanced level profile with achievement in 2 or more subjects supported by 5 or more GCSEs at grades 4/C and above
Other related level 3 subjects such as an ATHE level 3 Diplomas
An Access to Higher Education Certificate delivered by an approved further education institute and validated by an Access Validating Agency
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
IT Systems Development
Credits: 15
Mandatory: Yes
Programming and Scripting
Credits: 10
Mandatory: Yes
Data and Database Systems
Credits: 15
Mandatory: Yes
Practical Probability Theory for Data Science
Credits: 10
Mandatory: Yes
  1. Understand the principles of basic probability theory
  2. Understand the characteristics of common distributions
  3. Understands samples and populations
Methods and Tools for Analysis
Credits: 10
Mandatory: Yes
  1. Understand the common methods and tools used in data analysis.
  2. Understand the principles of user experience and domain context for data analysis.
  3. Understand the principal approaches to defining customer requirements for data analysis.
Data Preparation and Quality Risks
Credits: 10
Mandatory: Yes
Statistics for Analysing Datasets
Credits: 10
Mandatory: Yes
Analytical Impact through Data Visualisations
Credits: 10
Mandatory: Yes
Introduction to Artificial Intelligence
Credits: 10
Mandatory: Yes
  1. Understand intelligence and computer models
  2. Understand types of machine learning algorithms
  3. Carry out machine learning on a sample dataset
Synoptic Computing Project
Credits: 10
Mandatory: Yes
Legislation, Regulation, Ethics and Codes of Practice
Credits: 10
Mandatory: Yes
  1. Understand current legal and regulatory issues in IT
  2. Understand current ethical issues in IT
  3. Understand the need to create organisational cybersecurity policies and procedures
  4. Understand the role of professional bodies and industry certificatio
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