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Microsoft Azure Data Scientist (DP-100)
With the DP-100, become an expert in data science! Learn about Azure and get the abilities to create and execute data science solutions. This course is your ticket to unlocking Azure data’s full potential, regardless of your level of experience with data. Prepare yourself for a voyage of wisdom and creativity!
Overview
With the knowledge and abilities required to develop, deploy, and optimize data science solutions, this immersive course immerses you in the world of data science on Azure. Discover the art of integrating data solutions, design and implement machine learning models, and delve into the vast capabilities of Microsoft Azure’s data services. This curriculum meets your needs whether you’re an experienced professional trying to advance your abilities or an enthusiastic data science learner wanting to explore the cloud. Taught by professionals in the field, this course aims to prepare you for success in the data science and Azure fields by fusing theoretical knowledge with real-world experience gained through interactive data projects.
What you will learn in Microsoft Azure Data Scientist (DP-100) course?
• Creation of Azure Machine Learning space and management of data objects
• Execution of training scripts in Azure Machine Learning space
• Automation of model training method
• Utilization of Auto ml for the creation of best models
• Preparation of the model as a service
Who Should Attend Microsoft Azure Data Scientist (DP-100) course?
- Candidates who are interested in Machine Learning and AI.
- IT professionals who have a thorough knowledge of Microsoft Azure and some knowledge of data handling.
- People who are good at statistics.
- Data Scientists who prepare data, train models, and evaluate competing models but have never done this on Azure.
Our Package
Course Curriculm
Module 1: Getting Started With Azure Machine Learning
- Introduction to Azure Machine Learning
- Working with Azure Machine Learning
Module 2: Visual Tools For Machine Learning
- Automated Machine Learning
- Azure Machine Learning Designer
Module 3: Running Experiments and Training Models
- Introduction to Experiments
- Training and Registering Models
Module 4: Working with Data
- Working with Datastores
- Working with Datasets
Module 5: Working with Compute
- Environments
- Compute Targets
Module 6: Orchestrating Machine Learning Workflows
- Introduction to Pipelines
- Publishing and Running Pipelines
Module 7: Deploying and Consuming Models
- Real-time Inferencing
- Batch Inferencing
- Continuous Integration and Delivery
Module 8: Training Optimal Models
- Hyperparameter Tuning
- Automated Machine Learning
Module 9: Responsible Machine Learning
- Differential Privacy
- Model Interpretability
- Fairness
Module 10: Monitoring Models
- Monitoring Models with Application Insights
- Monitoring Data Drift
Upcoming Batch
April 20th (Weekends)
FRI & SAT (4 Weeks)
08:30 PM to 01:00 AM (CDT)
April 18th (Weekdays)
MON – FRI (18 Days)
10:00 AM to 12:00 PM (CDT)
Microsoft Azure Data Scientist (DP-100) FAQs
Q. What is designing and implementing a data science solution on Azure?
Ans.
This course guides you in utilizing your Python and machine learning expertise to effectively handle tasks such as data ingestion, preparation, model training, deployment, and monitoring within the Azure environment. It focuses on leveraging Azure Machine Learning and MLflow for a comprehensive data science solution.
Q. What is the objective of the DP 100 exam?
Ans.
The DP-100 exam, titled “Designing and Implementing a Data Science Solution on Azure,” evaluates your proficiency in various technical tasks. These tasks include designing and preparing a machine learning solution, exploring data and training models, preparing a model for deployment, and deploying and retraining a model.
Q. What is the difficulty level of Azure DP 100?
Ans.
The DP-100 exam is relatively manageable in comparison to other machine learning assessments. Proficiency in creating machine learning models using the pandas and Scikit-learn libraries significantly facilitates success in the exam. Now, let’s delve into the essential topics for the DP-100 exam, starting with exploring and analyzing data using pandas.
Q. What is the passing score for DP 100 certification?
Ans.
A passing score for the exam is set at 700 or above. It’s important to note that this score is scaled, and as such, it may not directly correspond to 70% of the total points. The passing score takes into consideration both the requisite knowledge and skills necessary to demonstrate competence, along with the difficulty level of the questions.
Q. How many questions are there in the DP 100 exam?
Ans.
You will be allotted 120 minutes to respond to 40 to 60 questions in the DP-100 exam. The question formats vary and include multiple-choice questions (both single and multiple answers), sequence reordering, scenario-based questions, and fill-in-the-blank questions requiring code completion.
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