School of Electronic Engineering and Computer Science

Mr Ammar Naich

Ammar

Research Assistant

Email: a.y.naich@qmul.ac.uk
Room Number: Engineering, Eng 153

Teaching

Big Data Processing (Undergraduate)

Parallel computing, which implies the simultaneous execution of several processes for solving a single problem, is a mainstream subject with wide ranging implications for computer architecture, algorithms design and programming. The UK has been at the forefront of this technology through its involvement in the development of several innovative architectures. Queen Mary has been actively involved with Parallel Computing for more than a decade. In this module, you will be introduced to parallel computing and will gain first hand experience in relevant techniques. Laboratory work will be based on the MPI (Message Passing Interfaces) standard, running on a network of PCs in the teaching laboratory. The module should be of interest to Computer Scientists and those following joint programmes (eg CS/Maths, CS/Stats). It is also suitable for Chemistry and Engineering students and all those who are concerned with the application of high performance parallel computing for their particular field of study (eg Simulation of chemical Behaviour). The 12-week module involves two hours of timetabled lectures per week. Laboratory sessions are timetabled at two hours per week, normally spanning half the semester only. The module syllabus adopts a hands-on programming stance. In addition, it focuses on algorithms and architectures to familiarise you with messagepassing systems (MPI) as adopted by the industry.

Big Data Processing (Postgraduate)

The 12 week module involves 2 hours of timetabled lectures per week. Laboratory sessions are timetabled at 2 hours per week for 6 to 7 weeks only. The module syllabus adopts a hands-on programming stance. In addition it focuses on algorithms and architectures to familiarise students with message-passing systems ((MPI) as adopted by industry. Parallel computing, which implies the simultaneous execution of several processes for solving a single problem, is a mainstream subject with wide ranging implications for computer architecture, algorithms design and programming. The UK has been at the forefront of this technology through its involvement in the development of several innovative architectures.Queen Mary has been involved with Parallel Computing for more than a decade. In this module, students will be introduced to parallel computing and will gain firsthand experience in relevant techniques.

Data Analytics (Undergraduate)

This module focuses on the range of approaches, methodologies, techniques and tools for data analysis, and the use of data analysis findings to inform decision-making in an industrial / business context.

Data Analytics (Postgraduate)

This module focuses on the range of approaches, methodologies, techniques and tools for data analysis, and the use of data analysis findings to inform decision-making in an industrial / business context. It exposes students to a range of industry-standard statistical and data analysis techniques and tools, and fosters awareness of the challenges associated with working with large datasets. The module also covers topics related to the legal, social, ethical and professional issues associated with data storage and analysis. Students will undertake practical work including empirical data analysis and summarisation / presentation of the results to a range of relevant stakeholders.

Database Systems (Undergraduate)

This module is an introduction to databases and their language systems in theory and practice. The main topics covered by the module are: the principles and components of database management systems; the main modelling techniques used in the construction of database systems; implementation of databases using an object-relational database management system; the main relational database language; Object-Oriented database systems; future trends, in particular information retrieval, data warehouses and data mining.There are two timetabled lectures a week, and one-hour tutorial per week (though not every week). There will be timetabled laboratory sessions (two hours a week) for approximately five weeks.

Project (Undergraduate)

Written and verbal reports on the design and implementation of a software (or software and hardware) system. The aim of the project is to produce a quality product with limited resources. The project tests both technical ability and organisation, communication and evaluation skills. The value of this module is worth more than its nominal 30 credit weighting. The project is seen as an excellent indicator of a student's overall ability to carry out a serious piece of work, and consequently employers are likely to be impressed by competence shown. It will give you a topic of conversation at your job interview. Some professional organisations, such as IEE, only accept a degree as a valid precondition of membership if it includes a substantial individual project. As G400 Computer Science is accredited by BCS this module is compulsory for this degree title. Online information is available from https://intranet.dcs.qmul.ac.uk/courses/coursenotes/projects/bsc/. Not open to Associate Students.

Software Engineering Project (Undergraduate)

Students in pre-assigned groups of approximately six will be presented with a significant software problem to solve. To meet the problem requirements and build a satisfactory system within the time constraints the students will have to apply the principles learnt in the Software Engineering module and will have to work effectively as a team. Each team must choose a project manager and assign appropriate roles to each member.

Research