Bachelor Of Information Technology (Artificial Intelligence & Data Science)
CRS1401743Shape the future with Artificial Intelligence and Data Science
Artificial Intelligence and Data Science are transforming the way we live, work, and solve complex problems. From predictive analytics and machine learning to intelligent automation and data-driven decision-making, organisations across every industry are seeking professionals with the skills to harness the power of data.
At Chisholm Higher Education College, the Bachelor of Information Technology (AI & Data Science) equips you with the knowledge, technical expertise, and practical experience needed to thrive in one of Australia's fastest-growing technology fields. You'll build a strong foundation in information technology while developing specialised skills in artificial intelligence, machine learning, data analytics, programming, database management, and responsible AI practices.
Graduate Career-Ready
Designed in consultation with industry, this three-year degree combines theoretical knowledge with hands-on learning, ensuring you graduate ready to undertake real-world challenges. You'll gain hands-on experience with industry-standard tools and technologies, analyse large datasets, develop AI-driven solutions, and apply data science techniques to solve real-world problems.
Fast-Track Your Qualification
Already completed a Diploma of Information Technology?
You may be eligible to receive credit towards your degree and complete the Bachelor of Information Technology (AI & Data Science) in just two years, accelerating your pathway into a rewarding technology career. This streamlined pathway allows you to build on your existing skills and enter the workforce sooner.
Exit Point
After successful completion of two years; students can decide to exit with an associate degree.
Further information about Chisholm's accreditation as a Higher Education provider can be found at Tertiary Education Quality and Standards Agency (TEQSA). Chisholm Higher Education College participates in surveys administered by Quality Indicators in Learning and Teaching (QILT).
Download how to meet the inherent requirements.
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Read more about this course
Course structure
To complete the Bachelor of Information Technology (AI & Data Science) you must complete the 24 subjects in the Bachelor.
The Bachelor of Information Technology (AI & Data Science) will require completion of 288 credit points
composed of:
• 15 core information technology subjects (180 credit points)
• 6 core specialisation subjects (72 credit points)
• 3 elective subjects (36 credit points)]
Indicative workload
As an IT student, your weekly workload for each subject you enrol in is approximately 9 hours per week. This is made up of a 3-hour class (delivered hybrid) plus 6-hours personal study time. For example, if you were to study full-time, the weekly workload for this course would be 36 hours.
What You'll Learn:
Throughout the course, you will learn to:
• Collect, clean, manage and analyse complex datasets
• Develop machine learning models and AI-driven applications
• Apply programming, statistical and data science techniques
• Create data visualisations and communicate meaningful insights
• Use technologies and industry-standard tools
• Apply ethical, responsible and secure practices when working with data and AI
• Collaborate on industry-relevant projects and solve real-world problems
How You'll Learn
You'll gain hands-on experience through a hybrid learning model, combining:
• Practical Labs: Develop job-ready skills through hands-on experiences with industry-standard tools and technologies. Analyse real-world datasets, build intelligent AI solutions, and apply data science techniques to solve complex business and societal challenges.
• Applied Assessments: Showcase your capabilities through industry-relevant projects including data exploration and visualisation, machine learning and AI model development, predictive analytics, business intelligence solutions, and professional technical reporting.
Required Resources
Resource
Internet, Computer and Webcam
Requirement
Students require internet access and competent computer skills in order to craft and submit assessment tasks, maintain lines of communication, and avail themselves of online resources as required. -
Timetable
Full-time: Enjoy a flexible hybrid learning model with dedicated on-campus sessions at Dandenong and convenient online classes via Zoom.
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Learning outcomes
1. Synthesise and apply discipline-specific principles, methods and theories of information technology.
2. Formulate research-informed solutions to real-world problems in information technology.
3. Exemplify the technical and communication skills required to work in diverse information technology contexts both individually and as part of a group.
