Digital-UNI original programs

Learning pathways built for applied work and interviews

Each pathway combines focused Digital-UNI instruction, practical assignments, a portfolio capstone, interview preparation, and carefully selected official reference material.

Catalog reviewed September 2026

Pathway 01

AI, Machine Learning & Data Science

Build, evaluate, explain, and deploy a data-driven model with reproducible evidence.

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Digital-UNI curriculum

1Python, NumPy, Pandas, SQL, and data quality
2Exploratory analysis, visualization, and statistical reasoning
3Regression, classification, clustering, and model selection
4Neural networks, TensorFlow/Keras, computer vision, and NLP
5Deployment, monitoring, drift, documentation, and responsible AI

Applied capstone

An end-to-end model, model card, evaluation report, and live demonstration.

Interview preparation

Coding, statistics, feature design, experiment review, and ML system design.

Official supplemental references

These links broaden preparation; they are not Digital-UNI lessons and do not create a partnership or transfer an external credential.

Pathway 02

Generative AI, RAG & AI Agents

Design a reliable tool-using assistant with retrieval, evaluations, safety controls, and human approval.

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Digital-UNI curriculum

1Foundation models, context, embeddings, and multimodal inputs
2Prompt design, structured output, retrieval, citations, and grounding
3Tools, agent loops, state, memory boundaries, and interoperability
4Evaluations, red teaming, guardrails, privacy, latency, and cost
5Production observability, human escalation, and failure recovery

Applied capstone

A grounded multilingual assistant with a test set, evaluation results, audit trail, and human-review checkpoints.

Interview preparation

RAG design, hallucination analysis, tool security, prompt injection, and evaluation strategy.

Official supplemental references

These links broaden preparation; they are not Digital-UNI lessons and do not create a partnership or transfer an external credential.

Pathway 03

Cybersecurity & Cloud Security

Defend a cloud-connected environment and communicate risk, evidence, and response decisions.

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Digital-UNI curriculum

1Networking, Linux, identity, access, cryptography, and secure configuration
2Threat modeling, vulnerability management, and zero-trust principles
3Cloud responsibility, secrets, logging, containers, and infrastructure as code
4SOC triage, detection engineering, incident response, and recovery
5Secure AI systems, supply-chain risk, and post-quantum migration awareness

Applied capstone

A cloud threat model, hardened reference deployment, detection lab, and incident report.

Interview preparation

Log investigation, IAM design, incident scenarios, architecture review, and risk prioritization.

Official supplemental references

These links broaden preparation; they are not Digital-UNI lessons and do not create a partnership or transfer an external credential.

Pathway 04

Cloud Computing, DevOps & Programming

Ship a secure, observable application through a repeatable development and deployment pipeline.

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Digital-UNI curriculum

1Python, TypeScript, APIs, testing, Git, and code review
2Linux, networking, containers, orchestration, and infrastructure as code
3Cloud architecture, serverless functions, storage, queues, and resiliency
4CI/CD, secrets, software supply-chain controls, and rollback
5Metrics, logs, traces, performance, cost, and reliability engineering

Applied capstone

A tested application deployed through CI/CD with monitoring, security checks, and rollback documentation.

Interview preparation

API design, debugging, distributed systems, reliability, and architecture trade-offs.

Official supplemental references

These links broaden preparation; they are not Digital-UNI lessons and do not create a partnership or transfer an external credential.

Pathway 05

Blockchain, Smart Contracts & Digital Assets

Evaluate when a distributed ledger is appropriate and build a secure, testable prototype.

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Digital-UNI curriculum

1Distributed systems, consensus, cryptographic hashes, keys, and wallets
2Ledger architectures, transactions, tokens, and custody models
3Smart-contract design, testing, upgrade risk, and common exploits
4Privacy, interoperability, governance, compliance, and operational risk
5Digital-asset economics, market structure, evidence, and responsible claims

Applied capstone

A test-network application with threat model, contract tests, governance plan, and user-risk disclosure.

Interview preparation

Consensus trade-offs, key management, contract vulnerabilities, scalability, and custody.

Official supplemental references

These links broaden preparation; they are not Digital-UNI lessons and do not create a partnership or transfer an external credential.

Pathway 06

Executive AI Leadership & Governance

Lead an AI portfolio with measurable value, governance, workforce planning, and accountable risk decisions.

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Digital-UNI curriculum

1AI opportunity discovery and business-case validation
2Data, talent, operating model, procurement, and build-versus-buy decisions
3Portfolio governance, risk ownership, human oversight, and responsible use
4Cybersecurity, privacy, intellectual property, vendor, and regulatory diligence
5Adoption metrics, financial controls, incident readiness, and board reporting

Applied capstone

An executive AI strategy, investment roadmap, governance charter, KPI dashboard, and board briefing.

Interview preparation

CEO/CTO/CIO/COO cases covering value, governance, transformation, procurement, and crisis response.

Official supplemental references

These links broaden preparation; they are not Digital-UNI lessons and do not create a partnership or transfer an external credential.

Pathway 07

AI Corporate Financial Audit & M&A

Use AI-supported analysis to strengthen diligence while preserving evidence, controls, and professional judgment.

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Digital-UNI curriculum

1Financial statements, valuation drivers, data lineage, and reconciliation
2Anomaly detection, document extraction, and reproducible analysis
3M&A screening, quality of earnings, scenarios, and integration risk
4Model validation, access control, audit trails, confidentiality, and human sign-off
5Reporting assumptions, limitations, exceptions, and unresolved evidence

Applied capstone

A controlled diligence analysis with valuation scenarios, evidence register, and review memorandum.

Interview preparation

Financial modeling, control testing, anomalies, deal risks, explainability, and escalation decisions.

Official supplemental references

These links broaden preparation; they are not Digital-UNI lessons and do not create a partnership or transfer an external credential.

Pathway 08

AI for Lawyers, Courts & Legal Operations

Use AI decision-support tools with confidentiality, verification, jurisdiction awareness, and human responsibility.

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Digital-UNI curriculum

1Legal research, source verification, citations, and document provenance
2Contract and litigation analysis with privilege and confidentiality controls
3Court operations, clerk assistance, service data, and jurisdictional checks
4Bias, due process, explainability, record preservation, and judicial independence
5Human review, professional responsibility, procurement, and validation

Applied capstone

A legal decision-support prototype with verified sources, a risk register, access controls, and human-review protocol.

Interview preparation

Citation verification, confidentiality, practice boundaries, bias, evidence, and failed-model scenarios.

Official supplemental references

These links broaden preparation; they are not Digital-UNI lessons and do not create a partnership or transfer an external credential.

How Digital-UNI certification works

A Digital-UNI certificate is awarded only after the learner completes the Digital-UNI lessons, required assignments, capstone, and final assessment. External exams, badges, certificates, licenses, and university credit remain separate and are issued only by the named provider.

Digital-UNI independently develops and delivers its educational programs and certification assessments. References to external institutions, companies, publications, and publicly available materials are provided for supplemental educational purposes only and do not imply sponsorship, endorsement, affiliation, accreditation, or joint certification.

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