In today’s world, where almost everything is driven by AI, it’s important to keep up with the changes. There’s no denying that AI has become a major part of our daily lives—so much so that some jobs are already being replaced by it. To respond to this shift, many universities are now updating their curricula to align with the needs of the modern workforce. 

What should you study if you want a career in AI? 

For some AI-related careers, you don’t necessarily need prior experience, but having a solid foundation in certain subjects is highly recommended. These may include: 

• Introduction to Machine Learning 
• AI Planning for Autonomy 
• Models of Computation 
• Cryptography and Security 
• Advanced Database Systems 
• Statistical Machine Learning 
• Digital Impacts on Business and Society 
• Internet Technologies 
• Algorithms and Complexity 
• Programming and Software Development 
• Database Systems & Information Modelling 

Beyond preparing you to work in a wide range of roles, an AI degree equips you with valuable skills such as: 

• Data and AI system analysis – understanding machine learning processes and evaluating AI models. 
• Application of modern theories and innovations in AI to real-world challenges. 
• AI system lifecycle management – from project planning in new domains to identifying data requirements and building user models. 
• Design, implementation, and evaluation skills for systems capable of learning, reasoning, and problem-solving. 

🟢 Interested in studying AI? Join the exclusive seminar “Preparing for the Future of Work and a 21st Century Career by the University of Melbourne” on Wednesday, 15th October 2025 from 5 pm – 6 pm via Zoom. Register Now  

Recommended Top 5 Career Opportunities in AI 

Graduating with a degree in AI opens the door to diverse career paths across industries. From technical roles in machine learning and system development to applied positions in business, healthcare, finance, or robotics, AI professionals are in high demand worldwide. 

1. Machine Learning Engineer 

A Machine Learning Engineer is responsible for developing machine learning systems through program design, coding, and implementation. Their role involves building AI systems that can analyze, solve problems, and make decisions autonomously without relying on explicit human instructions. 

2. Data Scientist  

A Data Scientist is a specialist who collects, processes, and analyzes data, including Big Data to build machine learning models that uncover insights, trends, and patterns. Their work supports decision-making, business strategy, and forecasting, while also driving data-driven innovations that can be applied to create value in business and beyond. 

3. AI Product Manager  

An AI Product Manager is responsible for planning, strategizing, and overseeing the development and launch of AI-related products. They bridge the gap between market trends, customer needs, and business goals, ensuring that product strategies align with organizational objectives. While they don’t typically build or code AI systems themselves, they must have a strong understanding of AI and machine learning technologies and their potential impact on product development. At the same time, they collaborate closely with engineering, marketing, and sales teams to deliver products that truly resonate with the market. 

4. AI UX/UI Designer  

AI UX/UI Designers focus on understanding user needs, pain points, and behaviors to create intuitive and effective digital experiences. A UX designer researches and organizes website or app structures, ensuring content and features are easy to navigate and meet user expectations. Meanwhile, a UI designer brings these experiences to life by making complex platforms visually appealing, user-friendly, and aligned with the brand identity. Together, they ensure that AI-powered products are not only functional but also engaging and seamless for end users. 

5. Generative AI Specialist  

A Generative AI Specialist researches, develops, and trains AI models designed to create new content such as text, images, audio, code, or video using generative models. Their role involves building applications or solutions powered by generative AI, analyzing model performance, measuring accuracy and output quality, and fine-tuning models based on real user feedback. This career blends technical expertise with creativity, enabling innovations across industries from digital media to healthcare. 

Interested in Studying in Australia or in the UK? 

For more information and assistance with the application process, contact One Education, an official representative of UK and Australian universities. We offer free consultation and support throughout your application journey. 
Add our Line official account: @one-edu 
Submit an enquiry form. We will get back to you as soon as possible.  
Call us: 02-652-0718   

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