Graduate Diploma in Medical Genomics & AI
Program Overview
Graduate Diploma in Medical Genomics & AI
Duration: 3 Months (September – October – November)
Program Fee: $1,400
Program Overview
Graduate Diploma in Medical Genomics & AI
Duration: 3 Months (final phase)
Courses: 4
Level: Advanced / Research-Focused Graduate Diploma
Program Overview
The Graduate Diploma in Medical Genomics & AI is the culminating, advanced phase of the progressive pathway in genetics and genomics offered by the California Institute of Genetics (CIG). This Diploma is designed for students who have completed the Certificate in Cancer Genetics and the Diploma in Medical Genetics, and who are ready to transition from knowledge acquisition to data-driven genomic research and translational applications.
This program focuses on the application of artificial intelligence to medical genomics, enabling students to analyze complex genomic and multi-omics datasets, integrate biomarkers, and support precision medicine decision-making. The emphasis is on research thinking, analytical rigor, and translational relevance, rather than clinical practice.
Program Objectives
By the end of the Graduate Diploma, students will be able to:
- Apply AI-based approaches to genomic variant analysis and risk assessment
- Integrate multi-modal biomarkers (genomic, transcriptomic, proteomic, imaging, clinical)
- Use precision medicine informatics for patient stratification and outcome prediction
- Apply pharmacogenomics principles to treatment optimization
- Interpret and communicate findings from complex genomic datasets
- Contribute meaningfully to research, biotech, and translational genomics projects
Curriculum Structure
Course 1: AI-Driven Variant Analysis & Risk Assessment
Focus: Advanced genomic variant interpretation using AI
This course trains students to:
- Analyze germline and somatic variants in medical genomics
- Prioritize variants using AI-assisted models
- Perform rare variant and risk stratification analyses
- Integrate genomic findings with phenotypic and clinical data
- Understand ethical considerations in AI-based genomic risk assessment
Students develop the ability to move beyond variant identification toward meaningful interpretation and risk modeling.
Course 2: Multi-modal Biomarker Integration
Focus: Integrative analysis of multi-omics and clinical data
Students learn to:
- Work with genomic, transcriptomic, epigenetic, proteomic, and imaging biomarkers
- Normalize and integrate heterogeneous biomedical datasets
- Apply AI models to discover and validate biomarkers
- Correlate biomarkers with disease states and outcomes
- Visualize and interpret complex multi-modal data
The course emphasizes systems-level thinking in medical genomics research.
Course 3: Precision Medicine Informatics
Focus: AI-enabled precision medicine frameworks
This course introduces:
- Patient stratification and disease subtyping using genomic data
- Predictive modeling of disease progression and outcomes
- Integration of multi-omics data into decision-support concepts
- Interpretation of AI outputs for translational research use
- Ethical considerations in personalized and data-driven medicine
Students gain experience in using informatics approaches to support precision medicine research pipelines.
Course 4: Pharmacogenomics & Treatment Optimization
Focus: Genomics-guided therapy and optimization strategies
Students explore:
- Drug–gene interactions and variability in treatment response
- Pharmacogenomic principles in precision therapy
- AI-based models for predicting drug response and toxicity
- Treatment stratification and dosing concepts
- Integration of genomic data with pharmacological decision-making
- Regulatory and ethical considerations in genomics-guided therapy
This course emphasizes responsible, evidence-based treatment optimization in research and translational settings.
Learning Approach
- Research-oriented, applied learning
- Analysis of real-world and simulated genomic datasets
- Problem-driven assignments and interpretation exercises
- Emphasis on reproducibility, ethics, and scientific communication
Who This Research Diploma Is For
- Students completing the Diploma in Medical Genetics
- Learners interested in genomics research, biotech, and AI-enabled healthcare innovation
- Candidates preparing for PhD programs, research internships, or translational genomics roles
Pathway Completion
Completion of this Research Diploma represents the highest level of the CIG progressive pathway:
1️⃣ Certificate in Cancer Genetics
2️⃣ Diploma in Medical Genetics
3️⃣ Graduate Diploma in Medical Genomics & AI
Graduates complete the pathway with:
- Strong foundations in genetics
- Clinical and translational understanding
- Advanced, research-ready skills in AI-enabled genomics
Key Strength
This Graduate Diploma transforms students from learners of genetics into contributors to genomics research, capable of working at the intersection of biology, data science, and precision medicine.