4. Negotiate and integrate ethical and social issues into professional practice.
5. Critically reflect on your own professional practice. -
Subjects - Year one
Database FundamentalsITS103
Semester one
This subject equips students with a comprehensive understanding of database systems and their critical role in managing organisational data. Students will learn fundamental database concepts and principles, including data modelling techniques at conceptual, logical, and physical levels to design structured and normalised schemas. The subject develops practical skills in using Structured Query Language (SQL) to create, manipulate, and query relational databases for common business applications. Students will also explore essential security and privacy considerations in database environments.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Programming EnvironmentITS102
Semester one
This subject provides students with a strong foundation in programming concepts, languages, and development tools. Students will learn to apply structured programming principles, utilise integrated development environments (IDEs), and practice version control. Through guided exercises, they will gain practical experience in writing, debugging, and managing code using industry-standard practices and methodologies, preparing them for collaborative software development in modern environments.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Information SystemsITS101
Semester one
This subject provides students with a foundational understanding of information systems and their role in organisations. Students will explore the basic concepts, components, and processes involved in information systems, gaining knowledge of how information is collected, stored, processed, and utilised to support business operations.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Introduction to Cyber SecurityITS104
Semester one
Introduction to Cyber Security provides students with a comprehensive overview of the principles, technologies, and practices related to cyber security. Students will develop a foundational understanding of the threats, vulnerabilities, and countermeasures used to protect computer systems, networks, and data from cyber-attacks.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
System and Network AdministrationITS203
Semester two
This subject develops practical fluency in operating system internals (processes/threads, memory management, file systems, I/O) and network fundamentals (hardware, topologies/technologies, configuration, basic administration). Students practice virtualisation and cloud concepts to deploy, observe, and benchmark operating system behaviour, and connect services across small networks. Two case studies—Unix/Linux/Android and Windows 11—provide comparison of design choices, administration workflows, and performance trade‑offs. This subject also develops skills to be able to identify and diagnose possible problems and troubleshoot computer network administration systems using both Windows and Linux operating systems.
This practical "hands-on" subject will teach the essential skills of installing, using, and supporting operating systems and its administrative features.Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Math Foundations for ComputingITS202
Semester two
Computing systems encode and transform information using mathematical structures. Number systems underpin data representation and cryptography; functions and logarithms describe scaling laws and performance; graphs model networks, dependencies, and workflows; linear algebra powers graphics, simulation, and machine learning; probability and statistics quantify uncertainty in data and risk; and algorithmic complexity explains why some solutions scale while others do not. This subject builds the mathematical fluency that enables rigorous reasoning, correct implementation, and defensible decision making in real computing contexts.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Web Technologies and Full-Stack FundamentalsITS204
Semester two
This subject introduces the full web development stack from browser and search fundamentals through HTML/CSS, responsive design, JavaScript (and libraries), content management systems, to server side PHP and databases. Students build progressively from static pages to interactive design, and a data driven web application, culminating in a small capstone website that demonstrates end to end skills including basic security, deployment considerations, and maintenance.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Inside Information TechnologyITS201
Semester two
This subject develops core problem‑solving skills in algorithms and data structures with an emphasis on recursion, asymptotic analysis, and algorithmic design. Students will implement and evaluate the efficiency of fundamental data structures (arrays, lists, stacks, queues, heaps, graphs) and algorithms (sorting, searching, divide‑and‑conquer, dynamic programming, and greedy). Students also learn to measure and compare efficiency, write correct programs, and choose suitable techniques (divide‑and‑conquer, dynamic programming, greedy).
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
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Subjects - Year two
Cyber AlgorithmsITS302
Semester one
This subject provides students with a foundational understanding of algorithms and their applications in the field of cyber security. This subject develops foundational and applied skills in modern cryptography and security engineering. Students learn core security concepts, number theory underpinning cryptosystems, and the design, operation, and secure use of cryptographic primitives including block ciphers, stream ciphers, public-key cryptography, hash functions, MACs, and digital signatures. The subject connects theory to practice through hands-on labs implementing and analysing algorithms, configuring cryptographic tools, and evaluating real-world protocol choices.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Data Acquisition and WranglingITI304
Semester one
This subject develops essential skills for acquiring, cleaning, transforming, and interpreting real‑world data for artificial intelligence and data science applications. Students learn to source data from files, repositories, and the web, and apply systematic data wrangling techniques using Python and pandas. Emphasis is placed on exploratory data analysis (EDA), understanding data distributions, working with date‑time data, applying visualisation principles, and communicating insights ethically and effectively. The subject provides foundational preparation for machine learning and advanced analytics units.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Foundations of Data Science and AIITS301
Semester one
