Azure Machine Learning Training
Catalogue index: IFS/9
product- line 1
Features
Description
Infoshare is the largest tech community in CEE and the organizer of the leading tech conference in Gdańsk. It connects startups, investors, corporations, and innovation enthusiasts. It promotes entrepreneurship, knowledge sharing, and networking. Through events, competitions, and programs, it supports the development of the tech ecosystem in Poland and the region.
The Azure Machine Learning training is an intensive two-day course that focuses on the practical application of tools and services available in Azure for creating, training, and deploying machine learning models. The training program is designed so that 80% of the time is dedicated to practical workshops and 20% to theory. Participants will learn how to leverage the full potential of the Azure Machine Learning platform by working on real-world examples and use cases.
- Programmers and data engineers who want to expand their skills in machine learning on Azure cloud
- IT specialists who want to use Azure Machine Learning for automating data processing and predictions
- Data scientists and data analysts wishing to train and deploy ML models in a production environment
- Individuals with a basic knowledge of programming in Python, foundational knowledge of machine learning, and basic skills in working with Kubernetes.
- Experience with cloud services will be an additional advantage
- How to configure the Azure ML Workspace environment and manage it
- How to deploy ML models on Azure ML Service and monitor their performance
- How to conduct exploratory data analysis and train ML models using Azure ML Designer and AutoML
- How to integrate ML models with other Azure services, such as Databricks and Cognitive Services
Day 1: Introduction to Azure Machine Learning and Basics
Basics of Azure Machine Learning
Introduction to the Azure ecosystem and its ML services
Configuring the Azure ML Workspace environment
Data Preparation and Exploratory Data Analysis (EDA)
Importing and processing data in Azure
Conducting EDA using tools available in Azure
Training Models in Azure
Introduction to Azure ML Designer
Automating model training using Azure AutoML
Training the First Model
Practical exercises in training a model using a real dataset
Analyzing results and evaluating the model
Day 2: Advanced Techniques and Practical Applications
Advanced Techniques for Training Models
Using custom scripts for training models
Using GPU and computing clusters to accelerate training
Deploying and Monitoring Models
Deploying models on Azure ML Service
Monitoring and managing deployed models
Deploying and Optimizing the Model
Practical exercises in deploying the model
Model optimization and hyperparameter tuning
16 h/2 days