Course Title: Algorithms and Analysis
Part A: Course Overview
Course Title: Algorithms and Analysis
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
COSC1285 |
City Campus |
Postgraduate |
140H Computer Science & Information Technology |
Face-to-Face |
Sem 1 2006, Sem 2 2006, Summer2007, Sem 1 2007, Sem 2 2007, Summer2008, Sem 1 2008, Sem 2 2008, Summer2009, Sem 1 2009, Sem 2 2009, Sem 1 2010, Sem 2 2010, Summer2011, Sem 1 2011, Sem 2 2011, Summer2012, Sem 1 2012, Sem 2 2012, Sem 2 2013, Summer2014, Sem 2 2014, Summer2015, Sem 2 2015, Sem 1 2016 |
COSC1285 |
City Campus |
Postgraduate |
171H School of Science |
Face-to-Face |
Sem 1 2017, Sem 2 2017, Sem 1 2018, Sem 2 2018, Sem 1 2019, Sem 2 2019, Sem 1 2020, Sem 2 2020, Sem 1 2021, Sem 2 2021 |
COSC1285 |
City Campus |
Postgraduate |
175H Computing Technologies |
Face-to-Face |
Sem 2 2022, Sem 1 2023, Sem 2 2023, Sem 1 2024, Sem 2 2024 |
COSC2123 |
City Campus |
Undergraduate |
140H Computer Science & Information Technology |
Face-to-Face |
Sem 1 2006, Sem 2 2006, Summer2007, Sem 1 2007, Sem 2 2007, Summer2008, Sem 1 2008, Sem 2 2008, Summer2009, Sem 1 2009, Sem 2 2009, Sem 1 2010, Sem 2 2010, Summer2011, Sem 1 2011, Sem 2 2011, Summer2012, Sem 1 2012, Sem 2 2012, Sem 2 2013, Summer2014, Sem 2 2014, Summer2015, Sem 2 2015, Sem 1 2016 |
COSC2123 |
City Campus |
Undergraduate |
171H School of Science |
Face-to-Face |
Sem 1 2017, Sem 2 2017, Sem 1 2018, Sem 2 2018, Sem 1 2019, Sem 2 2019, Sem 1 2020, Sem 2 2020, Sem 1 2021, Sem 2 2021 |
COSC2123 |
City Campus |
Undergraduate |
175H Computing Technologies |
Face-to-Face |
Sem 2 2022, Sem 1 2023, Sem 2 2023, Sem 1 2024, Sem 2 2024 |
COSC2203 |
RMIT University Vietnam |
Postgraduate |
175H Computing Technologies |
Face-to-Face |
Viet3 2022, Viet3 2023, Viet1 2024 |
COSC2469 |
RMIT University Vietnam |
Undergraduate |
140H Computer Science & Information Technology |
Face-to-Face |
Viet2 2016 |
COSC2469 |
RMIT University Vietnam |
Undergraduate |
171H School of Science |
Face-to-Face |
Viet2 2017, Viet3 2020, Viet3 2021 |
COSC2469 |
RMIT University Vietnam |
Undergraduate |
175H Computing Technologies |
Face-to-Face |
Viet1 2022, Viet3 2022, Viet1 2023, Viet3 2023, Viet1 2024 |
COSC2498 |
Taylors College KL |
Undergraduate |
140H Computer Science & Information Technology |
Face-to-Face |
Offsh 3 10 |
COSC2722 |
RMIT Vietnam Hanoi Campus |
Undergraduate |
175H Computing Technologies |
Face-to-Face |
Viet1 2024 |
Course Coordinator: A/Prof. Jeffrey Chan
Course Coordinator Phone: -
Course Coordinator Email: jeffrey.chan@rmit.edu.au
Course Coordinator Availability: By appointment
Pre-requisite Courses and Assumed Knowledge and Capabilities
Enforced Pre-requisite Courses
For the postgraduate course offering:
Successful completion of:
- COSC2531 - Programming Fundamentals (Course ID 045682)
For the undergraduate course offering:
Successful completion of:
- COSC2288 / COSC2391 / COSC2440 / COSC2684 / COSC2786 - Further Programming (Course ID 014052) OR
- COSC2802 - Programming Bootcamp 2 (Course ID 054080) OR
- COSC1076 / COSC2082 / COSC2136 / COSC2696 - Advanced Programming Techniques (Course ID 004068) OR
- COSC2800 - IT Studio 2 (Course ID 054075) OR
- EEET2482 - Software Engineering Design (Course ID 038296) AND
- MATH2411 - Mathematics for Computing 1 (Course ID 054076)
Note: it is a condition of enrolment at RMIT that you accept responsibility for ensuring that you have completed the prerequisite/s and agree to concurrently enrol in co-requisite courses before enrolling in a course.
