Teaching & Education

Sharing Knowledge in Data Science & AI

I'm passionate about teaching Data Science, Machine Learning, and Python Programming. Currently lecturing at Australian Catholic University and Victorian Institute of Technology, sharing my expertise in AI and data science with the next generation of professionals.

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Teaching Experience

Australian Catholic University (ACU)

Lecturer | July 2024 - Present

Teaching advanced courses in Data Science, Machine Learning, and Python Programming at the university level. My role involves developing curriculum, delivering lectures, and mentoring students in practical AI and data science applications.

Victorian Institute of Technology (VIT)

Lecturer | September 2024 - Present

Teaching mathematics and mentoring students in database, networking, and programming courses. I also supervise capstone projects, helping students apply their theoretical knowledge to real-world problems.

Teaching Philosophy

I believe in combining theoretical foundations with practical applications, ensuring students understand both the "why" and "how" of AI and data science concepts. My approach emphasizes hands-on learning through real-world projects and industry-relevant examples.

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Additional Teaching Activities

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Student Mentoring

At VIT, I mentor students in Database (ITAP1001), Networking (ITDA1001), and Programming (ITSU1001) courses, providing guidance on both technical concepts and career development.

Capstone Project Supervision

I supervise capstone projects (ICT802, ITSU3008) at VIT, helping students apply their accumulated knowledge to solve real-world problems and develop comprehensive solutions.

Curriculum Development

I actively contribute to curriculum development, ensuring course content remains current with industry trends and technological advancements in AI and data science.

Industry Integration

My industry experience as an AI Engineer allows me to bring real-world perspectives to the classroom, helping students understand how theoretical concepts apply in professional settings.

My Teaching Approach

Practical-First Learning

I emphasize hands-on learning through real-world projects, case studies, and industry examples that demonstrate the practical application of AI and data science concepts.

Industry-Relevant Content

Course content is continuously updated to reflect current industry practices, tools, and technologies, ensuring students graduate with relevant, marketable skills.

Individualized Support

I provide personalized guidance and support, recognizing that each student has unique learning needs and career aspirations in the rapidly evolving field of AI and data science.

Continuous Assessment

I use a variety of assessment methods including practical projects, presentations, and real-world problem-solving to evaluate student understanding and progress.

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