Advanced Diploma in AI in Genomics - 6 months online
Program Benefits
- Job-ready skills in genetics and genomics
- AI-enabled industry exposure (no coding required)
- Strong foundation for biotech and diagnostics roles
- Flexible, fully online learning
- Suitable for NC and international students
- Resume-ready professional diploma
Phase 1 - Foundations in AI, Genetics & Genomics
Molecular Biology
Basics of Genetics
Basics of Genetics
- Structure and function of DNA, RNA, and proteins
- Gene expression: transcription, translation, and regulation
- DNA replication, repair, and recombination mechanisms
- Molecular basis of cell signaling and regulation
- Laboratory principles underlying molecular diagnostics
Basics of Genetics
Basics of Genetics
Basics of Genetics
- Mendelian inheritance and patterns of transmission
- Chromosomal organization and karyotype concepts
- Modes of inheritance: autosomal, X-linked, mitochondrial
- Pedigree construction and interpretation
- Introduction to population and medical genetics
Human Genomics
Basics of Genetics
Genetic Engineering
- Organization of the human genome
- Genomic variation: SNPs, CNVs, structural variants
- Genome sequencing technologies and applications
- Reference genomes and annotation databases
- Clinical relevance of genomic data in health and disease
Genetic Engineering
Mutations and Mutational Analysis
Genetic Engineering
- Recombinant DNA technology principles
- Gene cloning, vectors, and expression systems
- CRISPR-Cas and genome editing concepts
- Applications in research, diagnostics, and therapeutics
- Ethical and safety considerations in genetic modification
Mutations and Mutational Analysis
Mutations and Mutational Analysis
Mutations and Mutational Analysis
- Types of mutations: point, frameshift, structural
- Germline vs. somatic mutations
- Functional consequences of mutations on proteins
- Methods for mutation detection and analysis
- Interpretation of pathogenic vs. benign variants
Cancer Genetics
Mutations and Mutational Analysis
Mutations and Mutational Analysis
- Genetic basis of cancer development
- Oncogenes, tumor suppressor genes, and driver mutations
- Hereditary cancer syndromes and familial risk
- Somatic mutations in tumor biology
- Role of genetics in cancer risk assessment and management
Rare Genetic Disorders
Genetic Testing and Gene Therapy
Genetic Testing and Gene Therapy
- Classification of rare and inherited disorders
- Monogenic diseases and genotype–phenotype correlations
- Inborn errors of metabolism
- Diagnostic approaches for rare diseases
- Impact of rare disorders on families and populations
Genetic Testing and Gene Therapy
Genetic Testing and Gene Therapy
Genetic Testing and Gene Therapy
- Types of genetic tests: diagnostic, predictive, carrier screening
- Indications and limitations of genetic testing
- Interpretation of genetic test reports
- Basics of gene therapy and targeted treatments
- Ethical, legal, and social implications of genetic testing
Introduction to AI in Genomics
Genetic Testing and Gene Therapy
Introduction to AI in Genomics
- Live online instruction by expert faculty
- Hands-on training in AI applications in healthcare/genomics
- Learn data-driven decision making and clinical analytics
- Apply AI tools for diagnostics, precision medicine, and research
- Flexible fully online format with interactive sessions
Phase 2 - Applied AI in Genomics by Greek University
AI-Driven Variant Analysis & Risk Assessment
AI-Driven Variant Analysis & Risk Assessment
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
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
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
Pharmacogenomics & Treatment Optimization
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
Advanced Diploma in AI in Genomics
Duration: 6 Months taught online Total Program Fee: $2499
This 6-month online Advanced Diploma includes 4 structured advanced courses in AI applications in Genomics. Students gain full access to live online classes, course materials, assessments, and receive the advanced diploma upon successful completion.