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  • Hands On Ml Model Development

Results for "hands-on+ml+model+development"


  • C

    Coursera

    AI Model Development & Deployment

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), AWS SageMaker, Software Documentation, Data Pipelines, Tensorflow, Model Evaluation, Apache Airflow, Systems Design, Cloud Computing Architecture, Transfer Learning, Unit Testing, Cloud Deployment, PyTorch (Machine Learning Library), API Design, Cloud Computing, Network Architecture, Deep Learning, Python Programming, Data Validation

    Intermediate · Specialization · 1 - 3 Months

  • K

    KodeKloud

    Hands-On MLOps Fundamentals for ML Engineers

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Apache Airflow, Data Pipelines, Apache Kafka, DevOps, CI/CD, Apache Spark, Pandas (Python Package), Deep Learning, Applied Machine Learning, Machine Learning, Data Governance, Supervised Learning, Flask (Web Framework), Grafana, Python Programming, Automation, Unsupervised Learning, Continuous Monitoring

    Beginner · Specialization · 1 - 3 Months

  • P

    Packt

    AI Agents and MLOps for Production-Ready AI

    Skills you'll gain: MLOps (Machine Learning Operations), Containerization, AI Workflows, Model Deployment, Generative AI Agents, LangGraph, Artificial Intelligence and Machine Learning (AI/ML), CrewAI, BeeAI, Docker (Software), Agentic systems, Google Cloud Platform, AWS SageMaker, CI/CD, Cloud Platforms, DevOps, Azure DevOps Pipelines, Kubernetes, Applied Machine Learning, Scalability

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    ML Production Systems

    Skills you'll gain: Model Deployment, Unit Testing, MLOps (Machine Learning Operations), Test Driven Development (TDD), Software Testing, Scalability, Dashboard, Feature Engineering, Continuous Integration, Kubernetes, Scikit Learn (Machine Learning Library), CI/CD, Performance Tuning, Tensorflow, Python Programming, Software Engineering, PyTorch (Machine Learning Library), Docker (Software), Containerization, Git (Version Control System)

    Intermediate · Specialization · 1 - 3 Months

  • C

    Coursera

    ML Model Training & Validation

    Skills you'll gain: MLOps (Machine Learning Operations), Data Pipelines, Model Evaluation, Systems Design, Transfer Learning, Data Preprocessing, Data Quality, Feature Engineering, Deep Learning, Python Programming, Data Validation, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Software Engineering, Debugging, Supervised Learning, Git (Version Control System), Performance Metric, Statistical Analysis

    Intermediate · Specialization · 1 - 3 Months

  • C

    Coursera

    Machine Learning Made Easy for Software Engineers

    Skills you'll gain: Model Evaluation, Model Deployment, Data Preprocessing, MLOps (Machine Learning Operations), Data Cleansing, Microservices, Data Pipelines, Feature Engineering, Data Quality, Data Validation, Containerization, Application Deployment, Extract, Transform, Load, Data Transformation, System Monitoring, Debugging, Applied Machine Learning, Machine Learning Methods, Performance Tuning, Machine Learning Algorithms

    Intermediate · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • C

    Coursera

    Hands-on Agentic AI: Building Intelligent Agents

    Skills you'll gain: Model Context Protocol, Responsible AI, LangGraph, AI Orchestration, AI Workflows, LangChain, Agentic systems, System Monitoring, CrewAI, OpenAI API, Generative AI Agents, LLM Application, Tool Calling, Agentic Workflows, Compliance Management, Governance, AI Security, Continuous Monitoring, Artificial Intelligence, Enterprise Application Management

    2.2
    Rating, 2.2 out of 5 stars
    ·
    12 reviews

    Intermediate · Specialization · 3 - 6 Months

  • M

    Microsoft

    Microsoft AI & ML Engineering

    Skills you'll gain: Unsupervised Learning, Model Deployment, Generative AI, Large Language Modeling, Data Management, Natural Language Processing, MLOps (Machine Learning Operations), Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Infrastructure Architecture, LLM Application, Responsible AI, Generative AI Agents, Applied Machine Learning, Azure DevOps, Reinforcement Learning, Data Preprocessing

    4.6
    Rating, 4.6 out of 5 stars
    ·
    352 reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • K

    KodeKloud

    ML Model Development and Tracking: Hands-on Guide

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Test Data, Model Evaluation, Data Synthesis, Development Environment, Claims Processing, Performance Tuning, Applied Machine Learning, Computer Hardware

    Beginner · Course · 1 - 4 Weeks

  • C

    Coursera

    Develop Production-Ready ML APIs with MLOps

    Skills you'll gain: MLOps (Machine Learning Operations), API Design, CI/CD, Software Quality Assurance, Code Review

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Debug ML Code: Fix, Trace & Evaluate

    Skills you'll gain: Regression Testing, Debugging, Unit Testing, Test Case, Code Review, Root Cause Analysis

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Automate and Evaluate ML Pipeline Tests

    Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Regression Testing, Unit Testing, Test Case, System Testing, Test Automation, Software Testing, Integration Testing, Test Planning, Verification And Validation, Anomaly Detection, Continuous Monitoring

    Intermediate · Course · 1 - 4 Weeks

1234…477

In summary, here are 10 of our most popular hands-on+ml+model+development courses

  • AI Model Development & Deployment: Coursera
  • Hands-On MLOps Fundamentals for ML Engineers: KodeKloud
  • AI Agents and MLOps for Production-Ready AI: Packt
  • ML Production Systems: Coursera
  • ML Model Training & Validation: Coursera
  • Machine Learning Made Easy for Software Engineers: Coursera
  • Hands-on Agentic AI: Building Intelligent Agents: Coursera
  • Microsoft AI & ML Engineering: Microsoft
  • ML Model Development and Tracking: Hands-on Guide: KodeKloud
  • Develop Production-Ready ML APIs with MLOps: Coursera

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