Microsoft AuthorisedAssociate · Data Science2026 ObjectivesTop-paid Azure ML Cert
DP-100 Azure Data Scientist Associate
Train, evaluate, deploy and operate ML models on Azure Machine Learning at production grade — mapped to DP-100. The senior Microsoft data-science credential.
⏱Duration: 4 days / 32 hrs
💻Format: Instructor-Led + Azure ML Sandbox
🌐Delivery: On-site · Virtual · Hybrid
✅Pass rate: 90%
📅Next intake: 19 May 2026
🧠
AML mastery
Studio, Compute, Datastore, Pipelines, Model Registry, MLflow
⚡
Generative AI on Azure
Azure OpenAI fine-tune, Foundry, prompt flow, RAG
📊
ML lifecycle
Data prep, training, evaluation, deployment, monitoring, retraining
🔐
Responsible AI
Fairlearn, InterpretML, RAI dashboard, model cards
What this course is
Where Azure ML stops being notebooks.
DP-100 is Microsoft's Azure Data Scientist Associate credential. It validates that you can build, train, deploy, monitor and govern ML solutions on Azure ML at production quality — not just run a notebook.
At Nexperts, DP-100 is delivered on a real Azure ML workspace. By day 4 you've shipped four production-shape ML products: a tabular classifier with AML Pipelines, a deployment with model monitor, a Foundry-grounded GenAI app, and a Responsible AI dashboard for an audit-ready model.
DP-100 is the cert that distinguishes ML platform engineers from data scientists who 'use Azure'. The exam tests platform discipline, not modelling craft.
The 2026 DP-100 update broadened coverage of generative AI on Azure (Foundry, OpenAI, prompt flow), MLflow integration, and Responsible AI tooling. We cover all three with hands-on labs.
Who should take this course
🧠
ML engineers
Already work on ML and want the formal Microsoft credential.
📊
Data scientists
Comfortable modelling. DP-100 is the bridge to Azure deployment.
☁️
Azure cloud engineers
Pivoting into ML platform engineering. DP-100 gives the Azure-native lens.
👨💻
Data engineers
Adding ML capabilities to data products. DP-100 + DP-203 is the full combo.
🌟
DP-203 holders
Natural progression. DP-203 gave data depth, DP-100 adds modelling depth.
💼
Solutions architects
Designing AI-augmented Azure workloads. DP-100 keeps you honest in technical reviews.
Prerequisites
✓ 1–2 years of professional Python and ML experience
✓ Comfortable with pandas, scikit-learn or PyTorch / TensorFlow
✓ Working knowledge of supervised vs unsupervised learning, evaluation metrics
✓ Basic Azure familiarity (AZ-900 / AI-900 helpful but not required)
→ Don't have AI-900? Ask about our AI-900 → DP-100 bundle.
Course Curriculum
Four domains. One Azure ML toolkit.
DP-100 is structured into Designing ML Solutions, Exploring Data, Training Models, and Deploying & Monitoring. We deliver in lifecycle order — you ship a real model by day 2.
Hands-On Azure ML Sandbox
9 builds. Real AML + Foundry.
Every learner gets an Azure ML workspace with Foundry / OpenAI access pre-approved. By day 4 you've shipped four real ML products end-to-end.
01
Workspace Stand-Up
Bootstrap an AML workspace with compute cluster, datastore and identity.
Setup
02
Data Profiling
Profile a sample dataset and produce a feature plan with EDA notebook.
Data
03
AutoML Sprint
Run AutoML on a tabular dataset. Inspect leaderboard and explainability.
ML
04
Custom Training
Train a custom XGBoost classifier with Sweep + MLflow tracking.
ML
05
Pipelines Build
Build a 5-step AML Pipeline with conditional branching and approval.
MLOps
06
Online Endpoint
Deploy a model to a managed online endpoint. Validate with synthetic load.
Inference
07
Drift Monitoring
Configure data-drift monitoring. Inject drift, validate alert and retrain trigger.
Monitoring
08
RAI Dashboard
Build a Responsible AI dashboard for a deployed model. Pass an audit review.
Governance
09
Foundry GenAI
Build a RAG-grounded GenAI app on Foundry. Wire prompt flow + tracing.
GenAI
+ 14 micro-tasks across AML SDK v2, MLflow CLI and Foundry portal flows.
Exam Information
One scenario exam. Modelling + platform mix.
DP-100 is 40–60 questions over 100 minutes. The exam blends modelling judgement (algorithm choice, evaluation metric) with Azure-platform decisions (compute, deployment, monitoring). Most candidates fail the platform half.
End of day 1. Maps weak knowledge areas. Average 56%.
02
Decision-Heavy Mock
Mid-course. 60% platform decisions. Average 70%.
03
Final Clearance
Full timed simulation. 80%+ before we book. Average 83%.
0%
Pass Rate
90% of our DP-100 candidates pass on first attempt.
The Microsoft global first-attempt rate for DP-100 sits around 63%. We hit 90% by drilling algorithm + platform decisions on a real AML workspace and gating booking on a clearance mock.
Real AML + FoundryDecision drill90% first attemptFree retake voucherGenAI track included
Why our pass rate is 90%
Industry average: ~63%
Most candidates know the modelling but freeze on Azure-platform decisions. They pick deployment modes by feature recall, not constraint match.
Nexperts: 90%
We drill platform decisions. We deploy real models. We run real Foundry RAG. By exam day, the platform decisions are reflexive.
Your Microsoft AI Path
DP-100 pairs with DP-203 and AI-102.
DP-100 stacks naturally with DP-203 (Data Engineer) for the full data + ML combo or AI-102 (AI Engineer) for the GenAI build track.
Before this
AI-900
Foundation credential. Most DP-100 candidates have AI-900 first.
Expected salary range after DP-100: RM 11,500 – RM 18,500/month for ML engineer / senior data-scientist roles in MY MNCs.
Student Reviews
What our DP-100 engineers say.
4.8
★★★★★
86 reviews
5★
83%
4★
14%
3★
3%
★★★★★
"Foundry GenAI lab was the most valuable single lab of any cert I've taken. Took the patterns straight back to my company and shipped two GenAI features."
SD
Sundari Devi
Senior ML Engineer · Maybank Innovation
✓ Passed first attempt · 836/1000
★★★★★
"Came in as a data scientist who avoided Azure. DP-100 with Nexperts was the bridge — I now confidently own deployment and monitoring at work."
RV
Rishabh Verma
ML Engineer · Carsome
✓ Passed first attempt
★★★★
"RAI dashboard lab solved an audit problem we'd been struggling with for 4 months. Best ROI I've ever had on a course fee."
FN
Fariza Naqvi
Data Scientist · PETRONAS Digital
✓ Passed first attempt · 802/1000
★★★★★
"Mock-3 was tougher than the real exam. The decision drill makes you think like Microsoft thinks. Career-defining course."
JC
Jonathan Chai
Senior Data Scientist · Standard Chartered GBS
✓ Passed first attempt · 858/1000
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