DP-100T01: Designing and Implementing a Data Science Solution on Azure Course Overview

DP-100T01: Designing and Implementing a Data Science Solution on Azure Course Overview

The DP-100T01: Designing and Implementing a Data Science Solution on Azure course provides an in-depth exploration of Azure's machine learning capabilities. It covers the entire data science process from data preparation, model training, model deployment, and model management. Learners will gain practical experience with Azure Machine Learning Service and Azure Machine Learning Studio, learning how to create, train, optimize, and deploy machine learning models at scale.

Throughout the course, participants will engage in hands-on labs, such as creating an Azure Machine Learning workspace, running experiments, working with datastores and datasets, and orchestrating machine learning workflows with pipelines. They will also explore real-time and batch inferencing, ensuring their models can respond promptly or handle large-scale processing.

By mastering hyperparameter tuning, automated machine learning, and model interpretation, students will be well-equipped to build responsible AI solutions. They'll also delve into the best practices for monitoring models to maintain optimal performance over time, using tools like Application Insights and data drift monitoring. This course is ideal for aspiring and existing data scientists looking to harness the power of Azure to streamline and enhance their machine learning workflows.

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  • Live Online Training (Duration : 32 Hours)
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Course Prerequisites

To ensure a successful learning experience in the DP-100T01: Designing and Implementing a Data Science Solution on Azure course, participants should have the following minimum prerequisites:


  • Basic understanding of data science and machine learning concepts.
  • Familiarity with common data science processes such as data exploration, data cleaning, feature engineering, model training, and evaluation.
  • Experience with Python programming, as Python is frequently used for data manipulation and model training within Azure Machine Learning.
  • Exposure to basic statistics, as they form the foundation of many machine learning algorithms.
  • Knowledge of cloud computing fundamentals, particularly within the Microsoft Azure ecosystem.
  • Prior experience using Azure services is beneficial but not mandatory.

These prerequisites are designed to provide a baseline for course participants, ensuring that they can actively engage with the course material and practical labs.


Target Audience for DP-100T01: Designing and Implementing a Data Science Solution on Azure

The DP-100T01 course is designed for professionals seeking to implement data science solutions on Azure's cloud platform.


  • Data Scientists
  • AI Engineers
  • Machine Learning Engineers
  • Cloud Solutions Architects
  • IT Professionals with a focus on data analytics
  • Software Developers interested in data science and machine learning
  • Technical Leads managing data science teams
  • Data Analysts aiming to advance in machine learning
  • DevOps Engineers focused on ML/AI lifecycle management
  • Professionals preparing for Azure Data Scientist Associate certification


Learning Objectives - What you will Learn in this DP-100T01: Designing and Implementing a Data Science Solution on Azure?

Introduction to the Course's Learning Outcomes and Concepts Covered:

The DP-100T01: Designing and Implementing a Data Science Solution on Azure course provides a comprehensive understanding of how to leverage Azure Machine Learning for building, training, and deploying predictive models.

Learning Objectives and Outcomes:

  • Create and Configure an Azure Machine Learning Workspace: Understand how to set up and manage the workspace, including assets and tools for machine learning projects.
  • Utilize Azure Machine Learning Tools: Learn to use both the Azure Machine Learning Studio and the Python SDK for machine learning tasks.
  • Run Automated Machine Learning Experiments: Discover how to use Automated ML to quickly identify high-performing models.
  • Build and Publish Models Using Designer: Explore the no-code Designer interface to train and deploy models without writing code.
  • Execute and Track Machine Learning Experiments: Learn to run experiments, track metrics, and register models within Azure Machine Learning.
  • Optimize Model Training with Hyperparameter Tuning: Utilize Azure Machine Learning's capabilities to fine-tune model performance.
  • Deploy Models for Real-time and Batch Inferencing: Master the deployment process for both real-time and batch predictions in Azure.
  • Create and Manage End-to-End Machine Learning Pipelines: Learn to orchestrate machine learning workflows with pipelines for reproducibility and scalability.
  • Interpret and Explain Models for Accountability: Gain insights into model behavior and ensure responsible AI with interpretability and fairness tools.
  • Monitor Models and Data Drift in Production: Implement monitoring for model performance and data drift to maintain and improve model reliability over time.

