Course Details | Cloudthat

Course Overview

The Microsoft DP-100 BootCamp course from CloudThat is designed to train candidates who plan to take up the Microsoft DP-100 certification exam. Taking this course and passing the Microsoft DP-100 exam will meet all the requirements needed to become a Microsoft Certified Azure Data Scientist Associate.

After completing this course, students will be able to:

  • To understand and build AI solutions on Azure
  • To learn about various Azure Machine Learning services usage & integration
  • To understand the profound impacts Machine Learning is making in smart business decisions

Upcoming Batches

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Key Features

  • Our training modules have 50% -60% hands-on lab sessions to encourage Thinking-Based Learning (TBL)
  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL)
  • Microsoft certified instructor-led training and mentoring sessions to develop Competency-Based Learning (CBL)
  • Well-structured use-cases to simulate challenges encountered in a Real-World environment
  • Integrated teaching assistance and support through experts designed Learning Management System (LMS) and ExamReady platform
  • Being a Microsoft Learning Partner provides us with the edge over competition

Who Should Attend

  • Candidates serving as part of a multi-disciplinary team that incorporates ethical, privacy, and governance considerations into the solution.

Prerequisites

  • Candidates typically have background in mathematics, statistics and computer science
  • Basic knowledge of Cloud platform: Azure
  • Basic understanding of Machine Learning
  • IT industry work experience or those pursuing a degree in the IT field
  • Strong learning acumen

Course Outline Download Course Outline

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.

Lessons :

  • Getting Started with Azure Machine Learning
  • Azure Machine Learning Tools

Hands-On:

  • Creating an Azure Machine Learning Workspace
  • Working with Azure Machine Learning Tools

This module introduces the Designer tool, a drag and drop interface for creating machine learning models without writing any code. You will learn how to create a training pipeline that encapsulates data preparation and model training, and then convert that training pipeline to an inference pipeline that can be used to predict values from new data, before finally deploying the inference pipeline as a service for client applications to consume.

Lessons:

  • Training Models with Designer
  • Publishing Models with Designer

Hands-On:

  • Creating a Training Pipeline with the Azure ML Designer
  • Deploying a Service with the Azure ML Designer

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.

Lessons:

  • Introduction to Experiments
  • Training and Registering Models

Hands-On:

  • Running Experiments
  • Training and Registering Models

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.

Lessons:

  • Working with Datastores
  • Working with Datasets

Hands-On:

  • Working with Datastores
  • Working with Datasets

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.

Lessons:

  • Working with Environments
  • Working with Compute Targets

Hands-On:

  • Working with Environments
  • Working with Compute Targets

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.

Lessons:

  • Introduction to Pipelines
  • Publishing and Running Pipelines

Hands-On:

  • Creating a Pipeline
  • Publishing a Pipeline

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.

Lessons:

  • Real-time Inferencing
  • Batch Inferencing

Hands-On:

  • Creating a Real-time Inferencing Service
  • Creating a Batch Inferencing Service

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.

Lessons:

  • Hyperparameter Tuning
  • Automated Machine Learning

Hands-On:

  • Tuning Hyperparameters
  • Using Automated Machine Learning

Many of the decisions made by organizations and automated systems today are based on predictions made by machine learning models. It’s increasingly important to be able to understand the factors that influence the predictions made by a model, and to be able to determine any unintended biases in the model’s behavior. This module describes how you can interpret models to explain how feature importance determines their predictions.

Lessons:

  • Introduction to Model Interpretation
  • using Model Explainers

Hands-On:

  • Reviewing Automated Machine Learning Explanations
  • Interpreting 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.

Lessons:

  • Monitoring Models with Application Insights
  • Monitoring Data Drift

Hands-On:

  • Monitoring a Model with Application Insights
  • Monitoring Data Drift

Certification

  • By earning DP-100 certification, you can be competent data scientist
  • Display abilities to understand the profound impacts Machine Learning is making in smart business decisions
  • On successful completion of DP-100: Design & Implement Data Science Solution on Azure training aspirants receive a Course Completion Certificate from us
  • By successfully clearing the DP-100 exams, aspirants earn Microsoft Certification

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Our Top Trainers

Pavan Bhawsar

Pavan is a Microsoft Certified Trainer at CloudThat. He is an enthusiastic and passionate trainer, empathic observer towards the trending technologies with demonstrated skill in Azure and hybrid Cloud Administration. He has 6+ years of corporate experience, etc.

Yanish Sahu

Yanish works as a Corporate Trainer with CloudThat Technologies. He is very passionate about learning new technologies. He is part of CloudThat’ s Microsoft team which helps to deploy Microsoft 365 setup. He is skilled on topics etc.

