Advanced Machine Learning Data

You can learn why data is core part of Machine Learning Operations

In this course, you will go deeper into data for MLOps and learn how to run large, fast, and cost-aware data platforms for ML. In real systems, the hard parts are streaming, schema changes, point-in-time correctness, and keeping features consistent online and offline. Senior MLOps Engineers solve this with strong data contracts, advanced lineage, and clear SLOs.

We will cover table formats and lakehouse tuning, CDC and real-time pipelines, feature stores at scale, schema evolution, and contract-driven checks. You’ll learn how to set data SLOs, trace drift to root cause, test data code, plan rollbacks, protect privacy with practical methods, and control spend with smart layouts and scheduling.

By the end, you’ll be able to design and operate production-grade ML data platforms with resilience, observability, and cost control.

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What you’ll learn

✓ Understand how data flows through ML systems and how to build pipelines that are simple, clear, and repeatable.

✓ Use tools to version datasets, store features, and test data quality.

✓ Learn to clean, check, and track data to make sure your models work well and do not fail silently in production.

✓ Monitor how data changes over time, detect drift, and set up alerts so you know when retraining is needed.

Course Content

Course Introduction
About Your Instructor
Course Structure
What is Data for MLOps
GitHub repositories

Table Formats Deep Dive (Delta/Iceberg/Hudi): ACID, Time Travel
Performance Tuning: Partitioning, Z-Ordering, Compaction, Vacuum
Data Retention, GDPR Deletes, and Backfills at Scale
Cost-Aware Layouts and Lifecycle Policies

Exactly-Once, Watermarks, Late Data, and Reprocessing
Change Data Capture (CDC) for ML (Debezium, Log-based)
Real-Time Feature Serving and State Stores (Redis/RocksDB Concepts)
Blue/Green and Shadow Data Paths for Serving

Online/Offline Consistency Guarantees
Point-in-Time Joins and Backfills
Entity Resolution and Keys at Scale
Feature Discovery, Cataloging, and Ownership Models

Dataset and Table Versioning Patterns (Branching, Tags, Snapshots)
Schema Evolution: Add/Change/Deprecate Safely
Data Migrations and Compatibility Testing
Promotion Flows: Dev → Staging → Prod Data

End-to-End Lineage with Impact Analysis
Data Contracts at Scale
Row/Column-Level Security and Dynamic Access
Catalog as a Product: Stewardship and KPIs

Golden Datasets, Contracts-Driven Checks, and SLAs
Drift/Quality Root-Cause Analysis with Lineage
Auto-Triage and Ticketing Integration
SLOs for Data (Freshness, Completeness, Accuracy); Error Budgets

Unit, Integration, and End-to-End Tests for Data
Property-Based Testing for Transformations
Canary/Shadow Validations and Backtest Frameworks
Test Data Management and Golden Files

Incident Response for Data: Runbooks and On-Call
Backpressure, Hot Partitions, and Throughput Limits
Retry/Idempotency Strategies and Dead-Letter Queues
Disaster Recovery for Data Stacks (RPO/RTO)

De-Identification at Scale (k-Anonymity, L-Diversity, T-Closeness)
Differential Privacy
Secure Data Sharing (Clean Rooms, Controlled Joins)

Storage/Compute Trade-offs and Tiering
Incremental Processing and Materialization Plans
Workload Scheduling and Auto-Scaling for Pipelines
Cost Dashboards and Guardrails for Data Jobs

Real-Time Recommendations: Streaming + Feature Store
High-Frequency Forecasting: Sliding Windows at Scale
LLM/Embeddings Data: Chunking, Vector Stores, Freshness SLOs
Post-Mortems: Cross-Team Coordination and Fix Forward

Start learning high demand tech skills today

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About Your Instructor

Hi, I’m Alex and I’ve spent over 20 years helping well known startups and enterprises introduce innovations. I also developed and taught Cloud&DevOps part for a Master’s Degree at the University.

In this course, I’ll show you what MLOps looks like in practice – step by step, with real tools and clear guidance.

You don’t need to be an expert. If you want to understand how to start or enforce your career as MLOps Engineer, not just in theory, but in real life, this course is for you. Let’s get started.

All Courses Access

Access to all current and future courses of Nubes Academy
Access to all reading materials and downloadable resources
GitHub repository with source code

Perfect for learners who want to master this topic by themselves.

Buy for 19,95 € / month

All Courses Access +
Capstone project + …

Access to all current and future courses of Nubes Academy
Access to all reading materials and downloadable resources
GitHub repository with source code
Quizzes
Capstone Projects and Expert review of your results
Certificate of course completion
Participation in live Q&A sessions with Experts
Participation in Slack community

The best option for serious learners who wanna master real-world skills with direct expert guidance.

Buy for 119,95 € / month

All courses are developed by experienced instructors with over 10 years of real-world industry expertise. We focus on delivering practical, up-to-date content – not just collecting enrollments, so that every course gives you real value.

Our courses meet high academic standards, and we’re actively working on certification to ensure they align with recognized best practices.

Each course includes video lectures, hands-on labs with screen recordings, quizzes, reading materials, GitHub repository with real project code, and a capstone project. This structure is designed to help you build practical, in-demand skills and knowledge that employers care about.

However, if you’re not satisfied for any reason, you can request a refund in accordance with our Refund Policy – your satisfaction matters to us.

It’s not just skills. It’s your next chapter.

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