FAQ's


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1-on-1 Private - Select your start date. You will be the only student in the class.
Yes, course requiring practical include hands-on labs.
It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes.You can access courseware for most vendors.
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You will receive the letter of course attendance post training completion via learning enhancement tool after registration.
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Buy-Now. Pay-Later option is available using credit card in USA and India only.
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You can request a refund if you do not wish to enroll in the course.
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The Fee includes:
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  • Remote Labs
Yes, Koenig Solutions is a Microsoft AI Cloud Partner having delivery capability across all titles.
Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1 on 1 Public you can select your own schedule, other students can be merged. Choose 1-on-1 if published schedule doesn't meet your requirement. If you want a private session, opt for 1-on-1 Private.
Duration of Ultra-Fast Track is 50% of the duration of the Standard Track. Yes(course content is same).
  • AI-102T00: Designing and Implementing a Microsoft Azure AI Solution
You can enroll for this Designing and Implementing a Data Solution on Azure DP-100 by:
  • Selecting a convenient schedule from the dates given
  • Enroll for Designing and Implementing a Data Solution on Azure DP-100 course by making the payment
  • Get pre-reading materials from Koenig Solutions and start your preparation
 
Participants who enroll for Designing and Implementing a Data Solution on Azure DP-100 certification training will get:
  • A copy of the course material
  • Microsoft Azure DP-100 Sample Papers
  • Access to Microsoft Azure Labs
  • A course completion certificate from a Microsoft Gold Partner
 
There are no reference materials for Designing and Implementing a Data Solution on Azure DP-100 course, but you can visit the official Designing and Implementing a Data Solution on Azure DP-100 page to understand: 
  • What is this the Designing and Implementing a Data Solution on Azure DP-100 course is all about
  • When was the Designing and Implementing a Data Solution on Azure DP-100 course was last updated
  • Skills Measured for Microsoft Azure DP-100 certification exam
  • Self-paced Microsoft Learn video modules
  • DP-100 certification exam resources, and more
 
This Designing and Implementing a Data Solution on Azure DP-100 course is ideal for data scientists, machine learning professionals, professionals who create data solutions on Microsoft Azure, and for individuals who are looking to clear their DP-100 certification exam.
Yes, Koenig Solutions is a Microsoft Gold Partner to deliver Designing and Implementing a Data Solution on Azure DP-100 Certification Course worldwide.
You can take up this Designing and Implementing a Data Solution on Azure DP-100 certification training course in multiple delivery modes that include:
  • Instructor-led classroom training
  • Instructor-led Live online training
  • 1-on-1 training
  • Fly-me-a-Trainer
  • Corporate/on-site training
 
The cost of Designing and Implementing a Data Solution on Azure DP-100 certification exam is USD 165. And this cost depends on the country in which the exam is proctored in.
No, the course fee does not include the Designing and Implementing a Data Solution on Azure DP-100 examination fee. By taking up the DP-100 training, you are only paying for the training and not for the exam. The certification exam cost for Microsoft Azure DP-100 is USD 165 and has to be taken from Pearson Vue.
Upon clearing your Microsoft DP-100 examination, your Microsoft Certified: Azure Data Scientist Associate certification will be valid for two years. After the validity period of two years, your certification will not be current anymore, but it will still be showcased under a different section with the Exam code and year mentioned along with it.
For more information on Designing and Implementing a Data Solution on Azure DP-100 course, you can mail us at info@koenig-solutions.com, call us at +91 80950 73333 (24x7) and chat with us to get your queries resolved immediately.

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All our trainers are fluent in English . Majority of our customers are from outside India and our trainers speak in a neutral accent which is easily understandable by students from all nationalities. Our money back guarantee also stands for accent of the trainer.
Yes, if you send 4 participants, we can offer an exclusive training for them which can be started from Any Date™ suitable for you.
Medical services in India are at par with the world and are a fraction of costs in Europe and USA. A number of our students have scheduled cosmetic, dental and ocular procedures during their stay in India. We can provide advice about this, on request.
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“It is an interesting story and dates back half a century. My father started a manufacturing business in India in the 1960's for import substitute electromechanical components such as microswitches. German and Japanese goods were held in high esteem so he named his company Essen Deinki (Essen is a well known industrial town in Germany and Deinki is Japanese for electric company). His products were very good quality and the fact that they sounded German and Japanese also helped. He did quite well. In 1970s he branched out into electronic products and again looked for a German name. This time he chose Koenig, and Koenig Electronics was born. In 1990s after graduating from college I was looking for a name for my company and Koenig Solutions sounded just right. Initially we had marketed under the brand of Digital Equipment Corporation but DEC went out of business and we switched to the Koenig name. Koenig is difficult to pronounce and marketeers said it is not a good choice for a B2C brand. But it has proven lucky for us.” – Says Rohit Aggarwal (Founder and CEO - Koenig Solutions)