MestoNovi Sad, Bulevar oslobođenja 78
Cena57.600,00 + PDV

Benefiti

  • 30 dana pristupa snimljenim video materijalima sa kursa (kada se kurs održava online)
  • 180 dana pristupa zvaničnim labovima
  • Svi Microsoft kursevi se rade sa MCT-jem (Microsoft Certified Trainer)
  • Microsoft digitalna značka po završetku kursa

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    At a glance

    Designing and Implementing a Data Science Solution on Azure – DP-100

    • Level: Intermediate

    • Product: Azure

    • Role: Data Scientist

    • Language: Serbian (English)

    • Duration: 4 days

    • Certification: Microsoft Certified: Azure Data Scientist Associate (Exam DP‑100)

    Overview

    Designing and Implementing a Data Science Solution on Azure training helps you learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you how to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, as well as monitoring of machine learning solutions using Azure Machine Learning and MLflow.

    Audience Profile

    This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.

    Course Syllabus

    • Design a data ingestion strategy for machine learning projects

    • Design a machine learning model training solution

    • Design a model deployment solution (real‑time & batch)

    • Design a machine learning operations (MLOps) solution

    • Explore Azure Machine Learning workspace resources and assets

    • Explore developer tools: Azure ML Studio, Python SDK, Azure CLI

    • Make data available in Azure Machine Learning (datastores & datasets)

    • Work with compute targets: instances & clusters

    • Work with environments: curated and custom

    • Find the best classification model with Automated Machine Learning (AutoML)

    • Track model training in Jupyter notebooks with MLflow

    • Run a training script as a command job in Azure ML

    • Track model training with MLflow in jobs

    • Perform hyperparameter tuning using sweep jobs

    • Run pipelines in Azure Machine Learning

    • Register an MLflow model in Azure Machine Learning

    • Create and explore the Responsible AI dashboard

    • Deploy a model to a managed online endpoint

    • Deploy a model to a batch endpoint

    Training Format:

    • Instructor-led
    • Online via Microsoft Teams
    • Language: Serbian / English (as preferred)
    • Includes access to course materials and practice labs

    Skills you’ll gain

    • Manage data ingestion and preparation strategies
    • Train and register ML models
    • Design and deploy models to real-time and batch endpoints
    • Build and automate MLOps pipelines
    • Track experiments and implement responsible AI practices
    • Monitor deployed models and retrain as necessary

    This training prepare you for official Microsoft Exam DP-100 Designing and implementing a data science solution on Azure.

    More information regarding certification you can find here.

    You can find all upcoming Microsoft courses listed here.