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View compareMLOps Engineer Program (AI-300 + CCFA)
Microsoft + Anthropic Dual Track New Launch
MLOps Engineer Program
Microsoft AI-300 (MLOps Engineer Associate) + Anthropic's Claude certification, in one program
- AI-300 is Microsoft's brand-new 2026 exam that replaced DP-100, for engineers who deploy and operate ML AND generative AI at scale
- Build the full lifecycle live: Azure ML pipelines, MLflow registries, managed endpoints, CI/CD promotion and drift monitoring in your own subscription
- Add GenAIOps and the Anthropic Claude certification track (CCFA), the operations skill set AI teams are hiring for right now
What you get
- 60+ hours of live weekend classes on the modern MLOps stack
- Full AI-300 exam prep with a domain-scored mock
- Dedicated Claude certification (CCFA) prep track
- 4 shipped projects: pipelines, CI/CD, monitoring & GenAIOps
- Credly + Microsoft badge milestones inside the curriculum
- Lifetime access to recordings and future batches
Next Cohort19 Sept 2026
Duration8 Weeks
TimingSat–Sun, 8–11 PM IST
FormatLive Online
60+
Hours of Live Training
2
Certifications Prepped: AI-300 & Claude (CCFA)
4
MLOps Projects You Ship
2026
Newest Microsoft ML Exam, Replaced DP-100
1:1
Dedicated Mentor Support
∞
Lifetime Access to Sessions
Built For
Who this program is for
Companies have models; what they lack is people who can run them in production. MLOps is where the hiring gap is. Tap any card to see why it fits you.
Data scientists whose DP-100 path just changed
Tap to learn moreDP-100 retired mid-2026 and AI-300 took its place with a heavier operations focus. This program covers exactly what shifted: deployment, CI/CD and monitoring at scale.
DevOps & platform engineers moving into AI infrastructure
Tap to learn moreYour pipeline and infra instincts are 70% of MLOps. We add the ML-specific 30%: experiments, registries, drift and GenAI evaluation, and certify it.
ML engineers who train models but never got to ship them
Tap to learn moreNotebook-to-production is the career jump. Managed endpoints, automated retraining and monitored rollouts turn your models into systems, and you into a senior hire.
Engineers who want the GenAIOps edge
Tap to learn moreOperating LLM systems, evaluation, prompt flows, safety monitoring, is brand new as a discipline. Learning it alongside classic MLOps puts you ahead of both camps.
Curriculum
The complete MLOps stack, module by module
Eight modules taught live over 8 weekends, mapped to the AI-300 skills outline plus a GenAIOps layer and the Anthropic Claude certification track.
1The ML Lifecycle & Azure Machine LearningModule 1
- From notebook to production: the real ML lifecycle
- Azure ML workspaces, compute and datastores
- Environments, jobs and reproducibility
- Hands-on: stand up your MLOps workspace
2Data & Feature PipelinesModule 2
- Data assets, versioning and lineage
- Feature engineering pipelines that rerun cleanly
- Data validation and quality gates
- Hands-on: versioned data pipeline for a training set
3Training at Scale: Experiments, MLflow & RegistriesModule 3
- Experiment tracking and hyperparameter sweeps
- MLflow logging, model signatures and packaging
- Model registry and promotion workflows
- Hands-on: tracked training runs with registered models
4Deployment: Managed Endpoints, Batch & Online InferenceModule 4
- Online vs batch endpoints, when each wins
- Blue-green deployments and traffic splitting
- Autoscaling, quotas and cost control
- Hands-on: deploy a model behind a managed endpoint
5CI/CD for ML: GitHub Actions & Azure DevOpsModule 5
- Pipelines that retrain, test and promote models
- Model tests: data checks, performance thresholds
- Environment promotion dev → stage → prod
- Hands-on: automated retraining pipeline with gates
6Monitoring: Drift, Data Quality & Responsible AIModule 6
- Data drift and prediction drift detection
- Alerting, dashboards and retrain triggers
- Responsible AI dashboards and model explanations
- Hands-on: full monitoring stack on your endpoint
Microsoft Certification Milestone
After Module 7's exam sprint you are exam-ready for AI-300, MLOps Engineer Associate.
