This is my timeline of career development experience where i will show which subject i will assign to each trimester from college up until my graduation from the university.
| Course Taken in : Trimester 1 | |
| SIT 111 Algorithm and Computing system | |
| SIT 124 Exploring I.T. | |
| SIT 192 Discrete Mathematics | |
| SIT 190 Introductory Mathematical Methods |
Learning Outcome
- practicing logical thinking for coding with computer language
- learning and using one of the most popular programming language ‘Python’
- refining my background of mathematical skills for future usage when encountering data that involve huge amount of data
- broaden my understanding of computers and the algorithm that is implemented by them
- Learning how to design website and set up LinkedIn profile
- understanding the affect of IT has in all areas of the industry to better prepare myself for future career in related field.
| Course Taken in : Trimester 2 | |
| SIT 112 Data Science Concepts | |
| SIT 151 Game Fundamentals | |
| SIT 103 Data and Information Management | |
| SIT 123 Data Capture Technologies |
Learning Outcome
- develop knowledge of fundamentals in data science, in particular data manipulation and algorithms for analytics
- designing games with a focus on engaging and refining their creative skills develop knowledge of fundamentals in data science, in particular data manipulation and algorithms for analytics
- understanding data capture protocols and methodologies, as well as data presentation and visualization methods.
- investigate issues of robustness, reliability and validity of data and the effects of these on conclusions drawn from data.
- Constructing, maintaining and retrieving information from the database using SQL
Moved onto 2nd year in Deakin University through pathway
| Course taken in : Trimester 1 | |
| SIT210 Embedded systems development | |
| SIT221 Data structure and Algorithms | |
| SIT215 Artificial and computational intelligence |
Learning outcome
- investigate, through a range of problem-based learning activities, a range of artificial and computational intelligence techniques that underpin modern, advanced intelligent systems such as autonomous vehicles, robotics, game-playing agents, and expert systems
- building and prototyping embedded devices and systems to capture data, sense the environment, and trigger actions using a range of hardware devices and for a variety of real-world projects. investigate, through a range of problem-based learning activities, a range of artificial and computational intelligence techniques that underpin modern, advanced intelligent systems such as autonomous vehicles, robotics, game-playing agents, and expert systems
- data modelling and computational trade-offs when developing software
| Course taken in : Trimester 2 | |
| SIT 202 Network and communication | |
| SIT 320 Advanced algorithms | |
| SIT 223 Professional practice in Information Technology | |
| SIT 312 System design and prototyping |
Learning Outcome
- examine design, give analysis and implementation of advanced algorithms, explore software design patterns and their use in problem solving, and software testing techniques and tools to verify implementation
- utilize methods and practices in system design, prototyping and testing, and business and funding models relevant to small start-ups and “Kickstarters” examine the design, analysis and implementation of advanced algorithms, explore software design patterns and their use in problem solving, and software testing techniques and tools to verify implementation
- explore the impact of information technology in society, through the investigation of ethical and professional issues, and explore the modern IT workplace
- understand how computer networks are constructed, how they work, and how modern applications use the services provided by modern computer networks.
| Course taken in : Trimester 1 | |
| SIT 374 Team project (A) – Project management and Practices | |
| SIT 307 Data mining and machine learning |
Learning outcome
- hands-on experience in using industry-standard tools to contribute to the project, analyse requirements, design solutions, monitor project progress and productivity, and reflect on sprint and project outcomes.
- methods and technologies for supervised and unsupervised machine learning, exploratory and confirmatory statistical methods, and predictive analytics.
| Course taken in : Trimester 2 | |
| SIT 378 Team project (B) – Execution and delivery | |
| SIT 375 Programming Paradigm |
Learning outcome
- investigating functional and parallel programming, as well as real-time systems programming.
- apply agile project management methods to iteratively create enhancements to a unique IT product, service or solution in a highly flexible and interactive manner.
KenTech 