Food Production Courses

Packt

Flask Fundamentals, App Basics, and Food Tracker App

Master Flask web development by building real-world apps—routing, SQLAlchemy databases, Jinja2 templates, user authentication, REST APIs, and cloud deployment on Amazon Lightsail.

• Coursera
• 8 weeks, 1 hour a week
• Self-Paced
• Paid Course

Pragmatic AI Labs

GitHub Production Applications

Build a complete production app using GitHub Copilot, covering API design, business logic, database persistence, testing, and code review in a real-world development workflow.

• Coursera
• 3 weeks, 1 hour a week
• Self-Paced
• Paid Course

Career Certificate

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

Architecting with Google Kubernetes Engine: Production en Français

Découvrez la sécurité, la surveillance et l'intégration des services Google Cloud avec GKE. Approfondissez vos connaissances en architecture Kubernetes pour des déploiements de production robustes.

• Coursera
• 7 weeks, 1 hour a week
• Self-Paced
• Paid Course

Architecting with Google Kubernetes Engine: Production em Português Brasileiro

Aprenda segurança, monitoramento e integração de serviços gerenciados no Google Kubernetes Engine. Explore controle de acesso, logs, armazenamento e CI/CD para implantar aplicativos em produção de forma eficiente.

• Coursera
• 7 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Validate LLM Embeddings for Production Use

Master validation and deployment of embedding models for production semantic search systems using FAISS, UMAP, and systematic evaluation techniques.

• Coursera
• 3 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Validating and Safeguarding Production AI

Discover how to build robust production AI systems with automated monitoring, drift detection, secure deployment, and continuous retraining pipelines for reliable MLOps.

• Coursera
• 7 weeks, 2 hours a week
• Self-Paced
• Paid Course

Packt

Deploying, Evaluating, and Scaling Production AI Systems

Master deploying, evaluating, and scaling production AI systems using LangChain and LangGraph, with hands-on experience in observability, cost management, and enterprise-level deployment strategies.

• Coursera
• 4 weeks, 1 hour a week
• Self-Paced
• Paid Course

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
• 13 weeks, 1 hour a week
• Self-Paced
• Paid Course

KodeKloud

Deploy ML Models to Production

Master MLOps by deploying ML models from development to production using MLflow, BentoML, and AWS SageMaker with hands-on insurance claim application project.

• Coursera
• 3 weeks, 1 hour a week
• Self-Paced
• Paid Course

Board Infinity

Deploying AI Agents: LLMs, LangGraph, and Production APIs

Master deploying LLM-powered AI agents using LangGraph, FastAPI, and CrewAI—covering schema validation, persistent memory, orchestration, and benchmarking for enterprise-grade production systems.

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

Coursera

Designing Production LLM Architectures

Master production-ready LLM system design, from architecture decisions to scalable microservices, deployment strategies, and automated data pipelines for real-world applications.

• Coursera
• 5 weeks, 2 hours a week
• 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

Engineer Features and Evaluate Models for Production

Discover how to build production-grade ML systems with robust feature engineering pipelines and advanced model evaluation techniques using scikit-learn and TensorBoard.

• Coursera
• 2 weeks, 1 hour a week
• Self-Paced
• Paid Course

LearnKartS

Build Production AI Agents with RAG & MCP

Master building production-ready AI agents using RAG & MCP, integrating Gemini and OpenAI with Node.js backends, embeddings, semantic search, and scalable architectures for real-world applications.

• Coursera
• 3 weeks, 4 hours a week
• Self-Paced
• Paid Course