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Assist in the deployment of artificial intelligence solutions

URN: TECIS804301
Business Sectors (Suites): IT(Data Science)
Developed by: e-skills
Approved on: 2020

Overview

This standard identifies the competences you need to assist in the development and implementation of artificial intelligence (AI) solutions in accordance with approved procedures. In order to do this, you are required to have the knowledge, skills and understanding necessary to apply a range of artificial intelligence methods to solve specific problems. Artificial intelligence is a general-purpose technology with many potential applications, and so needs to be contextualised to solve or automate specific outcomes. A typical artificial intelligence solution analyses it's environment and takes actions in response, this often revolves around the use of algorithms that operate on a range of data sources.
 
You will be able to work with data sources in order to prepare data and test the outcomes of artificial intelligence algorithms on data. You will work under close supervision and follow instructions and procedures, taking responsibility for the quality, accuracy and efficacy of the artificial intelligence work that you carry out.

Your underpinning knowledge will provide an understanding of the principles of artificial intelligence, potential applications and use of tools, methods and trends. You will have an understanding of the artificial intelligence solutions being developed and implemented, at an adequate depth to provide a sound basis for carrying out the artificial intelligence work to meet organisational needs.

This activity can be increasingly found in any sector or organisation and in particular those associated with the analyses of high-volume or complex data sets using advanced computational methods. It is likely to be undertaken by people working as Junior AI Data Specialists, Junior AI Data Technologists, Junior Data Analysts, Junior AI Data Engineers etc.

Performance criteria

You must be able to:

  1. assist artificial intelligence delivery teams with model deployment into production environments in a supportive way and within the required timescale

  2. assist in monitoring the status and performance of production analytics models to ensure they are up to date and delivering valid results

  3. produce status reports for deployed artificial intelligence models to a range of stakeholders to evaluate model outcomes

  4. assist with checking data quality using approved tools and techniques to verify conformance with policies and procedures 

  5. assist with the implementation of artificial intelligence solutions into production environments to address business problems

  6. assist in validation and testing the accuracy of model solutions

  7. create documentation to inform others on the role of artificial intelligence models and solutions within the organisation

Knowledge and Understanding

You need to know and understand:

  1. the types of problems that artificial intelligence solutions can solve

  2. the reasons why production models typically need to be assessed and recalibrated and how this is managed

  3. the role of data stewards in an organisation to maintain compliance with policy and/or regulatory obligations

  4. the data quality management techniques used to maintain data accuracy 

  5. the range of applications of artificial intelligence used within the organisation 

  6. the tools used to collect, store, analyse and visualise data

  7. the range of artificial intelligence tools and techniques that can be used to solve problems
  8. the industry standard statistical methods that are used for artificial intelligence solution development
  9. how to review requirements specifications in order to confirm the solution aims and objectives

  10. how to test artificial intelligence solutions to identify errors and verify outcomes are correct

  11. the functional and technological limitations of current artificial intelligence technologies and methods

  12. the distinction between artificial intelligence and machine learning
  13. the artificial intelligence ethical frameworks used to guide ethical artificial intelligence operations

Scope/range

Scope Performance

Scope Knowledge

Values

Behaviours

Skills

Glossary

Links To Other NOS

External Links

Version Number

1

Indicative Review Date

2023

Validity

Current

Status

Original

Originating Organisation

ODAG Consultants Ltd

Original URN

TECIS804301

Relevant Occupations

Software Development, Data Operations

SOC Code

2139

Keywords

Artificial intelligence, data science