Lesson proof
Concept, demo, checklist, lab, and assignment evidence.
MLOps / ML Engineering / Cloud AI / MLOps Engineer
MLOps Engineer
Build production MLOps skills across dataset versioning, feature pipelines, experiment tracking, model registry, CI/CD, deployment, monitoring, drift detection, governance, cost, and safe rollback.
MLOps pipeline evidenceModel operations readinessResponsible AI governance proof
Start domain mock testPlatform-wide module outputs
Every module now feeds portfolio proof and CV readiness.
Portfolio pack
Requirement, artifact, validation, risk note, and interview story.
CV signal
Role-specific skill statement linked to a score or artifact.
Review queue
Submitted evidence can support dashboard, readiness, and career exports.
Open materials
MLOps foundations and operating modelLesson + portfolio pack + CV evidenceData versioning lineage and quality checksLesson + portfolio pack + CV evidenceFeature stores pipelines and reproducibilityLesson + portfolio pack + CV evidenceExperiment tracking metrics and model comparisonLesson + portfolio pack + CV evidenceModel registry approval and release governanceLesson + portfolio pack + CV evidenceML CI/CD testing packaging and promotionLesson + portfolio pack + CV evidenceBatch real-time and edge model deploymentLesson + portfolio pack + CV evidenceModel monitoring drift bias latency and costLesson + portfolio pack + CV evidenceIncident response rollback and retraining triggersLesson + portfolio pack + CV evidenceResponsible AI security privacy and complianceLesson + portfolio pack + CV evidenceCloud MLOps platforms and tooling strategyLesson + portfolio pack + CV evidenceMLOps production capstoneLesson + portfolio pack + CV evidence
Certification objective coverage
Every provider-aligned module is connected to a lesson, labs, mock questions, and implementation proof.
This is the track-level audit view for blueprint alignment. Exact exam wording should still be checked against the current official provider guide before public exam-code claims are made.
mlops-engineer.mlops-foundations-and-operating-model.01 / 8% weight
Apply MLOps foundations and operating model decisions to MLOps Engineer scenarios
Implementation proof
- Define MLOps foundations and operating model in plain language and explain the provider service family it belongs to.
- Show how MLOps foundations and operating model is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.data-versioning-lineage-and-quality-checks.02 / 8% weight
Apply Data versioning lineage and quality checks decisions to MLOps Engineer scenarios
Implementation proof
- Define Data versioning lineage and quality checks in plain language and explain the provider service family it belongs to.
- Show how Data versioning lineage and quality checks is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.feature-stores-pipelines-and-reproducibility.03 / 8% weight
Apply Feature stores pipelines and reproducibility decisions to MLOps Engineer scenarios
Implementation proof
- Define Feature stores pipelines and reproducibility in plain language and explain the provider service family it belongs to.
- Show how Feature stores pipelines and reproducibility is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.experiment-tracking-metrics-and-model-comparison.04 / 8% weight
Apply Experiment tracking metrics and model comparison decisions to MLOps Engineer scenarios
Implementation proof
- Define Experiment tracking metrics and model comparison in plain language and explain the provider service family it belongs to.
- Show how Experiment tracking metrics and model comparison is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.model-registry-approval-and-release-governance.05 / 8% weight
Apply Model registry approval and release governance decisions to MLOps Engineer scenarios
Implementation proof
- Define Model registry approval and release governance in plain language and explain the provider service family it belongs to.
- Show how Model registry approval and release governance is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.ml-ci-cd-testing-packaging-and-promotion.06 / 8% weight
Apply ML CI/CD testing packaging and promotion decisions to MLOps Engineer scenarios
Implementation proof
- Define ML CI/CD testing packaging and promotion in plain language and explain the provider service family it belongs to.
- Show how ML CI/CD testing packaging and promotion is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.batch-real-time-and-edge-model-deployment.07 / 8% weight
Apply Batch real-time and edge model deployment decisions to MLOps Engineer scenarios
Implementation proof
- Define Batch real-time and edge model deployment in plain language and explain the provider service family it belongs to.
- Show how Batch real-time and edge model deployment is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.model-monitoring-drift-bias-latency-and-cost.08 / 8% weight
Apply Model monitoring drift bias latency and cost decisions to MLOps Engineer scenarios
Implementation proof
- Define Model monitoring drift bias latency and cost in plain language and explain the provider service family it belongs to.
- Show how Model monitoring drift bias latency and cost is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.incident-response-rollback-and-retraining-triggers.09 / 8% weight
Apply Incident response rollback and retraining triggers decisions to MLOps Engineer scenarios
Implementation proof
- Define Incident response rollback and retraining triggers in plain language and explain the provider service family it belongs to.
