Monash
Below are the units that I learned in Monash University with the score.
1
Algorithms and programming fundamentals in python
Learn Python fundamentals. Interesting project such as Twenty-One (card game).
Marks: 96
2
Introduction to computer systems, networks and security
Learn network basic such as wireshack and ensemble language (Marie).
Marks: 95
3
Programming fundamentals in Java
Learn Java fundamentals.
Marks: 94
4
Discrete Mathematics for computer science
Learn discrete mathematics for computer science (probability, set and logics)
Marks: 82
7
Object Oriented Design and implementation
Learn modern object-oriented languages and design principle using Java.
Marks: 94
10
Modelling for data analysis
Learn data collection, data sampling, analytic tasks, probability distribution, predictive models and estimation require for data science.
Marks: 84
13
Algorithms and data structures
Learn problem solving concepts and techniques fundamental by different algorithms.
Marks: 87
16
Databases
Develop skills in planning, designing, and implementing a data model using Oracle.
Marks: 90
19
Deep Learning
Focus on understand the fundamental concepts in DL such as in combination with laboratory sessions to gain hands-on experiences.
Marks: 94
22
Data analytics
Techniques covered include data management and transformation, visual analysis, social network analysis, statistical learning, clustering and natural language processing.
Marks:
5
Introduction to computer science
Learn intermediate python language and some of advance technique for computer science.
Marks: 86
8
Continuous mathematics for computer science
Learn linear algebra, calculus, multivariable calculus for computer science.
Marks: 95
11
Full Stack Development
Learn Non-B2B e-Business applications for Web platforms.
Marks: 99
14
Mobile Application development
Introduces and industrial strength programming language and OOP in the context of mobile application.
Marks: 97
17
Software Testing and Testing
Focuses on quality assurance issues and techniques in software development projects.
Marks: 87
20
Computer Science Project 1
This unit provides practical experience in researching, designing, developing and testing a substantial computer science project.
Marks: 83
23
Advanced data structures and algorithms
This unit builds on the concepts learnt in introductory algorithms and data structures study. It covers advanced algorithmic paradigms and problem-solving techniques required to address real-world programming challenges.
Marks:
6
IT Professional practice and ethics
Learn practical and theoretical foundation in developing the skills required as a Professional IT graduate.
Marks: 90
9
Theory of computation
Learn formal languages, models of computation, and computational complexity.
Marks: 74
12
Programming Paradigms
Learn functional and declarative programming styles, comparing the programming styles such as OOP, imperative and procedural programming styles.
Marks: 92
15
Cybersecurity tools and techniques
Learn common cryptographic encryption and authentication algorithms works.
Marks: 93
18
Parallel Computing
This unit covers the programming paradigms that allow parallelism to be exploited in software.
Marks: 89
21
Computer Science Project 2
This unit provides practical experience in researching, designing, developing and testing a non-trivial computer science project.
Marks:
24
Big data management and processing
Data engineering is about developing the software (and hardware) infrastructure to support data science. This unit introduces software tools and techniques for data engineering, but not hardware
Marks:
Final Year Project
Leveraging Emotional Cues for Real-Time Deception Detection
This project develops an AI-powered platform for real-time deception detection by analyzing facial micro-expressions. Unlike traditional multimodal systems that require extensive computational resources, our approach focuses exclusively on micro-expressions to create a more accessible and efficient detection system.
