| Course Name: | Master of Computer Science (Machine Learning and Big Data) |
| Course Institution: | University of Wollongong |
| Course Department: | Faculty of Engineering and Information Sciences |
| Course Duration: | 24 month(s) |
| Course Fee: | INR 3436800 |
| Course Mode: | Full Time Regular Classroom |
| Course Location(country): | Australia |
| Course Location(city): | Wollongong |
| Course Level: | Masters |
The MCompSc (ML & Big Data) by UoW aims at equipping students with the ability to solve real-world problems. ML helps analyze and extract relevant information from an extensive collection of big data. It provides fundamental tools for BDA. There are numerous applications that requires professionals with advanced skills in ML and big data. These applications include:
- Image recognition
- Computer vision
- Speech recognition and natural language processing
- Intelligent robotics
- Smart cars
- Automation
- Online search and recommendations
- Financial trading and risk management
- Healthcare
- Personal and public security.
This program focuses on developing Information and Communication Technology (ICT) professionals with a Bachelor’s degree in Information Technology or Computer Science for the challenges of rapidly advancing ICT technologies. This degree is extremely advantageous for professionals who want to further their careers in managerial roles related to IT. It can also prepare ICT professionals for entry into research degrees like Master of Philosophy and Ph.D.
Why choose MCompSc (ML and Big Data) by the University of Wollongong(UoW)?
The Master of Computer Science(ML & Big Data) by the University of Wollongong, Australia, aims to equip students with the ability to solve business problems by integrating computer science methods with effective management strategies and developing computer applications.
Students will be studying subjects in Machine Learning Applications and Algorithms, Big Data Analytics, and Computer Vision Algorithms and Systems. Through this program, students can solve complex real-world problems while meeting the demands of society for big data scientists & specialists in multiple fields. Students will also be taking up an individual capstone project where they apply theory into practical sense.
What to expect from the MCompSc (ML & Big Data) by UoW?
- Students learn to solve complex real-world problems as they understand how to combine computer science methods with effective management strategies and the development and usage of computer applications.
- Students research and apply essential information and skilled judgment in computer software design and project planning.
- Students can also interpret theoretical, professional, and practical information and communicate knowledge, procedures, and ideas to both computer scientists and stakeholders.
- Students learn to use independent learning strategies to update their knowledge in the field and be up to date with innovations in computer science techniques, industry standards, and trends.
- They develop self-reliant skills and learn to work in a team in a manner consistent with ethical and professional standards.
Why choose the University of Wollongong?
- The University of Wollongong has sciences IT, engineering, and mathematical methodologies experts.
- They have one of the most substantial schools for building, which deploys and manages the latest business computing systems and computing technologies.
- They work closely with industry partners to ensure the program remains relevant to industry trends & developments.
- The university provides its students to study real-world projects furthermore interact with and learn from industry professionals to ensure their job-readiness upon graduation.
Curriculum
Students can choose to complete a major in one of the following:
- Intelligent Systems
- ML and Big Data
- Network & Information Security
- Software Engineering
Or may wish to complete the ‘No Major’ option where they are required to complete one group with two subjects.
Duration
The MCompSC (ML & Big Data) by UoW is a 24-month(s) Full Time Regular Classroom program.
Admissions
Domestic Students
Candidate must have a recognized Bachelor’s degree and an equivalent average mark of 60% in any area. Candidates who have other qualifications and satisfactory suitable professional experience will be considered on cases to case basis.
Candidates applying for a Bachelor’s degree in Computer Science may apply for 24 credit points (1 session).
International Students
International candidates applying for this program must have a recognized Bachelor’s degree and an equivalent average mark of 60% in any area. Candidates who have other qualifications and satisfactory suitable professional experience will be considered on cases to case basis. Candidates applying for a Bachelor’s degree in Computer Science may apply for 24 credit points (1 session).
English Language Requirements
International applicants have to meet the basic English language requirements by taking one of the following standardized tests:
Fee
Candidates interested in pursuing the MCompSc (ML & Big Data) course for UoW have to pay a fee of INR 3436800.
How to Apply
Candidates who wish to apply for the MCompSC (ML & Big Data) program can submit their applications through UAC.
Candidates who wish to apply directly can visit this portal and follow the procedure prescribed
Please note: Candidates may be required to pay an application fee.
Accreditation and Recognition
The Master of Computer Science (ML & Big Data) is a degree that is professionally accredited by the Australian Computer Society (ACS). ACS has global reciprocal agreements and recognizes the student’s degree internationally.
Career Opportunities
The University of Wollongong hosts the UOW STEM Careers Expo to enourage businesses and organizations to offer internship and placement opportunities for its students. This year the UoW is hosting a Virtual event amit Covid-19 spread. It promote vacation work opportunities & internships over summer for students in their penultimate year of study.
You may have a look at our extensive coverage on other analytics courses. Disclaimer: This information is based on the research carried out by AI Monks. The information in this article should be used only for indicative purposes. AI Monks is not responsible for any information that may be different from the actual scenario.