Specialist Diploma in Biomedical Informatics and Analytics

Fundamentals of Genes and Omics

This module introduces genetic principles and omics technologies, providing learners with an understanding of how genetic data is generated, analysed, and applied in real-world contexts. The module covers key concepts such as DNA, genes, and omics approaches (genomics and proteomics) and their significance in healthcare, diagnostics, and personalized medicine.

It serves as a stepping stone for those pursuing bioinformatics and health informatics, equipping learners with foundational knowledge to understand biological data and its role in these fields

Health Informatics and Analytics

This module introduces learners to the evolving field of healthcare information management and its impact on modern medicine. Learners will explore the principles and applications of health informatics, gaining insight into how data supports clinical care, healthcare operations and evidence-based decision-making. Through hands-on activities and real-world case examples, learners will develop an understanding of the principles and applications of health informatics, equipping students with the knowledge to navigate and utilize various healthcare information systems.

They will also be introduced to basic data analytics techniques relevant to healthcare and will develop practical skills for analysing both clinical and administrative data. By developing proficiency in industry-relevant standards and tools, graduates of this module will be prepared to contribute to healthcare delivery in diverse clinical and operational settings.

Programming for Biomedical Science with Generative AI

This module introduces learners to Python programming for biomedical science, equipping them with essential coding skills applicable to real-world biomedical challenges. Designed for beginners and those looking to enhance their computational abilities, this module provides a blend of theoretical concepts and hands-on practical exercises for a comprehensive learning experience.

A key feature of this module is the integration of Generative AI (GenAI) as a learning and development tool. Learners will build a strong foundation in Python programming and leverage AI-powered coding assistants to enhance their efficiency, troubleshoot errors, and accelerate the development of biomedical solutions.

Bioinformatics and Analytics Project

This module provides an introduction to the integration of biology, computer science, and data analysis in biomedical research. Students will explore how biological data are processed and analysed using computational methods.

The course covers essential bioinformatics tools, the role of databases, and the analysis of various data such as those generated from Next Generation Sequencing (NGS). The use of basic command-line tools, and R programming for data analytics will be introduced. Key topics include data processing, read alignment, variant calling, and RNA-sequencing data analysis.

Biomedical Health and Data Sciences

This module provides insights to learners in the area of data science and data analytics. Learners will learn fundamental statistical methods, database knowledge, perform data preparation and apply programming to derive insights from large dataset.

Machine learning for Biomedical Science and Healthcare

This module covers fundamental concepts in the areas of AI that encompass machine learning. Learners will learn about basic data mining and predictive analysis tools and use existing tools for contextual applications. Learners will also be equipped with the skills and understanding of the use of machine learning in data collection and interpretation.

Integrated Project

The Integrated Project module provides leaners with a hands-on opportunity to apply the knowledge and skills acquired from the Biomedical Health and Data Science, and the Machine Learning modules in a practical setting. Learners will engage in comprehensive analysis and interpretation of real-life biomedical and healthcare datasets.

The project emphasises integrating statistical methods, programming, and machine learning techniques to solve complex biomedical problems. Through this applied experience, learners will develop analytical thinking, and communication skills essential for translating data insights into meaningful biomedical and healthcare outcomes

Prompt Engineering Fundamentals

This module introduces learners to the fundamentals of crafting effective prompts and fine-tuning of Large Language Models (LLMs). Learners will explore strategies to optimize LLM interactions, from designing precise prompts to customizing model behaviour for specific tasks for various real-world use-cases behaviour cases. Learners also will be delving into LLM fine-tuning methodologies.

Generative AI Tools and Workflows

Generative AI Tools and Workflows will introduce learners to practical applications of Generative AI in a code-free manner. Learners will learn to work with popular AI platforms and tools, such as ChatGPT, DALL-E and others, to create content, automate tasks, and/or enhance productivity. Learners will learn about the Generative AI workflow associated with tasks such as text generation, graphic design and more.

Ethical and Societal Impact of Generative AI

In this module, learners will develop an understanding of AI ethics, covering principles like bias, fairness and transparency. Learners will learn how to apply ethical considerations in AI development and deployment. Learners will also delve into the profound ripple effects of Generative AI on society. This module unravels the multifaceted influences of AI, touching upon its advantages, inherent challenges, and unforeseen ramifications.

Generative AI for Business Productivity

Generative AI for Business Productivity explores the transformative potential of Generative AI in modern office environments, including word processing, spreadsheets, and task automation. It equips learners with the knowledge and skills to enhance productivity, decision-making, and creativity through AI. It provides hands-on experience to effectively leverage AI tools in the workplace.

Generative AI Project

This project-based module explores Generative AI’s role in optimizing workflows, boosting productivity, and enhancing analytical capabilities. Learners will apply Generative AI to workplace scenarios, leveraging automation, data-driven insights, and AI-assisted decision-making. Through hands-on projects, they will develop practical skills in leveraging Generative AI.