Machine Learning Using Microsoft Azure Studio Training

Cybersecurity Training
  • Online (Microsoft Teams)
  • +971 562069465
  • Microsoft Azure Machine Learning Studio is a cloud-based integrated development environment (IDE) for building, training, and deploying machine-learning models on Microsoft Azure. This course typically involves learning how to use Azure Machine Learning Studio to develop and deploy machine learning solutions. The training may cover various aspects of the machine learning lifecycle, including data preparation, model development, training, evaluation, and deployment.

    It's important to note that Microsoft Azure provides a variety of tools and services for machine learning, and Azure Machine Learning Studio is just one of them. The training might also cover other Azure machine learning services, such as Azure Machine Learning Service and Azure Machine Learning Compute. 

  • By the end of this course, participants should be able to:

    • Understand the fundamentals of Azure Machine Learning, its key components, and its role in the machine learning lifecycle.
    • Navigate and use the Azure Machine Learning Studio interface effectively.
    • Learn techniques for importing, cleaning, and exploring datasets within Azure Machine Learning Studio.
    • Explore the process of selecting and building machine learning models using Azure Machine Learning Studio's drag-and-drop interface.
    • Understand how to use Azure Machine Learning Studio to train machine learning models on various types of data.
    • Learn how to evaluate the performance of machine learning models using metrics and visualizations within the Azure Machine Learning Studio environment.
    • Understand the importance of feature engineering and learn techniques for feature transformation and selection.
    • Learn the process of deploying machine learning models as web services or APIs using Azure Machine Learning Studio.
    • Understand how to monitor and manage deployed models, including versioning, logging, and troubleshooting.
  • Training will be conducted via Microsoft Team Meeting. Meeting invites will be shared on the day before the first day of training.

    • 3 days (18 hours)
    • Presentation Slides
    • Training Recordings
    • Study References
  • Upon successful completion of training, participants will receive a certificate.

  • This course is appropriate for a wide range of professionals but not limited to:

    • Individuals interested in starting a career in RPA.
    • Business analysts and professionals looking to automate routine tasks.
    • IT professionals seeking to enhance their automation skills.
    • Developers and programmers interested in RPA.
    • Familiarity with fundamental machine learning concepts, including supervised and unsupervised learning, classification, regression, and clustering.
    • Basic proficiency in a programming language such as Python or R, as many machine learning tasks involve coding.
    • A foundational understanding of statistics and mathematics, particularly concepts related to probability, linear algebra, and calculus.
    • Familiarity with data analysis techniques and tools, as participants may be working with datasets and performing exploratory data analysis.
    • Basic familiarity with Microsoft Azure fundamentals, including an understanding of Azure services and how they are used in a cloud computing environment.
    • Understanding of data preprocessing tasks such as cleaning, transformation, and feature engineering.
    • Strong problem-solving skills and an analytical mindset are essential for effectively applying machine learning techniques to real-world scenarios.
  • Participants can avail a discount of either an early bird or group discount whichever is higher with an additional discount when signing up for 2 or more courses.

    Group Discount (same company only)

    • 15% Discount for groups of 5 or more
    • 10% Discount for groups of 3-4

    Bundle Discount

    • Sign up for 2 courses and get an extra 10% off
    • Sign up for 3 courses and get an extra 15% off
how can we help you?

Contact us at the Velosi office nearest to you or submit a business inquiry online.

Fees + VAT as applicable

Tax Registration Number: 100442245500003

(including coffee breaks and a buffet lunch daily)

Course Outline

  • Module 1: Introduction to Azure Machine Learning

    • Overview of Azure Machine Learning
    • Understanding the Azure Machine Learning Studio interface
    • Setting up an Azure Machine Learning workspace
  • Module 2: Data Preparation and Exploration

    • Importing and exploring datasets in Azure Machine Learning Studio
    • Data cleaning and transformation techniques
    • Feature engineering and selection
  • Module 3: Model Development in Azure Machine Learning Studio

    • Choosing and configuring machine learning algorithms
    • Building machine learning models using the drag-and-drop interface
  • Module 4: Model Training and Evaluation

    • Training machine learning models with Azure Machine Learning Studio
    • Evaluating model performance using metrics and visualizations
  • Module 5: Hyperparameter Tuning

    • Optimizing model performance through hyperparameter tuning
    • Using Azure Machine Learning Studio for automated hyperparameter tuning
  • Module 6: Model Deployment

    • Deploying machine learning models as web services or APIs
    • Managing and versioning deployed models
  • Module 7: Monitoring and Management

    • Monitoring the performance of deployed models
    • Logging and troubleshooting model deployments
  • Module 8: Real-world Applications

    • Applying machine learning concepts to real-world scenarios
    • Case studies and practical implementation examples