20 Reasons to enroll into the program
- Transition from Learning to Research
This is the phase where students move beyond coursework and begin thinking like genomics researchers, not just learners. - AI as a Research Tool, Not a Buzzword
AI is taught as a practical analytical tool for genomics interpretation, not as abstract theory or hype. - Exposure to Real Research Logic
Students learn how genomic questions are framed, analyzed, interpreted, and communicated in real research environments. - Advanced Genomics Skillset
The program builds advanced capability in variant analysis, biomarker integration, and precision medicine workflows. - Multi-omics Thinking
Students learn to integrate genomic, transcriptomic, proteomic, imaging, and clinical data — a key requirement in modern research. - Strong Preparation for PhD Pathways
The Research Diploma builds the analytical maturity and research language expected in doctoral programs. - Research-Ready Internship Profiles
Graduates are better prepared for research internships and fellowships, not just entry-level roles. - Understanding Precision Medicine in Practice
Students learn how genomics and AI support patient stratification, outcome prediction, and treatment optimization. - Pharmacogenomics Expertise
The program introduces how genetic variation influences drug response — a critical skill in pharma and biotech research. - Hands-On Analytical Assignments
Learning is driven by analysis and interpretation, not memorization or exams. - High Academic Rigor
This phase demands deeper reasoning, structured thinking, and evidence-based conclusions — exactly what research requires. - Smaller, Focused Cohort Experience
Advanced programs typically involve more individual feedback, mentoring, and academic oversight. - Ethical & Responsible AI Training
Students learn to apply AI in genomics responsibly, with attention to ethics, bias, and data interpretation. - Bridges Biology and Data Science
The program connects biological understanding with computational thinking — a rare and valuable combination. - Relevant to Biotech & Pharma Research
Skills gained align directly with genomics-driven research in biotech and pharmaceutical environments. - Clear Differentiation from General Diplomas
A Research Diploma signals depth, seriousness, and specialization, setting students apart from generic programs. - Builds Confidence in Complex Data Handling
Students become comfortable working with complex, high-dimensional datasets, a core research skill. - Supports Long-Term Career Growth
This phase prepares students not just for the next role, but for long-term advancement in genomics and research. - No Premature Specialization Required
Students enter after building strong foundations, ensuring AI and genomics concepts are understood meaningfully, not superficially. - Culmination of a Structured Academic Journey
Completing the Research Diploma represents the highest level of achievement in the 9-month pathway, integrating genetics, medical genetics, and AI-enabled genomics research.
Graduate Diploma in Medical Genomics & AI (Phase 3)
9. AI-Driven Variant Analysis & Risk Assessment
9. AI-Driven Variant Analysis & Risk Assessment
9. 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
10. Multi-modal Biomarker Integration
9. AI-Driven Variant Analysis & Risk Assessment
9. 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
11. Precision Medicine Informatics
12. Pharmacogenomics & Treatment Optimization
12. 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
12. Pharmacogenomics & Treatment Optimization
12. Pharmacogenomics & Treatment Optimization
12. 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
Graduate Diploma in Medical Genomics & AI
Duration: 3 Months (Sep – Oct – Nov) Program Fee: $1,400
What this fee covers
The Research Diploma fee covers:
- Enrollment in the Graduate Diploma in Medical Genomics & AI
- Advanced instruction in AI-enabled genomics and multi-omics analysis
- Research-oriented assignments and evaluation
- Higher faculty involvement and academic oversight