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MEAN Stack Project 2026 - Build a Real-Time Trello Clone (Packt)
MERN eCommerce from Scratch (Packt)
MIPS Computer Architecture and Performance Optimization (Birla Institute of Technology & Science, Pilani)
MITRE ATT&CK Framework – Foundations for Cyber Defense (Packt)
ML Concepts, Models & Workflow Essentials (Coursera)
ML Data Pipelines and Communicating AI Insights (Coursera)
ML Engineer - Analyze and Evaluate Performance (Amazon Web Services)
ML Engineer - Automated Orchestration and CI/CD (Amazon Web Services)
ML Engineer - Choose Modeling Approaches (Amazon Web Services)
ML Engineer - Collect, Ingest, and Store Data (Amazon Web Services)
ML Engineer - Customize and Fine Tune Models (Amazon Web Services)
ML Engineer - Manage Deployment Infrastructure (Amazon Web Services)
ML Engineer - Monitor Model Inference (Amazon Web Services)
ML Engineer - Optimize Costs and Performance (Amazon Web Services)
ML Engineer - Provision and Configure Resources (Amazon Web Services)
ML Engineer - Secure ML and AI Workloads (Amazon Web Services)
ML Engineer - Train Models (Amazon Web Services)
ML Engineer - Validate Data and Prepare for Modeling (Amazon Web Services)
ML Engineer- Data Transformation and Feature Engineering (Amazon Web Services)
ML Model Deployment: Build a Production API with FastAPI (Board Infinity )
ML Model Development and Tracking: Hands-on Guide (KodeKloud)
ML Parameters Optimization: GridSearch, Bayesian, Random (Coursera)
ML Pipelines on Google Cloud - Français (Google Cloud)
ML Pipelines on Google Cloud - Português (Google Cloud)
ML Pipelines on Google Cloud - 日本語版 (Google Cloud)
ML Pipelines on Google Cloud - 한국어 (Google Cloud)
ML Pipelines on Google Cloud en Español (Google Cloud)
ML: Build, Train, Justify Models (Coursera)
MLOps Architecture and Scalable AI Deployment (The Skill Valley)
MLOps Foundations (Edureka)
MLOps Platforms: Amazon SageMaker and Azure ML (Duke University)
MLOps Tools: MLflow and Hugging Face (Duke University)
MLOps and LLMOps: Deploying and Scaling AI in Production (Board Infinity )
MLOps and responsible AI practices (Microsoft)
MLOps in R: Deploying machine learning models using vetiver (Coursera)
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