Graduate Diploma in Applied AI in Genomics

About the Program

Program Overview

The Graduate Diploma in Applied AI in Genomics is an advanced 8-month online program designed to integrate core knowledge in genetics and genomics with cutting-edge artificial intelligence applications. Students begin with a 5-month foundation in Genetics & Genomics and may progress to a 3-month advanced AI specialization delivered through live online sessions by faculty from a reputed Greek university.

This program is ideal for life sciences graduates and healthcare professionals seeking to develop expertise in AI-driven genomic analysis and precision medicine applications.

Program Description

The Graduate Diploma pathway combines structured asynchronous learning in Genetics and Genomics with advanced, live online instruction in AI applications in genomics. The first 5 months build a strong scientific foundation, while the additional 3-month specialization focuses on AI-driven genomic interpretation, biomarker integration, precision medicine informatics, and pharmacogenomics.

Students who successfully complete all required courses and assessments are awarded the Graduate Diploma in Applied AI in Genomics.

Learning Outcomes

Upon completion of the Graduate Diploma, students will be able to:

Demonstrate advanced understanding of genetics, genomics, and molecular biology.
Interpret genomic variations and their clinical relevance.
Apply AI-driven approaches to variant analysis and risk assessment.
Integrate multi-modal biomarker data for precision medicine insights.
Understand pharmacogenomic principles for treatment optimization.
Analyze genetic information within ethical and clinical frameworks.
Communicate complex genomic concepts effectively in professional settings.
Prepare for advanced research, academic progression, or industry roles in genomics and AI applications.

Course Curriculum

Phase 1: Diploma in Genetics & Genomics (5 Months – Asynchronous)

Molecular Biology A
Molecular Biology B
Basics of Genetics
Human Genomics
Genetic Engineering
Mutations and Mutational Analysis
Cancer Genetics
Rare Genetic Disorders
Genetic Testing and Gene Therapy
Introduction to AI in Genomics

Students earn the Diploma in Genetics & Genomics upon successful completion of Phase 1.

Phase 2: Applied AI in Genomics Specialization (3 Months – Live Online)

Delivered through live online instruction by faculty from a reputed Greek university:

AI-Driven Variant Analysis & Risk Assessment
Multi-Modal Biomarker Integration
Precision Medicine Informatics
Pharmacogenomics & Treatment Optimization

Completion of both phases leads to the award of the Graduate Diploma in Applied AI in Genomics (with additional certification from the Greek University)

Duration

Total Duration: 8 Months
Phase A: 5 Months (Online Asynchronous Self-Study with Mentor Guidance)
Phase B: 3 Months (Live Online Advanced Courses)

Who Should Enroll?

Graduates in Life Sciences, Biotechnology, Genetics, Molecular Biology, or related fields.
Medical, pharmacy, and healthcare professionals seeking advanced knowledge in genomics and AI applications.
Researchers and laboratory professionals interested in precision medicine and genomic interpretation.
Bioinformatics and data science learners looking to specialize in genomic healthcare applications.
Students planning to pursue higher studies in genetics, genomics, or AI-driven biomedical research.
Academic professionals seeking to expand interdisciplinary expertise in genomics and artificial intelligence.
Healthcare innovators and entrepreneurs interested in AI-powered precision medicine solutions.
International students seeking globally relevant, flexible online education.

30 Reasons to enroll into the program

Dual-focus program combining Genetics and AI in Genomics.
Structured 8-month progression pathway.
Strong foundation in core Genetics and Genomics.
Advanced specialization in AI-driven genomic applications.
Live online advanced courses taught by Greek university faculty.
Flexible asynchronous learning for the first 5 months.
Weekly mentor support during foundational phase.
Exposure to precision medicine concepts.
Training in variant analysis and risk assessment.
Knowledge of multi-modal biomarker integration.
Understanding of pharmacogenomics applications
Capstone and applied learning components.
Career-oriented and future-focused curriculum.
Ideal for life sciences and healthcare graduates.
Enhances academic and professional credentials.
Pathway to higher studies and research opportunities.
Builds interdisciplinary expertise in genomics and AI.
Accessible globally through online delivery.
Academic engagement with international faculty.
Prepares students for emerging roles in precision healthcare.
Gain interdisciplinary expertise at the intersection of genetics, genomics, and artificial intelligence.
Learn directly from international faculty through live advanced sessions.
Strengthen analytical and data interpretation skills for genomic applications.
Enhance competitiveness for global biotech and healthcare opportunities.
Develop knowledge aligned with emerging trends in precision and personalized medicine.
Build a progressive academic pathway from diploma to graduate diploma level.
Position yourself for future innovation in AI-driven healthcare solutions.
Gain exposure to real-world applications of AI in clinical genomics and precision healthcare.
Develop interdisciplinary expertise that bridges life sciences and emerging technologies.
Stay ahead in a rapidly evolving field shaping the future of personalized medicine.

Phase B - Applied AI in Genomics by Greek University

AI-Driven Variant Analysis & Risk Assessment

What you will learn

Understand how genetic variants are identified and interpreted in medical genomics
Apply AI-assisted approaches to prioritize clinically and biologically relevant variants
Distinguish between germline and somatic variants in disease contexts
Perform risk assessment based on genomic and phenotypic information
Understand principles of genetic risk modeling and uncertainty
Interpret variant significance using evidence-based criteria
Recognize limitations of AI models in genomic interpretation
Apply ethical considerations in AI-based variant analysis, including bias and responsible use

Multi-modal Biomarker Integration

AI-Driven Variant Analysis & Risk Assessment

What you will learn

Understand different types of biomedical data used in modern genomics research
Work conceptually with genomic, transcriptomic, proteomic, imaging, and clinical data
Integrate multiple data types to improve disease characterization and stratification
Apply AI-based methods for biomarker discovery
Correlate biomarkers with disease features and outcomes
Use data visualization techniques to explore and communicate multi-modal data
Understand principles of biomarker validation and reproducibility
Interpret integrated biomarker results in a research and translational context

Precision Medicine Informatics

Pharmacogenomics & Treatment Optimization

What you will learn

Understand the foundations of precision medicine and personalized care
Use genomic and clinical data for patient stratification and disease subtyping
Apply AI-based methods to predict disease progression and outcomes
Understand how multi-omics data informs treatment decisions
Learn concepts behind clinical decision-support systems
Interpret predictive models and their outputs responsibly
Communicate precision medicine insights clearly to scientific audiences
Recognize ethical and data-governance considerations in precision medicine

Pharmacogenomics & Treatment Optimization

What you will learn

Understand how genetic variation influences drug response
Analyze drug–gene interactions relevant to treatment outcomes
Apply AI-based models to predict treatment response and toxicity
Understand principles of therapy optimization and stratification
Learn how pharmacogenomics supports precision dosing and safety
Interpret treatment-related genomic data in a research setting
Appreciate regulatory and ethical considerations in genomics-guided therapy
Integrate pharmacogenomic insights into broader precision medicine frameworks