AICE Lab Programme Year 1 | AICE1000 | University of Southampton

Module overview

This module is the lab programme for all first-year students enrolled on an AICE degree programme. A range of lab activities which tie into each of the first year modules are provided. It aims to give students the opportunity to apply the theory that they learn in their other modules, and to provide them with transferrable, subject-based and professional skills that they will need for their degree and career. The module must be passed as a whole to progress onto year 2.

Structurally, the AICE Part One Laboratory Programme is organized to cover all practical and laboratory based work in the first-year in a single timetable organized into central laboratory locations.

There are a number of technical laboratories integrated into the Laboratory Programme which cover practical Learning Outcomes from other technical modules in the Programmes.

Aims and Objectives

Learning Outcomes

Subject Specific Practical Skills

Having successfully completed this module you will be able to:

Create and deliver functionally correct programs that meet a specification
Be able to use tools to compute appropriate statistics from data
Implement and run interpreted programs that read and write files
Use memory transactions to communicate with devices in an embedded system
Write, compile, and execute programs in an embedded device
Empirically evaluate the performance of algorithms for a given data-set
Use a hardware description language to create finite-state machines
Install, manage, and use a command-line environment
Implement arithmetic and logic circuits using digital logic
Use libraries and classes to access application-specific functionality
Gain facility in using computational tools to inspect, process, filter and refine data for different types
Be able to implement simple data structures in code

Transferable and Generic Skills

Having successfully completed this module you will be able to:

Plan and record self-learning while performing practical work

Syllabus

Introduction to Part 1 labs

The syllabus is driven by the practical labs located within the technical modules, and driven by practical learning-outcomes within those modules. An indicative syllabus is:

High-Level Programming:

Working with a command line environment, toolchains to compile and build programs.
Compiling and installing open-source libraries.
Using file-based I/O operations in your program
Working with loops and iterators
Using open-source libraries in your programs
Selecting license for designed software, ethical considerations using datasets

Maths-1 [Python Jupyter or Mathematica]

Introduction to math visualization tools
Solving systems of equations symbolically
Use linear algebra libraries

Digital Computer Systems

Circuit Construction and Testing
Sequential digital circuits. Logic gates and d-type flip-flops for traffic controller application
Programmable Logic Devices: FPGA programming, simulation and testing
Bus operation and control

Data analytics

Git and version control
Shell programming, Bash scripts, pipes and filters to process data and compute statistics.
Using tools to visualize processed data
Use SQL to create, query and update a database

Algorithms and analysis (with C++)

Working with basic data structures – insert, update and delete operations
Empirical analysis of algorithm vs theoretical methods for all algorithms implemented

Low-Level Programming (with C)

Write, compile, and execute programs in an embedded device
Pointers and memory management
Using tools to debug your programs and plug memory leaks.
Device communication with i/o operations
Testing and debugging techniques to find and fix programming errors

Maths [Python Jupyter or Mathematica]

Working with ordinary differential equations symbolically and numerically: Jacobian matrix for stability analysis and numerical integration
Partial differential equations and visualizations
Lane centering in an automotive driving application

Learning and Teaching

Teaching and learning methods

Computer-based and hardware laboratory sessions

Study time
Type	Hours
Specialist Laboratory	72
Preparation for scheduled sessions	36
Total study time	108

Assessment

Assessment strategy

The lab module consists of 40 individual labs (20 per semester), each of which is worth 2.5% of an associated credit-bearing module. In each semester there are 10 programming labs, with other modules having varying numbers of labs according to module type.

Each lab has a mark, and a marks schema sufficient to define a 40% pass mark in the lab. Students must pass at least 35 out of the 40 labs in order to pass the lab module.

Each lab is scheduled into a specific week as part of the lab scheduling, and has an associated deadline.

Students failing to submit a module by the deadline, or who do not meet the pass-mark by the deadline, will be given at least one opportunity to refer that lab in order to achieve the (capped) pass mark. There is no limit on the number of referrals possible for a given lab, beyond constraints on assessment resources (e.g. personnel, equipment, available times)

Summative

This is how we’ll formally assess what you have learned in this module.

Breakdown
Method	Percentage contribution
Lab work	100%

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.

Breakdown
Method	Percentage contribution
Lab work	100%

Repeat Information

Repeat type: Internal