Existing internal control measures need to be complemented with AI-specific practices that address the data integrity risks in the artificial intelligence data life cycle. Countering risks that arise when using artificial intelligence systems requires planning, preparation, validation, processing, output, distribution, and decommissioning controls. 

Internal controls are required throughout the life cycle of an artificial intelligence system. They are influenced by multiple factors, including societal, commercial, organisational, and technical considerations, each of which can vary or at times be combined with other stages during the life of a system. This course will provide an understanding of the internal controls needed for data in AI systems.

Description

This Internal controls for AI systems course will address:

• data life cycle
• system development life cycle
• system deployment
• system operation and control
• data availability, reuse, acquisition, collection, transformation, authored or curated, validation
• data types and volume
• source of the data and provenance
• data processing, synthesized and generated data
• data outputs and distribution
• format of the data
• what the data represent
• data properties and choice of algorithm for model development
• data licensing requirements
• data security
• data protection
• data availability and system resilience
• data safety requirements.

Course details

This two-day course ends with a short quiz. This is necessary to confirm knowledge transfer to the attendee.

This in-person classroom course takes place in Dublin, Ireland on the advertised dates.

Cancellation/Refund Policy

The organiser reserves the right to cancel a training event, at any time prior to the actual start of the course. In such circumstances, participants will be advised as soon as possible by telephone or email, and the purchaser will be entitled to a full refund of the course fee, or the course fee can be credited towards a future course, at the purchaser’s choice. Any repayment will be by the same method as the payment. The organisers will not be responsible for any loss or expenses incurred by the participant or purchaser, howsoever arising, irrespective of the length of notice given.

Cancellation by the participant

Notice of a training participant’s intention to cancel a course registration must be made in writing (letter, fax or email), and in good time. In such cases, participants will have the option of nominating a replacement to attend in their place. Participants whose cancellation request is received more than 10 working days prior to the start date of the training course will receive a full refund or credit. Participants whose cancellation request is received less than 10 working days prior to the start date of the training course will be charged 100% of the full fee. Participants who fail to attend the course will be charged 100% of the full fee.

Payment

Payment terms are strictly 30 days from the date of invoice or prior to course commencement, whichever comes earliest. A place on the course is not guaranteed until payment in full has been received.

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