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11 Jan 2025 | 24 | 06:00 PM - 09:00 PM | Sat, Sun | |
12 Jan 2025 | 24 | 06:00 PM - 09:00 PM | Sat, Sun | |
18 Jan 2025 | 24 | 06:00 PM - 09:00 PM | Sat, Sun | |
19 Jan 2025 | 24 | 06:00 PM - 09:00 PM | Sat, Sun |
Course Price At
Online Self Learning Courses are designed for self-directed training, allowing participants to begin at their convenience with structured training and review exercises to reinforce learning. You’ll learn through videos, PPTs and complete assignments, projects and other activities designed to enhance learning outcomes, all at times that are most convenient to you.
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DP-100 Designing and Implementing a Data Science Solution on Azure Training Certification Course offered by Multisoft Virtual Academy teaches participants how to use Azure services to develop machine learning solutions; perform data science activities on Azure; gain understanding of automate machine learning with Azure machine learning and learn how to manage and monitor machine learning models with Azure machine learning. Dividing in 4 modules, this course covers topics such as setting up an Azure Machine Learning workspace; running experiments and train models and optimizing and managing models.
Taught by Multisoft’s global subject matter experts, this course has been 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; Azure Data Scientists; Data Engineers; Azure Software Engineers; Machine Learning Engineers and Data & Applied Scientists. DP-100 Designing and Implementing a Data Science Solution on Azure Training Certification Course comes with perks like lifetime e-learning access, recorded training session videos and after-training support. This course is delivered in live instructor-led one-on-one and corporate sessions. Once the candidate has successfully completed the program, he/she will be awarded with a globally recognized training certificate.
Responsibilities of an Azure data scientist include designing and creating a suitable working environment for data science workloads; exploring data; training machine learning models; implementing pipelines; running jobs to prepare for production; and managing, deploying, and monitoring scalable machine learning solutions.
Data scientists and AI developers use the Azure Machine Learning SDK for Python to build and run machine learning workflows with the Azure Machine Learning service. You can interact with the service in any Python environment, including Jupyter Notebooks, Visual Studio Code, or your favorite Python IDE.
Azure Machine Learning is a cloud service for accelerating and managing the machine learning project lifecycle. Machine learning professionals, data scientists, and engineers can use it in their day-to-day workflows: Train and deploy models, and manage MLOps.
The Azure Databricks Lakehouse Platform provides a unified set of tools for building, deploying, sharing, and maintaining enterprise-grade data solutions at scale. Azure Databricks integrates with cloud storage and security in your cloud account, and manages and deploys cloud infrastructure on your behalf.