- Show how Incident response rollback and retraining triggers is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.responsible-ai-security-privacy-and-compliance.10 / 8% weight
Apply Responsible AI security privacy and compliance decisions to MLOps Engineer scenarios
Implementation proof
- Define Responsible AI security privacy and compliance in plain language and explain the provider service family it belongs to.
- Show how Responsible AI security privacy and compliance is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.cloud-mlops-platforms-and-tooling-strategy.11 / 8% weight
Apply Cloud MLOps platforms and tooling strategy decisions to MLOps Engineer scenarios
Implementation proof
- Define Cloud MLOps platforms and tooling strategy in plain language and explain the provider service family it belongs to.
- Show how Cloud MLOps platforms and tooling strategy is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
mlops-engineer.mlops-production-capstone.12 / 12% weight
Apply MLOps production capstone decisions to MLOps Engineer scenarios
Implementation proof
- Define MLOps production capstone in plain language and explain the provider service family it belongs to.
- Show how MLOps production capstone is implemented through a guided configuration, simulator, command, diagram, notebook, or case study.
- Capture evidence with screenshots, command output, logs, metrics, topology state, policy review, query result, or troubleshooting notes.
- Connect the evidence to a portfolio pack, CV-ready skill statement, and mock-test weak-domain recovery action.
Evidence requirements
- Correct scenario decision in mock exam
- Written explanation of the key requirement or constraint
- Hands-on lab evidence or troubleshooting proof
- Portfolio pack with requirement, artifact, validation, risk note, and interview story
- CV-ready skill statement linked to a score, artifact, or project result
Test readiness
Mock test by domain
Practice every domain in this track with exam-style questions, answer keys, and explanations.
Open mock testMost in-demand certification materials
High-value certificates connected to this track.
CompTIA
CompTIA Security+
Needs reviewLast verified: Not verifiedNext review: Provider source review required
Entry security, cloud security fundamentals, and broad IT baseline roles.
CompTIA Security+ is mapped to platform lessons and labs, but still needs a dated official-source review.
- Security terminology flashcards
- Risk, identity, encryption, network, and incident-response checklist
- Scenario questions covering least privilege, logging, malware, and secure operations
AWS
AWS Certified Cloud Practitioner (CLF-C02)
CurrentLast verified: 2026-06-24Next review: 2026-09-22
Beginners and career switchers who need cloud concepts, pricing, shared responsibility, global infrastructure, and core AWS service literacy.
CLF-C02 was verified against the official AWS certification page on 2026-06-24. Keep this source check on the 90-day review cadence.
AWS official-source stamp
Foundational / CLF-C02
Official domain weighting
Cloud Concepts24%
Security and Compliance30%
Cloud Technology and Services34%
Billing, Pricing, and Support12%
Lab focus
- Service-family mapping
- Shared responsibility
- IAM baseline
- Billing and support signals
Readiness gates
- Foundation lessons complete
- Core AWS service map complete
- Billing/security quiz passed
- Cleanup evidence captured
- Cloud concepts, global infrastructure, billing, support, and shared-responsibility notes
- AWS compute, storage, database, networking, security, monitoring, and pricing service map
- Foundation scenario drills for service selection, cost awareness, and cloud adoption
PeopleCert / ITIL
ITIL Foundation Version 5
Needs reviewLast verified: Not verifiedNext review: Provider source review required
Support, operations, service desk, cloud operations, and team-lead learners who need service value, incident, change, SLA, and continual improvement fluency.
ITIL Foundation Version 5 is mapped to platform lessons and labs, but still needs a dated official-source review.
- Service value system, value chain, guiding principles, and practice vocabulary map
- Incident, problem, change, request, service level, knowledge, and continual improvement drills
- Service review evidence pack with tickets, SLA metrics, improvement actions, and stakeholder communication
GitHub
GitHub Foundations
Needs reviewLast verified: Not verifiedNext review: Provider source review required
Software, DevOps, cloud, data, and AI learners proving repository workflow, collaboration, issues, pull requests, and portfolio evidence.
GitHub Foundations is mapped to platform lessons and labs, but still needs a dated official-source review.
- Repository, commit, branch, pull request, issue, release, and project-board checklist
- Code review, branch protection, README, and portfolio repository quality rubric
- Workflow scenario drills for collaboration, review, release notes, and change history
Google Skillshop
Google Analytics Certification
Needs reviewLast verified: Not verifiedNext review: Provider source review required
Design, marketing, product, and business learners who need GA4 events, conversions, audiences, acquisition, and reporting fluency.
Google Analytics Certification is mapped to platform lessons and labs, but still needs a dated official-source review.
