BachelorFaculty of Digital Health & BioInnovation

Bachelor of Biomedical Data Analytics

¡Hola! Welcome, future architects of biomedical data. My work focuses on how we can use data to improve our understanding of human health. Together, we'll harness the power of AI and big data to answer some of the most important questions in medical science.

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Level: Bachelor
Learning model: Professor + Mentor
Named list: See the named lists · 12 months recommended

NXAcademic
Edition

The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

Academic focus

Big Data Processing, Health Informatics, AI-Driven Medical Research, Predictive Analytics

Practical focus

Health Informatics, Data Analysis, AI-Driven Medical Research, Machine Learning

After this programme

Success journey, careers and practice

Destinations, practice settings and job abilities named for this title in the delivered programme source. From graduation onwards where the source names that path.

Success journey

Deutsche Bank
Internships in quantitative finance and risk management
The European Central Bank
Internships in financial stability and economic analysis

Career opportunities

Biomedical Data Analyst
In medical research institutions or hospitals
Health Informatics Specialist
In health IT companies or hospitals
AI Engineer
In medical or pharmaceutical companies
Clinical Research Associate
In academia or biotech firms

Jobs and projects

Critical Thinking
Applying a data-driven approach to complex medical problems
Problem-Solving
Tackling data challenges creatively and effectively
Technical Communication
Clearly explaining technical concepts to medical professionals
Collaboration
Working effectively with doctors, researchers, and other specialists

Copied from the delivered professor and mentor rows for this title.

This programme

What you study, and what it builds

Gains and skills named for this title, listed as a reader would scan them.

What you gain
- You will gain a deep understanding of how to use data to improve human health, with a skill set that is in high demand in the rapidly growing field of personalized medicine and diagnostics.
Skills you build
- Big Data Processing: Utilizing tools to manage and analyze health data.
- Health Informatics: Designing systems for managing and analyzing medical data.
- AI-Driven Research: Building AI and machine learning models to advance medical research.
- Statistical Modeling: Applying statistical models to extract meaningful conclusions from data.

Listed courses

Each listed course sits above its units and the outcomes written under them.

Bachelor of Biomedical Data Analytics

01Introduction to Data Science
1. FoundationsFoundations of Introduction to Data Science
  The learner can you will gain a deep understanding of how to use data to improve human health, with a skill set that is in high demand in the rapidly growing field of personalized medicine and diagnostics, as applied to Introduction to Data Science.
  The learner can distinguish related ideas inside Introduction to Data Science.
2. MethodsMethods in Introduction to Data Science
  The learner can apply a method from Introduction to Data Science to a documented case.
  The learner can aI-Driven Research: Building AI and machine learning models to advance medical research, as applied to Introduction to Data Science.
3. ApplicationApplication of Introduction to Data Science
  The learner can evaluate a practice of Introduction to Data Science against a stated criterion.
  The learner can transfer Introduction to Data Science to a new documented context.
02Biomedical Data Analytics
1. FoundationsFoundations of Biomedical Data Analytics
  The learner can explain the core terms of Biomedical Data Analytics.
  The learner can distinguish related ideas inside Biomedical Data Analytics.
2. MethodsMethods in Biomedical Data Analytics
  The learner can apply a method from Biomedical Data Analytics to a documented case.
  The learner can select an appropriate method from Biomedical Data Analytics for a stated problem.
3. ApplicationApplication of Biomedical Data Analytics
  The learner can evaluate a practice of Biomedical Data Analytics against a stated criterion.
  The learner can transfer Biomedical Data Analytics to a new documented context.
03AI and Medical Research
1. FoundationsFoundations of AI and Medical Research
  The learner can explain the core terms of AI and Medical Research.
  The learner can distinguish related ideas inside AI and Medical Research.
2. MethodsMethods in AI and Medical Research
  The learner can apply a method from AI and Medical Research to a documented case.
  The learner can select an appropriate method from AI and Medical Research for a stated problem.
3. ApplicationApplication of AI and Medical Research
  The learner can evaluate a practice of AI and Medical Research against a stated criterion.
  The learner can transfer AI and Medical Research to a new documented context.
04Health Informatics
1. FoundationsFoundations of Health Informatics
  The learner can explain the core terms of Health Informatics.
  The learner can distinguish related ideas inside Health Informatics.
2. MethodsMethods in Health Informatics
  The learner can apply a method from Health Informatics to a documented case.
  The learner can select an appropriate method from Health Informatics for a stated problem.
3. ApplicationApplication of Health Informatics
  The learner can evaluate a practice of Health Informatics against a stated criterion.
  The learner can transfer Health Informatics to a new documented context.
05Biomedical Data Analytics Research Project
1. FoundationsFoundations of Biomedical Data Analytics Research Project
  The learner can explain the core terms of Biomedical Data Analytics Research Project.
  The learner can distinguish related ideas inside Biomedical Data Analytics Research Project.
2. MethodsMethods in Biomedical Data Analytics Research Project
  The learner can apply a method from Biomedical Data Analytics Research Project to a documented case.
  The learner can select an appropriate method from Biomedical Data Analytics Research Project for a stated problem.
3. ApplicationApplication of Biomedical Data Analytics Research Project
  The learner can evaluate a practice of Biomedical Data Analytics Research Project against a stated criterion.
  The learner can transfer Biomedical Data Analytics Research Project to a new documented context.
06The Practical Guide to Digital History
1. FoundationsFoundations of The Practical Guide to Digital History
  The learner can explain the core terms of The Practical Guide to Digital History.
  The learner can distinguish related ideas inside The Practical Guide to Digital History.
2. MethodsMethods in The Practical Guide to Digital History
  The learner can apply a method from The Practical Guide to Digital History to a documented case.
  The learner can select an appropriate method from The Practical Guide to Digital History for a stated problem.
3. ApplicationApplication of The Practical Guide to Digital History
  The learner can evaluate a practice of The Practical Guide to Digital History against a stated criterion.
  The learner can transfer The Practical Guide to Digital History to a new documented context.
07Archival Science for Public Policy
1. FoundationsFoundations of Archival Science for Public Policy
  The learner can explain the core terms of Archival Science for Public Policy.
  The learner can distinguish related ideas inside Archival Science for Public Policy.
2. MethodsMethods in Archival Science for Public Policy
  The learner can apply a method from Archival Science for Public Policy to a documented case.
  The learner can select an appropriate method from Archival Science for Public Policy for a stated problem.
3. ApplicationApplication of Archival Science for Public Policy
  The learner can evaluate a practice of Archival Science for Public Policy against a stated criterion.
  The learner can transfer Archival Science for Public Policy to a new documented context.
08Capstone Project in Historical Analysis
1. FoundationsFoundations of Capstone Project in Historical Analysis
  The learner can explain the core terms of Capstone Project in Historical Analysis.
  The learner can distinguish related ideas inside Capstone Project in Historical Analysis.
2. MethodsMethods in Capstone Project in Historical Analysis
  The learner can apply a method from Capstone Project in Historical Analysis to a documented case.
  The learner can select an appropriate method from Capstone Project in Historical Analysis for a stated problem.
3. ApplicationApplication of Capstone Project in Historical Analysis
  The learner can evaluate a practice of Capstone Project in Historical Analysis against a stated criterion.
  The learner can transfer Capstone Project in Historical Analysis to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

