Teaching Experience: Artificial Intelligence and Machine Learning

During my time as a part-time lecturer at Teesside University, I taught several courses in artificial intelligence and machine learning to both undergraduate students and professionals in intensive bootcamp formats. These courses provided students with a hands-on understanding of core AI principles, applications in business, and foundations of machine learning.

Courses Taught

Artificial Intelligence Bootcamp (July-August 2021)

An intensive summer bootcamp designed to equip students with essential skills in AI, covering basic machine learning concepts, data preprocessing, and introductory algorithms.

Machine Learning & AI for Business Applications Bootcamp (October 2021-February 2022)

Focused on practical applications of AI in business contexts, this course introduced machine learning pipelines, model deployment, and case studies on AI-driven business solutions.

Artificial Intelligence Foundations (September-December 2021)

An undergraduate course providing foundational knowledge in artificial intelligence, including topics such as supervised learning, unsupervised learning, and neural networks.

Machine Learning (January-May 2022)

This course covered core machine learning algorithms, model evaluation techniques, and data analysis, giving students practical skills in Python and popular machine learning libraries.

Highlights

• Interactive Learning: Emphasized project-based learning, where students completed hands-on projects to reinforce theoretical concepts.
• Student Supervision: Supervised students on independent projects, supporting their growth and application of AI techniques in real-world scenarios.
• Comprehensive Curriculum: Covered a wide range of topics, from foundational AI concepts to advanced machine learning applications, tailored to diverse skill levels.

This experience allowed me to foster a deep understanding of AI and ML among students, nurturing their analytical skills and preparing them for industry or further study.