This subject introduces the foundations of Artificial Intelligence (AI) and Data Science tailored to students from a range of health, science, technology, engineering, and mathematics disciplines. AI is a branch of computer science devoted to developing intelligent hardware and software systems, while Data Science focuses on extracting insight and value from data through collection, cleaning, exploration, modelling, and communication. Applications of AI and Data Science is increasingly important for graduates across these disciplines to understand the foundations and applications of AI and Data Science relevant to their own profession.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Object Oriented ProgrammingITS303
Semester one
This subject develops ability of students to analyse, design, implement, and communicate robust software solutions using object-oriented (OO) concepts and OO design practices. Students learn to think in objects by modelling real-world problems as collaborating classes and objects, exploring the anatomy of a class, encapsulation, polymorphism, and responsible state management. Students design for reuse and extensibility through interfaces and abstract classes, and build event-driven programs that incorporate event handling and exception handling for reliability. The subject also connects OO systems to modern software ecosystems by working with portable data formats and by consuming and documenting APIs using professional documentation conventions.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Software Engineering and Project ManagementITS401
Semester two
The subject focuses on designing and developing software systems that meet user requirements. Within this context of designing systems, students will undertake activities including requirement analysis; system modelling; architectural design, and validation. Across Weeks 1–8 (Software Engineering), students build core capabilities in software processes, agile practices, requirements engineering, architectural design, implementation, testing, evolution, and dependability. In Weeks 9–12 (IT Project Management), students develop competence in the project management process groups and knowledge areas, including integration, scope, schedule, cost, quality, resources, communications, and risk. Students gain expertise in industry tools to produce professional artefacts such as an system requirements specification, design models and architecture views, test cases, and an IT project plan, while communicating effectively in teams and practicing ethical, professional conduct.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Big Data Management and AnalyticsITI402
Semester two
This subject introduces students to managing and analysing large-scale datasets using modern big data platforms and cloud-native services. Students learn how to design end-to-end pipelines for batch and streaming data, store data in cloud storage and NoSQL systems, process data using Hadoop MapReduce and distributed engines, and apply analytics techniques to generate insights. The subject also addresses the handling of semi-structured and unstructured data, data governance, security, privacy, and ethical data use
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Introduction to Machine LearningITI404
Semester two
This subject examines the computational data science of machine learning as applicable to science, technology, the social sciences and medicine. It examines its use in products such as banner ad selection, email spam filtering, and social media newsfeeds. Students study how machine learning determines accurate, computationally efficient, interpretable and robust inferences from data. Students will examine its origins in artificial intelligence from early complex predictive models that emphasised computation through to recent developments where machine learning has grown more accessible to the public with the adoption of Generative AI and curated datasets.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Visual Analytics and StorytellingITI403
Semester two
This subject introduces students to the principles, tools, and practices of data visualisation and data storytelling. It focuses on transforming raw data into meaningful insights and compelling narratives that support decision making in artificial intelligence and data science contexts. Students will learn how to prepare, analyse, visualise, and communicate data effectively, using appropriate visual forms, dashboards, and stories tailored to diverse audiences. The subject combines theoretical foundations, hands on practice, and industry informed case studies. Contemporary topics such as advanced visualisation techniques, dashboards, evaluation methods, and generative AI for data storytelling are integrated to ensure graduates are workplace-ready and ethically informed
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
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Subjects - Year three
Industry Engagement 1ITS501
Semester one
This subject introduces students to project management principles, the role of a project manager, and the roles of the project team. Students examine project management methodologies, and the key activities required to initiate and plan a project in collaboration with a commercial enterprise. The subject focuses on the initiation and planning stages of a project as well as the tools and techniques required for its successful implementation.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Threat Intelligence and Security AnalyticsITS502
Semester one
The subject builds practical skills in cyber threat intelligence and security analytics, with a strong emphasis on using machine learning methods to detect, investigate, and respond to cyber threats. Students learn how to turn threat intelligence into actionable security work by using popular knowledge base of attacker behaviours and techniques. Students also learn how to detect threats from event records by using case study, like query-based hunting capability that uses the Kusto Query Language. The subject covers malware analysis using machine learning, anomaly detection, and how attackers may try to deceive machine learning systems, with a strong focus on sound evaluation and responsible handling of privacy and ethical issues.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Governance, Ethics, Privacy and Responsible AIITI503
Semester one
This subject introduces the essential knowledge and practical skills required to govern and use AI responsibly. Students learn how to identify ethical risks, protect privacy, manage bias, improve transparency, and establish governance structures that support accountability across the AI lifecycle. It emphasises real-world decision-making using internationally recognised principles and risk management approaches, including the NIST AI Risk Management Framework and ISO guidance on AI risk. Students apply privacy principles (including Australia’s 13 Australian Privacy Principles) and develop governance artefacts such as risk registers, impact assessments, accountability matrices, and transparency documentation.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Elective 1ELECT01
Semester one
Students can choose any subject from our Bachelor of Business (Leadership and Management), Bachelor of Engineering Technology or Bachelor of Information Technology (Cyber Security).