- GA4 event, conversion, UTM, audience, report, and attribution vocabulary map
- Measurement plan and dashboard checklist for websites, campaigns, and landing pages
- Optimization scenario drills connecting traffic, conversion, content, and campaign decisions
Certification provider connections
Connect this learning path to the official exam provider.
CompTIA Certification
CompTIA Security+
Use CompTIA objectives as the checklist, then connect Security+, Network+, or Cloud+ progress to the learner dashboard.
Booking partner: Pearson VUE
- Create or confirm the CompTIA account.
- Review the official exam guide, ID policy, delivery options, and reschedule rules.
- Add target exam date, booking status, renewal date, and certificate proof to the learner record.
AWS Certification
AWS Certified Cloud Practitioner (CLF-C02)
Use the AWS Certification account to review exam guides, book exams, manage score reports, and share verified badges.
Booking partner: Pearson VUE or PSI, depending on exam and region
- Create or confirm the AWS Certification account.
- Review the official exam guide, ID policy, delivery options, and reschedule rules.
- Add target exam date, booking status, renewal date, and certificate proof to the learner record.
PeopleCert
ITIL Foundation Version 5
Connect ITIL and service-management readiness to the learner's exam booking, certificate proof, and renewal reminders.
Booking partner: PeopleCert
- Create or confirm the PeopleCert account.
- Review the official exam guide, ID policy, delivery options, and reschedule rules.
- Add target exam date, booking status, renewal date, and certificate proof to the learner record.
GitHub Certifications
GitHub Foundations
Connect repository, Actions, security, and collaboration evidence to certification readiness and portfolio exports.
Booking partner: GitHub exam delivery partner
- Create or confirm the GitHub account.
- Review the official exam guide, ID policy, delivery options, and reschedule rules.
- Add target exam date, booking status, renewal date, and certificate proof to the learner record.
Google Skillshop
Google Analytics Certification
Use Skillshop for Google product credentials and connect analytics or marketing evidence to learner progress.
Booking partner: Google Skillshop
- Create or confirm the Google Skillshop profile.
- Review the official exam guide, ID policy, delivery options, and reschedule rules.
- Add target exam date, booking status, renewal date, and certificate proof to the learner record.
01 Match
Map each Daskerel track to the official provider, exam code, registration page, and verification route.
02 Prepare
Use provider objectives with Daskerel lessons, mock exams, labs, and evidence packs before booking.
03 Book
Send learners to the official scheduling partner while keeping target dates and next actions in the dashboard.
04 Verify
Capture certificate URL, badge, expiry, renewal plan, and portfolio proof after the learner passes.
Study plan
Start with the lifecycle: data, features, training, evaluation, registry, deployment, monitoring, incident response, retraining, and governance.
Practise evidence capture for every stage: version IDs, quality checks, experiment metrics, approval notes, deployment logs, monitoring signals, and rollback plan.
Connect MLOps to platform settings by treating cost, access, privacy, safety, observability, and portfolio proof as required deliverables.
Hands-on labs
Design an MLOps lifecycle map with data sources, feature pipeline, experiment tracking, registry, deployment target, monitoring, and retraining loop.
Create a data quality and versioning checklist with schema checks, drift checks, lineage, ownership, access, and reproducibility notes.
Compare two model runs using metrics, parameters, dataset version, error analysis, fairness notes, and approval criteria.
Write a CI/CD pipeline plan for model packaging, tests, security scan, registry promotion, deployment, smoke test, and rollback.
Define monitoring signals for prediction quality, data drift, latency, cost, bias, incident severity, and retraining triggers.
Package an MLOps portfolio artifact with lifecycle diagram, pipeline plan, model card, monitoring dashboard, incident runbook, and governance notes.
Track learning assets
Templates and revision tools for this path.
Exam blueprint checklistMLOps Engineer
Weekly study plannerMLOps Engineer
Command and service cheat sheetMLOps Engineer
Architecture pattern cardsMLOps Engineer
Flashcard revision setMLOps Engineer
Mock exam review sheetMLOps Engineer
Lab evidence templateMLOps Engineer
Interview story builderMLOps Engineer
Portfolio project rubricMLOps Engineer
Final readiness checklistMLOps Engineer
Practice questions
What separates MLOps from a one-off notebook model?
MLOps adds reproducible data and feature pipelines, experiment tracking, approval gates, deployment automation, monitoring, incident response, governance, and retraining controls.
Why should model monitoring include more than accuracy?
Production models also need monitoring for data drift, prediction distribution, latency, cost, bias, errors, usage, dependency health, and business impact.
What evidence should be saved for a model release?
Save dataset and feature versions, experiment metrics, model card, approval record, deployment logs, smoke tests, monitoring configuration, rollback plan, and governance notes.