For your information go to RMIT Course Requisites webpage.
Course Description
The main objective of this course is for you to acquire the tools and techniques necessary to propose practical algorithmic solutions to real-world problems which still allow strong theoretical bounds on time and space usage. You will study a broad variety of important and useful algorithms and data structures in different areas of applications, and will concentrate on fundamental algorithms. You will spend a significant time on each algorithm to understand its essential characteristics and to respect its subtleties.
Objectives/Learning Outcomes/Capability Development
Program Learning Outcomes
This course contributes to the following Program Learning Outcomes (PLOs) for BP094 Bachelor of Computer Science, BP096 Bachelor of Software Engineering, BP215 Bachelor of Information Technology (Games and Graphics Programming), BH094 Bachelor of Engineering (Electronic & Communication Engineering (Hons)/Bachelor of Computer Science, BH091 - Bachelor of Engineering (Computer and Network Engineering) (Honours)/Bachelor of Computer Science, MC061 Master of Computer Science, and MC208 Master of Information Technology:
- Enabling Knowledge: You will gain skills as you apply knowledge effectively in diverse contexts.
- Enabling Knowledge: You will gain skills as you apply knowledge with creativity and initiative to new situations. In doing so, you will: Demonstrate mastery of a body of knowledge that includes recent developments in computer science and information technology; Recognise and use research principles and methods applicable to computer science and information technology.
- Critical Analysis: You will learn to accurately and objectively examine and consider computer science and information technology (IT) topics, evidence, or situations, in particular to: (i) Analyse and model requirements and constraints for the purpose of designing and implementing software artefacts and IT systems; (ii) Evaluate and compare designs of software artefacts and IT systems on the basis of organisational and user requirements.
- Problem Solving: Your capability to analyse problems and synthesise suitable solutions will be extended as you learn to: Design and implement software solutions that accommodate specified requirements and constraints, based on analysis or modelling or requirements specification.
- Communication: You will learn to communicate effectively with a variety of audiences through a range of modes and media, in particular to: Present a clear, coherent and independent exposition of software applications, alternative IT solutions, and decision recommendations to both IT and non-IT personnel via technical reports of professional standard and technical presentations. Interpret abstract theoretical propositions, choose methodologies, justify conclusions and defend professional decisions to both IT and non-IT personnel via technical reports of professional standard and technical presentations.
- Team Work: You will learn to work as an effective and productive team member in a range of professional and social situations, in particular to: Work effectively in different roles, to form, manage, and successfully produce outcomes from teams whose members may have diverse cultural backgrounds and life circumstances and differing levels of technical expertise.
On successful completion of this course you should be able to:
- Compare, contrast, and apply the key algorithmic design paradigms: brute force, divide and conquer, decrease and conquer, transform and conquer, greedy, dynamic programming and iterative improvement;
- Compare, contrast, and apply key data structures: trees, lists, stacks, queues, hash tables and graph representations;
- Define, compare, analyse, and solve general algorithmic problem types: sorting, searching, graphs and geometric;
- Theoretically compare and analyse the time complexities of algorithms and data structures; and
- Implement, empirically compare, and apply fundamental algorithms and data structures to real-world problems.
Overview of Learning Activities
Key concepts will be explained in pre-recorded lectures and live lectorials, where course material will be presented and the subject matter will be illustrated with demonstrations and examples.
Workshop sessions focus on problem solving and application of data structures and algorithms learnt in classes and provide practice in the application of theory and procedures.
Overview of Learning Resources
Computer laboratories and relevant software will be provided by the School. You will be able to access course information and learning materials and any recommended textbooks through the Canvas learning management system. Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided.
Overview of Assessment
The assessment for this course comprises of assignments, weekly quizzes and a set of end-of-semester timed and timetabled assessment.
This course has no hurdle requirements.
Assessment Task 1: Weekly Quizzes
Weighting 10%
This assessment task supports CLOs 1, 2, 3 & 4
Assessment Task 2: Assignment 1
Weighting 20%
This assessment task supports CLOs 1, 2, 3, 4 & 5
Assessment Task 3: Assignment 2
Weighting 30%
This assessment supports CLOs 1, 2, 3, 4 & 5
Assessment Task 4: End-of-semester Timed and Timetabled Exercises
Weighting 40%
This assessment supports CLOs 1, 2, 3, 4 & 5
This assessment is a timed and timetabled assessment that students must attend on campus.
Please note that postgraduate students are expected to demonstrate deeper knowledge and higher level application of knowledge and skills than undergraduate students.