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Advanced Artificial IntelligenceITI602
Semester two
This subject introduces students to advanced concepts and applications of Artificial Intelligence, focusing on practical use of modern AI systems rather than deep mathematical derivations. The student will explore diverse application domains where problems can benefit from AI solutions. You will develop conceptual understanding of major AI methods and know when and where to use them. In the practical components, you will implement simple AI algorithms. Students explore intelligent agents, deep learning, computer vision, NLP, Generative AI, and large language models (LLMs), with emphasis on pre‑trained models, prompt engineering, explainability, and deployment considerations. Through hands‑on activities and case‑based assessments, students learn how advanced AI is applied in real‑world contexts, how to critically evaluate AI systems, and how to communicate evidence‑based insights.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Industry Engagement 2ITS601
Semester two
Building on Industry Engagement 1, students examine strategies for identifying the milestones and actions required to manage an IT project in a commercial enterprise. Students examine the effective stakeholder management and collaboration skills required to work as part of a team in a commercial environment.
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Elective 2ELECT02
Semester two
Students can choose any subject from our Bachelor of Business (Leadership and Management), Bachelor of Engineering Technology or Bachelor of Information Technology (Cyber Security).
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
Elective 3ELECT03
Semester two
Students can choose any subject from our Bachelor of Business (Leadership and Management), Bachelor of Engineering Technology or Bachelor of Information Technology (Cyber Security).
Assessment method:A combination of online quizzes, practical laboratory activities, critical thinking and problem solving exercises, individual and group projects, presentations, and examinations.
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Admission requirements
Applicants with recent secondary education (within the past two years)
Inherent requirements
• Completion of Australian Year 12 or equivalent (no minimum ATAR required).
Applicants with vocational education and training (VET) study
• A completed Certificate IV or above
Applicants with higher education study
• A complete or incomplete higher education qualification
English
• Academic IELTS 6.5 with no individual band below 6, or Chisholm recognised equivalent;
and
Must be at least 18 years of age at enrolment.Our inherent requirements are a guide to help you decide if a course is right for you.
If you are a student with a disability, long-term illness, mental health condition or are a primary carer of an individual with a disability, you can apply for support through our Equitable Learning and Disability Support team.
Purpose
Inherent course requirements are the essential components of a course that are required to support participation, learning, assessment, and demonstration of the learning outcomes. They reflect the core
abilities, knowledge, skills, and professional behaviours necessary to successfully complete the course.
Scope
These inherent course requirements apply to all students enrolled in the course, across all modes of delivery (on‑campus, online, blended), and all learning, assessment, simulated, and work‑integrated learning
environments, including placements where applicable.
Inherent course requirements are distinct from Academic, English language and Course specific admission requirements.
Reasonable Adjustments and Equity Statement
Chisholm Institute is committed to inclusive education and equitable participation. Students may meet inherent course requirements with reasonable adjustments, provided such adjustments do not compromise
academic integrity, fundamentally alter learning outcomes, or undermine professional, safety, or accreditation standards.
Students are encouraged to engage early with Chisholm Equitable Learning and Disability Support to discuss adjustment needs.
Our 'How to meet the inherent requirements' document provides further guidance on meeting these requirements. This document can be downloaded from the course description above. -
Practical placement
Across two third year subjects, students will participate in work integrated learning, where you will examine strategies for identifying the milestones and actions required to manage an IT project in a commercial enterprise.
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Course pathways
Nationally recognised training Certificate IV In Information Technology Diploma of Information Technology Certificate IV in Cyber Security Bachelor Of Information Technology (Artificial Intelligence & Data Science) Possible job outcome - help desk officer
- support web designer
- network support technician
- IT Security Analyst
- cyber security specialist
- Data Scientist
- analyst
- applications developer
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Fees
Indicative total course cost is $66,960. Total course cost is indicative based upon the 2027 tuition fee. Any increase in fees for subsequent years is not included in this value. Indicative annual tuition fees of $23,320. Indicative fees are based upon a student enrolling in 100% full time study load and does not reflect if subjects are repeated or advanced standing is granted.
This course is accredited by the Tertiary Education Quality and Standards Agency (TEQSA) and aligned to Australian Qualification Framework (AQF) Level 7.
Please note: Students may be required to undertake an assessment of their literacy and numeracy as part of their application process.
Chisholm is a Registered Training Organisation (RTO) and provides Nationally Recognised Training (NRT). This means you can be assured that our training will provide you with a qualification that is recognised and respected across Australia.
Chisholm courses are subject to minimum and maximum group numbers. Courses may be cancelled or postponed if minimum numbers are not achieved by the start date of the course. Courses may close prior to the start date if the maximum numbers are reached. In that situation, eligible applicants will be offered a place in the next available intake.