I am a data scientist who believes that medicine is a data science. My work focuses on developing algorithms and models to extract meaningful insights from large medical datasets. My goal is to use the power of data to transform healthcare, from diagnosis to treatment.

Applied mentorship

Bonjour! The code of life is a language. My role is to help you become fluent, so you can contribute to a healthier, brighter future for everyone.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

• Blog Post: 'From Data to Diagnosis: The Power of Biomedical Data Analytics' - An accessible article on how biomedical data analytics is transforming healthcare. · • Blog Post: 'AI-Driven Medical Research: Ethics and Applications' - Discusses the ethical considerations and practical applications of using AI in medical research. · • Conference Paper: 'Deep Learning Models for Predicting Patient Outcomes' - Presented at the International Conference on AI and Medicine, detailing how deep learning models can be used to predict patient outcomes. · • Journal Article: 'Big Data Systems for Real-Time Health Analytics' - Published in the Journal of Health Informatics, this paper provides a framework for building systems for real-time health data analysis. · • Standard Article: 'The Rise of Data Science in Medical Research' - A multi-part series for a medical journal on the increasing role of data science in medical research. · • Book: 'Biomedical Data Analytics: From Data to Insight' - A comprehensive textbook on the theoretical and practical applications of biomedical data analytics. · • Total Score: 29/30 · • Kairos Badge: 🥇

R / 02

Mentor practice lens

• Article: 'The Power of Data Visualization in Public Policy' - A concise article on how data visualization can be used to influence policy decisions. · • Guide: 'A Beginner's Guide to Using R for Historical Data Analysis' - A practical tutorial for new students on the basics of a key bioinformatics programming language. · • Essay: 'Building Ethical AI for Public Policy' - An essay on the challenges and responsibilities of creating AI tools for government. · • Total Score: 28/30 · • Kairos Badge: 🥇

Adaptive capability

Professor superpower

GAF-powered Interactive Data Exploration

Adaptive capability

Mentor superpower

GAF-powered Clinical Insight Extraction

Your academic team

Guidance with depth and continuity

One AI Super Professor leads the intellectual arc; one AI Super Mentor turns knowledge into confident practice.

AI Super Professor

Prof. Dr. Miguel Aranda

Big Data Processing, Health Informatics, AI-Driven Medical Research, Predictive Analytics

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AI Super Mentor

Dr. Sophie Tremblay

Health Informatics, Data Analysis, AI-Driven Medical Research, Machine Learning

Meet your mentor Open the classroom

Same faculty and level

Related programs

Named lists

Named lists for this house

Core. Bachelor, Master and Doctorate by duration. Enrolment is not open. Nothing here is a sale.

Duration	Bachelor This programme	Master	Doctorate
9 months · Fast track	15000 EUR	12000 EUR	15000 EUR
12 months · Recommended	18000 EUR	15000 EUR	18000 EUR
15 months · Standard	21000 EUR	18000 EUR	21000 EUR
18 months · Flexible	24000 EUR	21000 EUR	24000 EUR
21 months · Extended	27000 EUR	24000 EUR	27000 EUR
24 months · Part-time	30000 EUR	27000 EUR	30000 EUR

These are the owner lists. Enrolment is not open. Nothing here is a sale.

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Bachelor of Biomedical Data Analytics

Academic focus

Practical focus

Deutsche Bank

The European Central Bank

Biomedical Data Analyst

Health Informatics Specialist

AI Engineer

Clinical Research Associate

Critical Thinking

Problem-Solving

Technical Communication

Collaboration

Research leadership

Applied mentorship

Professor research lens

Mentor practice lens

Professor superpower

Mentor superpower

Prof. Dr. Miguel Aranda

Dr. Sophie Tremblay

Find the program that expands your universe.