7GenAIOps + AI-300 Exam SprintModule 7
- Operating LLM systems: evaluation flows and prompt management
- Safety monitoring and cost observability for GenAI
- Full AI-300 skills outline with a domain-scored mock
- Exam booking and strategy
Credly Badge Milestone
Complete the Claude track to earn the 360DT AI Operations Engineer badge for LinkedIn.
8Claude Certification Track (CCFA) + CapstoneModule 8
- Claude platform mastery and the Claude API for ops tooling
- Anthropic certification prep with practice questions
- AI-assisted runbooks: Claude drafts diagnoses and postmortems
- Capstone: fully monitored, CI/CD-managed model in production
Portfolio
4 builds you actually ship
Every project is a production MLOps pattern hiring managers probe for in interviews. Tap any card for the full brief.
Project 01
End-to-End Azure ML Pipeline
Tap for detail
Project 01
Versioned data → tracked training → registered model → managed endpoint, one reproducible pipeline with MLflow throughout.
Project 02
Automated Retraining CI/CD
Tap for detail
Project 02
A GitHub Actions workflow that retrains on new data, runs model tests, and promotes only when thresholds pass.
Project 03
Drift Monitoring & Alerting Stack
Tap for detail
Project 03
Data and prediction drift detection wired to alerts and retrain triggers, with a responsible-AI dashboard for stakeholders.
Project 04
GenAIOps Evaluation Harness
Tap for detail
Project 04
An evaluation and safety-monitoring loop for an LLM feature, with Claude generating the ops runbooks and postmortem drafts.
Skills Covered
ML Pipelines & ReproducibilityExperiment TrackingModel Registry & PromotionManaged EndpointsCI/CD for MLDrift MonitoringResponsible AIGenAIOps & LLM Evaluation
Tools & Frameworks Covered
Azure ML
MLflow
Python
GitHub Actions
Docker
Kubernetes
Terraform
Claude & Claude API
Fees & Batch
Reserve your seat for the next live batch
Live Online · Weekend Batch · 20% OFF
MLOps Engineer Program (AI-300 + CCFA)
Start Date19 September 2026
Duration8 Weeks
TimingSat–Sun, 8:00 – 11:00 PM IST
SeatsLimited per batch
₹31,249₹24,999
EMI options available · Corporate/team batches, contact us
Enroll on WhatsAppPut it in perspective: DP-100-era data science courses cost ₹35,000–₹50,000 for a retired exam and no operations depth. This preps the NEW AI-300 live, covers GenAIOps, adds an Anthropic Claude certification track, and ships four production-grade builds.
Next MLOps cohort starts 19 Sept 2026
Live, online, Saturday–Sunday · Limited seats · The operations side of AI is where the jobs are.
Reserve Your SeatFAQ
Frequently asked questions
How does AI-300 relate to DP-100?
DP-100 (Azure Data Scientist) retired on 1 June 2026 and AI-300, MLOps Engineer Associate, replaced it. The focus shifted from training models to deploying, operationalizing and maintaining ML and generative AI solutions at scale, which is what this program teaches.
Do I need to know machine learning theory?
Working Python plus a basic idea of what a model is suffices. This is an engineering program, we cover the ML concepts you need as we operationalize real models, not math derivations.
What is the CCFA / Claude certification track?
A dedicated module preparing you for Anthropic's official Claude certification, plus using Claude for operations tooling: runbooks, diagnoses and postmortems. Certification exam registration is done with Anthropic separately.
What if I miss a class?
Every session is recorded with lifetime access, and you can re-attend any future batch free.