Food Production Courses

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MLOps1 (GCP): Deploying AI & ML Models in Production using Google Cloud Platform

Deploy AI & ML models in production using GCP. Learn data pipelines, versioning, model storage, and monitoring. Gain hands-on experience with key MLOps concepts for effective deployment and maintenance of machine learning models.

• edX
• 4 weeks, 5-7 hours/week
• Self-Paced
• Free Online Course (Audit)

Credential

Machine Learning Engineering for Production (MLOps)

Develop production-ready ML systems: conceptualize, build, and maintain integrated solutions that handle evolving data, operate continuously, and balance cost with performance for real-world AI applications.

• Coursera
• 17 weeks, 6 hours a week
• Self-Paced
• Paid Course
• 4 courses

Coursera

YouTube Production: Video Fundamentals

Master smartphone video production techniques to create polished YouTube content using everyday items, covering lighting, framing, audio, and engagement strategies.

• Coursera
• 48 minutes
• Self-Paced
• Paid Course

Packt

Advanced TypeScript: Building Production-Grade Applications

Master advanced TypeScript concepts—union types, mapped types, generics, and conditional types—to build scalable, production-grade applications through hands-on exercises mirroring real-world challenges.

• Coursera
• 14 hours 6 minutes
• Self-Paced
• Paid Course

Coursera

Develop Production-Ready ML APIs with MLOps

Master MLOps practices—version control, CI/CD pipelines, and FastAPI microservices—to build and deploy production-ready ML APIs that serve transformer models at scale.

• Coursera
• 2 hours 33 minutes
• Self-Paced
• Paid Course

Coursera

Production ML Engineering: Packaging, APIs, and Testing

Master the end-to-end process of packaging ML models, building production APIs, implementing CI/CD workflows, and designing automated tests to deploy reliable machine learning systems.

• Coursera
• 11 hours 20 minutes
• Self-Paced
• Paid Course

Snowflake

Apache Iceberg: From Zero to Production Data Lakehouse

Master Apache Iceberg from setup to production, covering lakehouse architecture, table optimization, data migration, schema evolution, and maintenance operations using Spark and Trino.

• Coursera
• 5 hours 45 minutes
• Self-Paced
• Paid Course

Food Photography (Self-Paced)

Learn how to create mouth-watering food images through thoughtful styling, lighting, and composition.

• CourseHorse
• Self-Paced
• $74.00

Coursera

Optimizing Models for Production

Master quantization, inference optimization, and hardware tuning to deploy efficient, scalable generative AI models in production environments.

• Coursera
• 8 hours 40 minutes
• Self-Paced
• Paid Course

Pragmatic AI Labs

Production ML with Hugging Face

Master production ML deployment using the Sovereign Rust Stack with zero Python dependencies across GPU, CPU, WebAssembly, and edge targets through hands-on projects.

• Coursera
• 5 hours 27 minutes
• Self-Paced
• Paid Course

Coursera Credential

ML Production Systems

Master containerization, deployment, and MLOps practices to transform ML models into scalable production systems using Docker, Kubernetes, and automated pipelines.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 4 courses

Coursera

Deploying and Maintaining Production AI Systems

Master MLOps and site reliability engineering to deploy generative AI systems safely, automate model lifecycle management, and maintain peak performance in production.

• Coursera
• 12 hours 56 minutes
• Self-Paced
• Paid Course

Board Infinity

Advance Multi-Agent Systems & Production AI with LangSmith

Master multi-agent AI systems using LangSmith, LangChain, and ChromaDB. Build RAG pipelines, vector databases, conversational agents, and production-ready workflows with observability and optimization tools.

• Coursera
• 15 hours 43 minutes
• Self-Paced
• Paid Course

Board Infinity

MLOps and LLMOps: Deploying and Scaling AI in Production

Master deploying and scaling AI systems in production—covering MLOps, LLMOps, CI/CD pipelines, RAG, Kubernetes, observability, and automated evaluation with real-world tools.

• Coursera
• 17 hours 19 minutes
• Self-Paced
• Paid Course

Pragmatic AI Labs

Build a Production SaaS Application with AI

Master building a complete SaaS app with AI tools—covering FastAPI development, Docker containerization, CI pipelines, landing pages, pricing tiers, API authentication, and deployment from MVP to production launch.

• Coursera
• 4 hours
• Self-Paced
• Paid Course