top of page
Lecturing

Computer Systems & Architecture (Level 2/I )

 

Principles of computer organisation, architecture and design; the hardware-software interface; control of peripherals; basics of networking.

The aims of this module are to:

  • provide an understanding of the fundamental concepts and principles of computer architectures

  • introduce the basic components of computer systems, their internal design and operation and their interactions

  • understand how computer hardware and software interact

  • provide a basic understanding of networking sufficient to support programming involving networks in other modules

On successful completion of this module, the student should be able to:

  • explain and apply the fundamental principles upon which the operation of modern computers is based

  • demonstrate a knowledge of the structure and organization of computer systems, including the role and operation of each of the component modules

  • explain and apply the fundamental concepts and issues involved in the control of peripherals, including interrupt-handling

  • explain the fundamental concepts and issues involved in computer networking, including the need for protocols, addressing and routing

  • Demonstrate a knowledge of the interaction between software and hardware, demonstrating how programs are executed

 

 

MCs/ICY Introdution to AI (Level 4/M - Level 1/C I) (>150 students)

 

This module provides a general introduction to artificial intelligence, its techniques, and main subfields. The principal focus of the module will be on the common underlying principles, such as knowledge representation, search, and learning.

The aims of this module are to:

  • Provide a general introduction to artificial intelligence, its techniques and its main subfields.

  • Give an overview of key underlying ideas, such as knowledge representation, reasoning, search, and learning.

  • Demonstrate the need for different approaches for different problems .

On successful completion of this module, the student should be able to:

  • Discuss the major issues and techniques in a variety of sub-fields of AI, such as vision, robotics, natural language processing, planning, probabilistic reasoning, and machine learning.

  • Apply a variety of standard AI techniques to simple examples.

  • Understand applications of AI to real world situations and possible problems and limitations.

Web pages:
http://www.cs.bham.ac.uk/internal/modules/2016/06-27112/

http://www.cs.bham.ac.uk/internal/modules/2016/06-27110/​

TA/Demonstrator at UoB

Intelligent Robotics 
    Lecturer: Jeremy L. Wyatt
    Artificial Intelligence is concerned with mechanisms for generating intelligent behaviour. When this behaviour occurs in the everyday physical world, with its uncertainty and rapid change, we find that all kinds of new problems and opportunities arise. We will try to understand some of these in the context of robotics. In a series of lectures we will look at some theories of how to sense the real world, and act intelligently in it. In a series of labs you will build your own robots to see how well (or badly) these theories actually work.
Web page: http://www.cs.bham.ac.uk/internal/courses/int-robot/

 

Intro to AI 
     Lecturers: Richard Dearden, Nick Hawes
    This module provides a general introduction to artificial intelligence, its techniques, and main subfields. The principal focus of the module will be on the common underlying ideas, such as knowledge representation, rule based systems, search, and learning. It will provide a foundation for further study of specific areas of artificial intelligence.
    
Robot Programming 
    Lecturer: Nick Hawes
    This module teaches basic AI and robotic programming skills through a series of team exercises using small, mostly prebuilt, robots. Regular exercises will give each team the skills to build up a robot capable of tackling a competitive, arena-based, task that includes a variety of AI-requiring sub-problems.
    
Computational Vision 
    Lecturer: Hamid Dehghani
    The module provides an introduction to computer vision, intended for students with some prior background in AI. Appropriate computational models, techniques and algorithms will be introduced, so that students can both understand the relevant literature and construct simple sofware systems.
    
Networks & Distributed Systems 
    Lecturer: Mirco Musolesi
    This module will explore the basic concepts, technologies and standards in the areas of Computer Networks and Distributed Systems. It will cover topics related to the Internet architecture and protocols, networking technologies, distributed systems and algorithms. It will also introduce the students to the recent trends in network technologies and systems, such as wireless networks, mobile computing, cloud computing and online social network applications. The module will be based on the discussion of real-world case studies, research papers and standardisation documents.

bottom of page