Artificial Intelligence Overview

Overview

In this course, you will learn how to define and differentiate between Artificial Intelligence (AI) and Machine Learning (ML), the philosophies underpinning AI, and how to identify and use appropriate tools to build AI/ML modelling for real-world problem-solving. You will learn how to construct simple correlation and regression models before constructing more complex modelling to solve problems using a variety of evolutionary algorithms.

 

Course Overview

This short course covers:  

Weeks 1-3

  • AI Foundations: Artificial Intelligence (AI) vs. Machine Learning (ML)
  • Learning paradigms: Supervised learning, unsupervised learning and reinforcement learning.
  • Real-life applications of ML – case studies and Search algorithms

Weeks 4-6

  • Linear models for classification
  • Linear models for regression
  • Lazy learning methods: K nearest neighbour method

Weeks 7-10 

  • Nonlinear methods, Neural networks
  • Neural networks, MLP, Back Propagation
  • Deep learning
  • Ethical considerations of AI and ML

 

Course Aims

Gain skills:

  • Discover the fundamentals of artificial intelligence and machine learning.
  • Introductory, hands-on experience with some tools and techniques.

Gain knowledge:

  • Gain an appreciation of where AI/ML technologies fit within industry business processes.

 

Benefits

The learner will leave the session with:

  • Organisations can benefit from understanding if AI/ML techniques apply to solving their business problems or improving their business processes.
  • Organisations can remain competitive where necessary by using AI/ML processes to augment existing processes.
  • The learner will benefit through the discovery and appreciation of AI/ML technologies
  • The learner will apply limited hands-on skills to get started with AI/ML technologies in their organisation.
  • The learner will know the wider context of AI/ML within industry and society.

 

Audience 

No prior experience is necessary, although a background in IT, computing, or computer science would be beneficial.

Some basic mathematical or statistical knowledge at a GCSE higher level or equivalent would be useful, but not essential.

 

Award

After completing the course, learners will receive a certificate of attendance. Learners who complete the assignment will also receive 20 credits, which can be used for future learning. 

 

Funding

The Staffordshire E-Skills & Entrepreneurship Gateway (SEGway) is part funded by the European Social Fund.

Delivery method
Distance learning
Location
Online
Duration

10 weeks (one 2-hour session per week) 

Start date

Thursday 9 February 2023

School
School of Digital, Technologies and Arts
Award
Certificate of Attendance

Entry requirements

This training course is exclusively available to Stoke-on-Trent and Staffordshire based students, graduates and businesses with a maximum of 250 employees (SMEs).

Cost

This course is free to all Staffordshire based students, graduates, start-ups and small to medium-sized businesses (SMEs). 

Staff

Joideep Banerjee

P/T Lecturer (Hrly) - Computing

How to apply

To apply for this course, please email employers@staffs.ac.uk.

UK University

StudentCrowd University Awards 2022

for Job Prospects

StudentCrowd University Awards 2022

for Student Satisfaction

Complete University Guide 2022

for Social Inclusion

The Times and The Sunday Times Good University Guide 2023

for Course Content

StudentCrowd University Awards 2022

of Research Impact is ‘Outstanding’ or ‘Very Considerable’

Research Excellence Framework 2021