Bachelor of Data Science

Program Overview

Deakin's Bachelor of Data Science equips students with the skills to navigate the data-driven landscape. Through a comprehensive curriculum covering data lifecycle, analytical methods, and emerging technologies, graduates gain a sought-after skillset in machine learning, AI, and predictive analytics, preparing them for high-demand careers in data analysis, data science, and related fields.

Program Outline

Degree Overview:

Propel yourself into the thriving field of data science with Deakin's Bachelor of Data Science. With every click, swipe, search, share, and stream, data is created. The rate of data generation is phenomenal, and its volume and complexity give rise to considerable opportunities as businesses strive to harness the power of big data to remain competitive. Throughout this course, you will explore the entire lifecycle of data to develop a deep understanding of how information is created, gathered, processed, analyzed, and used to generate insights and inform strategic decisions. You will study innovative course content covering the latest data science trends, insights, and emerging topics to ensure you graduate with a specialist, technical, and highly relevant skill-set that is sought-after by employers across the globe. Explore different analytical methods, tools, and techniques as you learn key concepts and deep dive into advanced topics in machine learning, AI, and predictive analytics.

Outline:

Year 1

Trimester 1

• Academic Integrity Module (0 credit points)
• Safety Induction Program (0 credit points)
• Career Tools for Employability (0 credit points)
• Computer Systems
• Discrete Mathematics
• Introduction to Data Science and Artificial Intelligence
• Introduction to Programming

Trimester 2

• Database Fundamentals
• Introduction to Statistics and Data Analysis
• Object-Oriented Development
• Linear Algebra for Data Analysis

Year 2

Trimester 1

• Computer Networks and Communication
• Data Wrangling
• Data Structures and Algorithms
• Minor or elective unit (one (1) credit point)

Trimester 2

• Professional Practice in Information Technology
• Feature Generation and Engineering
• Data Capture Technologies
• Minor or elective unit (one (1) credit point)

Year 3

Trimester 1

• Natural Language Processing
• Machine Learning
• Minor or elective unit (one (1) credit point)

Trimester 2

• Deep Learning
• Minor or elective unit (one (1) credit point)
• Team Project (B) - Execution and Delivery
• Professional Practice

Assessment:

Assessment methods may vary depending on the individual unit, but typically include:

• Assignments
• Case studies
• Exams
• Group projects
• Presentations
• Quizzes
• Reports

Teaching:

The Bachelor of Data Science is taught by a team of experienced academics and industry professionals who are passionate about data science and its applications. Teaching methods include:

• Lectures
• Seminars
• Tutorials
• Workshops
• Online learning
The program also includes a mandatory work placement, where you will gain practical experience in a real-world setting.

Careers:

Graduates of the Bachelor of Data Science are in high demand, with a wide range of career opportunities available in various industries, including:

• Data analysis
• Data science
• Business strategy
• Data engineering
• Data architecture
• Data visualization
• Information analysis
• Reporting analysis
You could work in a variety of settings, such as:
• Government
• Business
• Healthcare
• Education
• Finance
• Manufacturing