Code: MS_DP-100 Cloud MICROSOFT Difficulty: Advanced

Azure Data Scientist Associate

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Price without VAT 940,00 €

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Goals

Gain the necessary knowledge about how to use Azure services to develop, train, and deploy, machine learning solutions. The course starts with an overview of Azure services that support data science. From there, it focuses on using Azure's premier data science service, Azure Machine Learning service, to automate the data science pipeline. This course is focused on Azure and does not teach the student how to do data science. It is assumed students already know that.

Duration

3 days (8h/day)

Contents

Module 1: Getting Started with Azure Machine Learning

In this module, you will learn how to provision an Azure Machine Learning workspace and use it to manage machine learning assets such as data, compute, model training code, logged metrics, and trained models. You will learn how to use the web-based Azure Machine Learning studio interface as well as the Azure Machine Learning SDK and developer tools like Visual Studio Code and Jupyter Notebooks to work with the assets in your workspace.

Module 2: No-Code Machine Learning

This module introduces the Automated Machine Learning and Designer visual tools, which you can use to train, evaluate, and deploy machine learning models without writing any code.

Module 3: Running Experiments and Training Models

In this module, you will get started with experiments that encapsulate data processing and model training code, and use them to train machine learning models.

Module 4: Working with Data

Data is a fundamental element in any machine learning workload, so in this module, you will learn how to create and manage datastores and datasets in an Azure Machine Learning workspace, and how to use them in model training experiments.

Module 5: Working with Compute

One of the key benefits of the cloud is the ability to leverage compute resources on demand, and use them to scale machine learning processes to an extent that would be infeasible on your own hardware. In this module, you'll learn how to manage experiment environments that ensure consistent runtime consistency for experiments, and how to create and use compute targets for experiment runs.

Module 6: Orchestrating Operations with Pipelines

Now that you understand the basics of running workloads as experiments that leverage data assets and compute resources, it's time to learn how to orchestrate these workloads as pipelines of connected steps. Pipelines are key to implementing an effective Machine Learning Operationalization (ML Ops) solution in Azure, so you'll explore how to define and run them in this module.

Module 7: Deploying and Consuming Models

Models are designed to help decision making through predictions, so they're only useful when deployed and available for an application to consume. In this module learn how to deploy models for real-time inferencing, and for batch inferencing.

Module 8: Training Optimal Models

By this stage of the course, you've learned the end-to-end process for training, deploying, and consuming machine learning models; but how do you ensure your model produces the best predictive outputs for your data? In this module, you'll explore how you can use hyperparameter tuning and automated machine learning to take advantage of cloud-scale compute and find the best model for your data.

Module 9: Responsible Machine Learning

Data scientists have a duty to ensure they analyze data and train machine learning models responsibly; respecting individual privacy, mitigating bias, and ensuring transparency. This module explores some considerations and techniques for applying responsible machine learning principles.

Module 10: Monitoring Models

After a model has been deployed, it's important to understand how the model is being used in production, and to detect any degradation in its effectiveness due to data drift. This module describes techniques for monitoring models and their data.

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Training rooms

ALEF operates with training rooms match submarine's style to unexpected, unusual while still being smart and available to work in. We have several type of rooms for small groups and up to larger rooms with modern technical equipment and supportive technologies we provide.

We also deliver the high-quality multimedia sharing for efficient, effective virtual communication on a global scale. In the Competence Center is also available Spark Board. Cisco Sparkboard integrates the most common tools needed for team collaboration in physical meeting rooms into a single elegant device. It also combines white board, video or audio conference features.

All ALEF training centres operates with testing centre that provides full acess to take an exam and get certificate provided by our vendors. ALEF provides to our customer complete management and administration.

Training rooms – Bratislava

Team of lecturers

Our team - consisting of more than 50 instructors - offers a full range of technological knowledge in the field of routing, switching, security, collaboration and data centers. The expertise of instructors is evidenced by a range of top-level international certifications.

The uniqueness of our lecturers lies mainly in their extensive experience in connection with each project, allowing them to respond very flexibly to any question or suggestion from students, and to pass on their practical knowledge to the participants of these courses. Thanks to the synergy of the company’s reliable operation and many years of experience, we have been very flexible in responding to the changes prepared in the Cisco field, so we can guarantee you a wide range of certified courses that enable you and your colleagues to acquire the necessary know-how for future certification tests.

In addition to the certified trainings, we offer special courses that are focused primarily on the development of the necessary configuration skills.

OUR KNOWLEDGE IS YOUR FUTURE

200 +

Courses

20+

Training rooms

10000+

Certificates

50+

Certified lecturers

7

Countries

Cisco Learning Partner Comptia F5 AWS Microsoft vmware palo alto

CONTACT

ALEF Distribution SK, s.r.o.
Galvaniho Business Centrum IV
Galvaniho 17/C
821 04 Bratislava 2
Slovenská republika
+421 (2) 4920 3819
sk-training@alef.com