MLOps.community Courses

Unified Data and AI Governance with Unity Catalog

Explore Unity Catalog's approach to simplifying governance across diverse data and AI assets, addressing challenges in multi-vendor landscapes and enhancing control over resources.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

11 Lessons Learned from Doing AI Deployments - DE4AI

Discover 11 crucial lessons for AI product deployment at scale. Gain insights into technical and non-technical challenges faced during the development of 200+ POCs and 40+ production products.

• YouTube
• 36 minutes
• Self-Paced
• Free Video

The Daft Distributed Python Data Engine: Multimodal Data Curation at Any Scale

Explore Daft, an open-source Python data engine for ML/AI platforms. Learn to build performant data systems using Daft Dataframe and open file formats for ETL, analytics, and dataloading at scale.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Reproducible Data Science Over Data Lakes

Explore reproducible data science techniques for data lakes using Bauplan and Nessie. Learn to decouple compute from data management, enabling time-travel and branching semantics for enhanced pipeline reproducibility.

• YouTube
• 12 minutes
• Self-Paced
• Free Video

Data Contracts and Observability: Complementary Approaches to Data Quality

Explore the complementary roles of data contracts and observability in ensuring data quality. Learn how these approaches work together to prevent known issues and detect unknown ones across data systems.

• YouTube
• 14 minutes
• Self-Paced
• Free Video

Scaling Data Reliably: A Journey in Growing Through Data Pain Points

Explore data reliability engineering techniques to minimize downtime, implement service level metrics, and enhance monitoring for robust data pipelines and improved system performance.

• YouTube
• 16 minutes
• Self-Paced
• Free Video

An Overview of Common ML Serving Architectures

Explore common ML serving architectures, industry constraints, and practical deployment designs. Learn to bridge the gap between theory and real-world implementation in MLOps.

• YouTube
• 18 minutes
• Self-Paced
• Free Video

Data Engineering for Streamlining the Data Science Developer Experience - DE4AI

Optimize feature engineering for low-latency fraud detection models. Learn infrastructure and frameworks to streamline data scientist workflows and ensure feature parity between training and inference.

• YouTube
• 12 minutes
• Self-Paced
• Free Video

Partnering with Product for Effective Data Ingestion and Training Data

Discover strategies for collaborating with product teams to optimize data collection, architecture, and ML model success. Learn to prove ROI and leverage product analytics for effective data-driven decision-making.

• YouTube
• 19 minutes
• Self-Paced
• Free Video

Real-Time Data Streaming Architectures for Generative AI

Explore real-time data streaming architectures for GenAI, leveraging Apache Kafka and Flink to enhance performance and reliability of applications through the "shift-left" paradigm and RAG method.

• YouTube
• 12 minutes
• Self-Paced
• Free Video

The Evolution of Lyft's ML Feature Store

Explore Lyft's ML feature store evolution, its impact on business, and insights from a seasoned data engineer's perspective.

• YouTube
• 13 minutes
• Self-Paced
• Free Video

Chronon: Airbnb's Open-Source Data Platform for AI and ML Applications

Explore Chronon, an open-source data platform for AI/ML applications, and learn how it accelerates AI/ML efforts in organizations.

• YouTube
• 13 minutes
• Self-Paced
• Free Video

Data Mesh: Composability over Ideology in the Data Stack - DE4AI

Explore Whatnot's journey in balancing reliable data services with decentralized ownership. Learn practical frameworks for maturing data services and patterns to increase adoption while reducing maintenance.

• YouTube
• 13 minutes
• Self-Paced
• Free Video

LLMs and Beyond with Lepton - Observations on Utilization and Enterprise AI Strategy

Explore LLM applications, challenges, and enterprise AI strategies with insights from algorithm and infrastructure perspectives. Gain practical knowledge for efficient AI implementation.

• YouTube
• 14 minutes
• Self-Paced
• Free Video

From Notebook to Kubernetes: Scaling GenAI Pipelines with ZenML

Scale generative AI pipelines from local development to cloud deployment using ZenML's open-source MLOps framework, featuring Kubernetes integration and caching for streamlined workflows.

• YouTube
• 13 minutes
• Self-Paced
• Free Video