Sohini Rakshit

Sohini serves as a trainer for Azure cloud at CloudThat Technologies. She is an experienced Cloud Consultant and Architect, Corporate trainer working on Microsoft Azure around multi-tier distributed application design planning and deployment for several Cloud Solutions. She holds a etc.

Lakhan Kriplani

He had involved in various client projects to set up infrastructure on Cloud for various Analytics applications, E-Commerce, setup CICD Pipeline using AWS services. He has experience in developing highly secure, scalable web applications using MVC architecture. etc.

Jagadesh Gonnagar

He has been a part of several large and complex software development projects with global clients. He has worked in USA for over 11 years before relocating to India. He has expertise in Database design/development, Web development, etc.

Devi Vara Prasad

A Microsoft Certified Trainer with more than 15+ years of Corporate, Online and Classroom Training Experience, well versed in AWS an Azure Cloud platforms and have been delivering trainings for more than 5years. Also has a vast etc.

Anjali Srivastava

Anjali serves as a Research Associate for IoT (including AI/ML) and Azure cloud at CloudThat technologies. She is an experienced Solutions Engineer & Developer, corporate trainer working on Microsoft Azure around multi-tier distributed application design planning and deployment for several etc.

Ajay Kumar Lodha

Ajay is cloud obsessed and cloud addict, that's how he describes himself. Ajay has been working with all the major cloud computing platforms like AWS, Azure, and GCP for more than 5 years now. He is into etc.

Prarthit Mehta

Prarthit has been involved in various large and complex projects with global clients. He has experience in Microsoft, MS office 365 & AWS Infrastructure technologies and Windows servers, designing Active Directory and managing various domain services. He etc.

Priyant Gupta

Priyant is working in the Microsoft Technology space for last 5 years and is sharing the knowledge gained on Azure Administration, Azure Data Engineering and Dynamics 365 CE Apps. He has trained 1000+ professionals as a corporate trainer at etc.

Course Fee

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Reviews

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Srinidhi Gowda

Great set up for certification training.

Frequently Asked Questions

CloudThat’s Azure training course for the preparation of DP-100 certification exam can be taken up by: Candidates serving as part of a multi-disciplinary team that incorporates ethical, privacy, and governance considerations into the solution.

Candidates appearing for the DP-100 exam will get 180 minutes to complete the Microsoft Azure Data Scientist Associate certification exam.

Candidates need to answer between 45-60 questions. However, the number of questions may change as and when changes in technology and job roles occur.

The cost of the Microsoft Azure Fundamentals certification exam is ₹4800 in Bangalore and other Indian cities.
The exam cost is mostly priced according to the currency values in specific regions and countries. However, the exam prices are subject to change and may also vary depending on the additional taxes that may apply in some countries and regions.

Candidates need to score 700 (on a scale of 1-1000) approx. to pass the Microsoft AZ-900 exam.

• Candidates must wait for 24 hours to retake the DP-100 exam on failing in his/her first attempt. Also, candidates can log in to their certification dashboard to reschedule the exam.
• The candidate must wait for at least 14 days to retake the exam for the third time on failing in their second attempt. The waiting period is the same while retaking the exam for the fourth and fifth times.
• In a year, a candidate is allowed a maximum of 5 retakes. (One year is calculated from the day of the fifth unsuccessful exam attempt.)

After completing CloudThat’s highly interactive DP-100 exam training in Bangalore or other cities, you will be able to:
• Set up an Azure Machine Learning workspace
• Run experiments and train models
• Optimize and manage models
• Deploy and consume models

CloudThat, a Microsoft Gold Partner and the winner of Microsoft Learning Partner 2020 of the Year Finalist award, is undoubtedly the best Azure training provider in Bangalore and other cities in India. CloudThat has trained over 350K+ IT professionals from fortune 500 companies in Cloud since 2012. From personalized mentoring to self-paced learning modules, we work towards providing a growth-oriented learning experience to nurture their future.
• CloudThat’s training modules are equipped with 50%-60% hands-on lab sessions.
• Highly interactive virtual and classroom teaching.
• Qualified instructor-led training and mentoring sessions.
• Practice lab and projects aligned to Azure learning modules.
• Integrated teaching assistance and support.

To prepare for the DP-100 certification and pass the exam successfully, candidates need to enroll in CloudThat’s DP-100 certification training course in Bangalore. Our subject matter experts and certified Azure trainers offer training through online or instructor-led classes and provide relevant study material necessary to support your exam preparation. At CloudThat, you can strengthen your practical Azure skills through hands-on lab sessions and test your knowledge before the final exam through our testprep platform. Besides our training and assistance, candidates can also:
• Join online forum discussions and study groups to enrich your knowledge.
• Have a detailed understanding of the exam structure.
• Study Microsoft documentation along with relevant whitepapers and eBooks.

The different types of DP-100 exam questions that may appear in the real exam include:
• Multiple-choice questions
• Drag and drop
• Reordering
• Short answers