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DP-100T01: Designing and Implementing a Data Science Solution on Azure Training & Certification Course

The DP-100T01: Designing and Implementing a Data Science Solution on Azure course equips data scientists with proven methods to operationalize machine learning at scale on Microsoft Azure, solving the critical industry challenge of transitioning models from experimentation to production.

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🎓 980 Learners
⏱️ 32 Hours (4 Days)
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Course Overview

The DP-100T01: Designing and Implementing a Data Science Solution on Azure by Microsoft is a comprehensive course tailored for data scientists, AI engineers, and machine learning practitioners aiming to validate their expertise through the DP-100 certification. This course equips learners with the skills to design and run machine learning workloads on Azure, focusing on core responsibilities such as creating data science environments, training models, and managing scalable solutions. With Microsoft Azure commanding over 25% of the cloud AI services market, professionals certified in DP-100 are in high demand across industries leveraging cloud-based machine learning.

Students engage with key Microsoft technologies including Azure Machine Learning, Azure AI Foundry, MLflow, and Azure AI services such as Azure AI Search. Through hands-on labs in the Azure Portal, learners configure compute targets, create and manage workspaces, and build automated machine learning pipelines. A central project involves training, registering, and deploying an MLflow model to a managed online endpoint, simulating real-world deployment scenarios. These labs emphasize practical implementation of responsible AI principles, hyperparameter tuning, and Retrieval Augmented Generation (RAG) workflows within a fully integrated cloud environment.

This training prepares candidates for the Microsoft Azure Data Scientist Associate (DP-100) certification, a credential recognized globally for its rigor and alignment with industry standards. Certified professionals command an average starting salary of $125,000, reflecting the high value placed on cloud data science skills. Optiv Solutions enhances this learning path with Guaranteed-to-Run batches and official Microsoft courseware, ensuring structured, instructor-led mastery. Completing the DP-100T01 course empowers data science professionals to lead AI initiatives and advance into senior roles in cloud machine learning and generative AI development.

Skills You’ll Develop

✦ Azure Machine Learning ✦ MLflow Model Tracking ✦ Azure AI Foundry ✦ RAG Implementation ✦ Hyperparameter Tuning ✦ Prompt Engineering ✦ Model Deployment ✦ Automated Machine Learning ✦ Fine-tuning Language Models ✦ Azure AI Search ✦ Managed Online Endpoints ✦ Responsible AI ✦ Prompt Flow Development ✦ Vector Store Configuration ✦ Model Registry ✦ Data Grounding ✦ Generative AI Evaluation

Who Should Attend

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WHO SHOULD ATTEND (TARGET AUDIENCE)

• 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

Pre-requisites

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RECOMMENDED KNOWLEDGE BEFORE TAKING THIS COURSE

  • ✓ Basic understanding of Microsoft Azure cloud services and architecture
  • ✓ Experience deploying and managing cloud resources within Microsoft Azure
  • ✓ Proficiency in Python programming for data analysis and visualization with libraries like Pandas, Numpy, and Matplotlib
  • ✓ Practical experience training and validating machine learning models using frameworks such as Scikit-Learn, PyTorch, or TensorFlow
  • ✓ Knowledge of container technologies and their application in Azure environments
  • ✓ Completion of AI-900T00: Introduction to AI in Azure or comparable foundational AI expertise

Certification Exam Details

Everything you need to know about the certification exam

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Exam Details

EXAM CODE DP-100T01
EXAM NAME Designing and Implementing a Data Science Solution on Azure
FORMAT Multiple Choice Questions (MCQs) and Case Study-based Questions
QUESTIONS 40-60 questions
DURATION 180 minutes
PASSING SCORE 700 (out of 1000)

Upcoming Batch Schedule

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Curriculum & Course Syllabus

Module 1: Explore and configure the Azure Machine Learning workspace
  • Explore Azure Machine Learning workspace resources and assets
  • Explore developer tools for workspace interaction
  • Make data available in Azure Machine Learning
  • Work with compute targets in Azure Machine Learning
  • Work with environments in Azure Machine Learning
Module 2: Experiment with Azure Machine Learning
  • Find the best classification model with Automated Machine Learning
  • Track model training in Jupyter notebooks with MLflow
Module 3: Optimize model training with Azure Machine Learning
  • Run a training script as a command job in Azure Machine Learning
  • Track model training with MLflow in jobs
  • Perform hyperparameter tuning with Azure Machine Learning
  • Run pipelines in Azure Machine Learning
Module 4: Manage and review models in Azure Machine Learning
  • Register an MLflow model in Azure Machine Learning
  • Create and explore the Responsible AI dashboard for a model in Azure Machine Learning
Module 5: Deploy and consume models with Azure Machine Learning
  • Deploy a model to a managed online endpoint
  • Deploy a model to a batch endpoint
Module 6: Develop generative AI apps in Azure AI Foundry portal
  • Introduction to Azure AI Foundry
  • Explore and deploy models from the model catalog in Azure AI Foundry portal
  • Get started with prompt flow to develop language model apps in the Azure AI Foundry
  • Build a RAG-based agent with your own data using Azure AI Foundry
  • Fine-tune a language model with Azure AI Foundry
  • Evaluate the performance of generative AI apps with Azure AI Foundry

Student Reviews & Testimonials

Real feedback from certified professionals and corporate teams

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Frequently Asked Questions

What will I learn in the DP-100T01: Designing and Implementing a Data Science Solution on Azure training?

The DP-100T01 course teaches Azure Machine Learning service creation, model training/deployment, real-time data processing, and offers hands-on labs to build predictive solutions, benefiting learners with practical data science skills.

What are the prerequisites for enrolling in the DP-100T01: Designing and Implementing a Data Science Solution on Azure course?

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.

Will I receive a certificate after completing the DP-100T01: Designing and Implementing a Data Science Solution on Azure course?

Yes, you will receive a Certificate of Training Completion from Optiv Solutions.

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