CSC8622 : Programming for Big Data (Inactive)
CSC8622 : Programming for Big Data (Inactive)
- Inactive for Year: 2024/25
- Module Leader(s): Dr Matthew Forshaw
- Other Staff: Dr Stephen Johnson
- Owning School: Computing
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 1 Credit Value: | 15 |
| ECTS Credits: | 8.0 |
| European Credit Transfer System | |
Pre-requisite
Modules you must have done previously to study this module
Pre Requisite Comment
N/A
Co-Requisite
Modules you need to take at the same time
| Code | Title |
|---|---|
| MAS8382 | Time Series Data |
Co Requisite Comment
N/A
Aims
To gain an appreciation of the use of computational and algorithmic methods for the analysis of big data.
To gain experience in use of the Java and R programming languages.
To provide a grounding in object-oriented design and implementation.
To gain experience in the use of programming environments, shell scripting, version control systems, and build tools.
To gain experience in the design, implementation and use of database systems.
Outline Of Syllabus
Best practices for software development
- Programming environments
- Version Control systems
- Build tools
- Shell scripting
- Regular expressions
- Test-driven development
Java Programming:
- :types; variable declarations; expressions; assignment.
- control-flow abstractions; input and output; Data structures; dynamic memory allocation.
- simple algorithms: searching, sorting.
- object-oriented programming: methods, inheritance; applications.
R Programming:
- the basic constructs of R programming
- data analysis in R
- R libraries
- data visualisation in R
Databases:
- introduction to databases,
- relational database querying and interfacing.
- schema design
- introduction to non-relational databases
Learning Outcomes
Intended Knowledge Outcomes
N/A
Intended Skill Outcomes
Students will be able to understand the process of designing and implementing computer programs for data analysis, with specific knowledge of the R and Java languages.
They will understand the principles of object-orientation.
They will be able to understand some common data structures and their use for data analysis.
They will be able to understand the principles of database systems, including the design of databases, and how to query them.
The ability to use modern IDEs for programming.
The ability to design, implement, test and debug R and Java programs
The ability to design relational databases, and to query them.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 60 | 1:00 | 60:00 | Practical/lab report exercises |
| Guided Independent Study | Assessment preparation and completion | 33 | 1:00 | 33:00 | Lecture follow-up |
| Scheduled Learning And Teaching Activities | Lecture | 33 | 1:00 | 33:00 | N/A |
| Scheduled Learning And Teaching Activities | Practical | 24 | 1:00 | 24:00 | N/A |
| Total | 150:00 |
Teaching Rationale And Relationship
Techniques and theory are presented in lectures. Supervised hands-on practical sessions provide experience of writing programs and using PCs with help available. Further practical work takes place during the private study hours
Reading Lists
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Practical/lab report | 1 | A | 40 | 4 practical reports, equal weighting (max 300 words each). 2 practical reports emphasise use of programming language R & 2 for Java. |
| Practical/lab report | 1 | A | 30 | Programmatic code assignment using R (max 1,000 words) |
| Practical/lab report | 1 | A | 30 | Programmatic code assignment using Java (max 1,000 words) |
Assessment Rationale And Relationship
Written assignments (approximately 4 pieces of work of approximately equal weight) followed by 2 larger pieces of project work allow the students to develop their problem solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; the smaller pieces of work are thus formative as well as summative assessment.
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CSC8622's Timetable
Past Exam Papers
- Exam Papers Online : www.ncl.ac.uk/exam.papers/
- CSC8622's past Exam Papers
General Notes
N/A
Welcome to Newcastle University Module Catalogue
This is where you will be able to find all key information about modules on your programme of study. It will help you make an informed decision on the options available to you within your programme.
You may have some queries about the modules available to you. Your school office will be able to signpost you to someone who will support you with any queries.
Disclaimer
The information contained within the Module Catalogue relates to the 2024 academic year.
In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described.
Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, and student feedback. Module information for the 2025/26 entry will be published here in early-April 2025. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.