Science
Bachelor of Data Analytics
Learning Mode
Full Time
Duration
3 Years
Start date
March, July, November
Qualification
Bachelor of Data Analytics
Fees
UG – 23,528 AUD for 1 yr full-time
Location
Melbourne / Sydney
About the Course
The Bachelor of Data Analytics (BDA) at Melbourne Institute of Technology (MIT) offers a cutting-edge and highly practical education, preparing you for a thriving career in the rapidly expanding field of data. This program equips you with essential knowledge of data analytic lifecycles and the application of industry-relevant tools and methodologies. You will learn to analyze massive amounts of structured and unstructured data, extract valuable insights, and apply these insights to innovate and create effective business solutions, particularly in emerging areas like smart technologies, artificial intelligence, and deep learning.
Career prospects
Graduates of the Bachelor of Data Analytics program are highly sought after across diverse industries, including technology, finance, healthcare, consulting, and government, both in Australia and internationally. The program prepares students for roles such as Data Analyst, Business Intelligence Analyst, Data Scientist (entry-level), Data Architect, Fraud Analyst, Marketing Analyst, Operations Analyst, and IT Systems Analyst. Our strong emphasis on practical skills, industry-relevant tools (like Tableau, Python, R, SQL), and real-world problem-solving ensures graduates are well-equipped for impactful and essential careers in the data-driven economy.
Why choose Melbourne Institute of Technology for a Bachelor of Data Analytics?
Industry connected
Gain real-world experience through projects, internships, and lectures from leaders in data innovation.
Global opportunities
Learn global data trends and practices, preparing for international careers and advanced postgraduate opportunities.
Professional accreditation
TEQSA-accredited program aligns with ACS standards, boosting employability and recognition in data analytics careers.
Course Overview
The Bachelor of Data Analytics program at Melbourne Institute of Technology offers a dynamic and engaging learning experience, designed to develop highly skilled and innovative data professionals. The curriculum integrates data science, statistics, artificial intelligence, and machine learning, with a strong emphasis on practical application. Students will gain expertise in data visualization, data modelling, statistical analysis, and strategic decision-making using up-to-date software and programming languages including Tableau, Python, R, SQL, NoSQL, and MATLAB. The program includes an Industry-based Project where students apply their learning to real-world challenges, fostering creative thinking, communication, and leadership skills crucial for success in this evolving industry.
Course Duration
Length of the course
- 3 years full-time (standard)
- Fast-track options may be available to complete in 2 years.
Mode of Study for international students:
- Full-time (on-campus)
Course Curriculum
The Bachelor of Data Analytics curriculum is structured to provide a comprehensive understanding of data analytics principles, advanced tools, and real-world applications.
- Year 1: Data Foundations & Programming
- Includes core units such as Business Communications, Platform Technologies, Operating Systems, Networking Fundamentals, Information Systems Fundamentals, Programming Fundamentals, and Data Science.
- Years 2-3: Advanced Analytics & Specializations
- Focuses on in-depth topics like Data Visualisation, Statistical Analysis, Database Management, and specialized electives in areas such as Smart Industry Automations, Data Science Mathematics, Applied Artificial Intelligence, Intelligent Sensor Networks, Cloud Engineering, Computer Forensics, IT Security Management, and Enterprise Cybersecurity & Management.
- Final Year: Industry-Based Project
- A culminating practical project where students work with an industry client on a real-world data problem, applying their technical and problem-solving skills to develop innovative data-driven solutions.
Admission Requirements
- Academic qualifications
- Successful completion of Australian Year 12 or equivalent secondary education qualification.
- For VCE students, a study score of at least 20 in any English and 20 in any Mathematics.
- For HSC students, Band 2 or higher in any English and Band 2 or higher in any Mathematics.
- International equivalent qualifications are assessed on a case-by-case basis (e.g., IB Diploma with at least 25 points; Senior School Certificate (CBSE) or CISCE with 60% average marks for Indian applicants).
- Prior learning recognition
- Relevant Diplomas or Advanced Diplomas may receive credit transfer, potentially shortening the course duration.
Language Proficiency
- English language requirements (e.g., IELTS, TOEFL)
- The minimum score required is an overall IELTS (Academic) band score of 6.0, with no individual band score less than 5.5, or equivalent scores such as PTE Academic (overall 50, with no section less than 42) or TOEFL iBT (overall 60-78, with minimum scores: Reading 12, Listening 11, Speaking 17, Writing 20).
Fees and Funding
Tuition Fees:
- UG – 23,528 AUD for 1 yr full-time
Scholarships and Bursaries:
- Melbourne Institute of Technology may offer various scholarships and bursaries, including “Beyond the ATAR” scholarships for domestic students. International students are encouraged to check the MIT website for any available international student scholarships or payment plan options.
Career Opportunities
Graduates of the Bachelor of Data Analytics program are well-prepared for diverse and high-demand roles in the data-driven economy. Potential job roles include Data Analyst, Business Intelligence Analyst, Data Scientist (entry-level), Data Architect, Fraud Analyst, Corporate Strategy Analyst, IT Systems Analyst, Social Media Data Analyst, Operations Analyst, Marketing Analyst, Applications Architect, and Enterprise Architect. Industries employing our graduates span technology, finance, health, science, law, government, and any sector leveraging data for strategic decision-making and innovation.
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