BR6006 - Artificial Intelligence

At The Bridge you learn through a blended approach where short, focused and interactive face-to-face sessions are underpinned by guided and independent online learning. Your attendance for scheduled activities is monitored regardless of whether you are on campus or joining the session remotely. This ensures you access all of the learning opportunities which have been purposefully designed for your success.

A range of teaching and learning approaches are adopted to accelerate your learning in this module.

During the first week of this module, you will receive information about the module and Teaching & Learning Plan. The teaching and learning plan (TLP) sets out
• Learning outcomes and overall module and programme aims
• Teaching, learning and assessment strategy
• Teaching schedule
• Directed reading references (text and journals) and core texts for the module
• References to data sources and details of lab activities

You will also receive the assessment brief which sets out the formative and summative assessments throughout the module.

There are three key sources of academic support available to you during your time at the Bridge in addition to Ask4Help who are available 24/7 for general queries related to your studies.

Your Module Tutor
Your module tutor is responsible for your learning outcomes on the module. They deliver the workshops and provide guidance in relation to learning and assignments. They develop all of the key resources and make them available through the eLP (electronic learning portal module) Blackboard, which is used to provide support materials, interactive learning tasks and give you regular opportunities to test and get feedback on your learning. You will be given both written and verbal feedback and guidance on your work and progress during the semester by your module tutor.

Your Learning Mentor
On programme, you will have your in-person and online engagement activity tracked against the learning plan with key check-in points built into the academic calendar to ensure you maximise your learning potential. Engagement with formative assessments will also be used by the learning mentor to discuss any action planning required to ensure success.

Academic Skills Team
The Bridge aspires to build a range of student skillsets, including digital skills, academic writing and discourse, working alone and in teams. Your learning mentor may refer you a dedicated academic skills team which is based in the centre. Here you can attend drop-ins or schedule 1-1 sessions on issues which have been identified at the diagnostic stages of the programme however you may also have self-identified areas for your own growth and self-refer yourself for support.

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

Knowledge & Understanding:
ML01 - Demonstrate knowledge, and critical understanding, of facts, concepts, principles, theories, techniques, and technologies related to computing, computer science, data science and Artificial Intelligence (AI).
ML02 - Demonstrate knowledge, and critical understanding, of the considerations organisations should take when implementing Machine Learning and Artificial Intelligence (AI) approaches.

Intellectual / Professional skills & abilities:
ML03 - Specify, design and construct simple computer- and AI- based systems

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
ML05 – Demonstrate an awareness of the global, ethical, and cultural issues related to computing, and specifically AI and data - and its societal implications for equality and diversity.

You will receive formative feedback throughout the module including at the following checkpoints:-

•Week 2: Navigating the course materials
•Week 4: Completing the in-module reflective tasks
•Week 6: Completing the in-module knowledge checks and tasks

This module is assessed by submitting a programming project utilising AI. In total it will be 2500 words including AI model designs and building a no code AI-based service for either a case study/ real world application

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This module will give you a knowledge of machine learning (ML) and artificial intelligence (AI) concepts and how to implement common ML and AI in the workplace Ideed, employers are seeking talented individuals who can work as members of a team in understanding, analysing, and designing AI and manchine learning solutions leading to sustainable growth, change and impact and applying effective, responsible and ethical AI-enabled techniques.

In order to develop and demonstrate your practical understanding of AI and Machine Learning you will be assessed by means of a programming project utilising AI.

This is the focus of this mdoule and will prepare you for roles in Data Science and AI Engineering.