DP - 604T00 : Implement a data science and machine learning solution for AI with Microsoft Fabric
Implement a Data Science and ML solution for AI with Microsoft Fabric (DP-604) Course, a specialized course designed to empower professionals with advanced AI, data science, and ML skills using Microsoft Fabric. Learn to process and analyze data, train predictive models,
Instructor
DP-604T00: Data Science & AI with Microsoft Fabric Training
Curriculum
Master DP-604T00: Implement Data Science & Machine Learning with AI using Microsoft Fabric. Gain hands-on skills & boost your career in AI solutions.
DP - 604T00 : Implement a data science and machine learning solution for AI with Microsoft Fabric
The DP-604T00: Implement a Data Science and Machine Learning Solution for AI with Microsoft Fabric course covers the implementation of data science and machine learning workflows in Microsoft Fabric, with a focus on AI model training and deployment.
Course Objectives:
Get started with data science in Microsoft Fabric
Explore data for data science with notebooks in Microsoft Fabric
Preprocess data with Data Wrangler in Microsoft Fabric
Train and track machine learning models with MLflow in Microsoft Fabric
Generate batch predictions using a deployed model in Microsoft Fabric
Target Audience:
Data Scientists
AI Professionals
Machine Learning Engineers
IT Specialists working with Data Science
Developers implementing AI solutions
Technical Personnel exploring Microsoft Azure
Individuals seeking expertise in Microsoft Azure Machine Learning services
Course Outline:
Get started with data science in Microsoft Fabric
Understand the data science process
Train models with notebooks in Microsoft Fabric
Track model training metrics with MLflow and experiments
Lab: Explore data science in Microsoft Fabric
Explore data for data science with notebooks in Microsoft Fabric
Load data and perform initial data exploration
Gain knowledge about different types of data distributions
Understand the concept of missing data, and strategies to handle missing data effectively
Visualize data using various data visualization techniques and libraries
Lab: Use notebook for data exploration in Microsoft Fabric
Preprocess data with Data Wrangler in Microsoft Fabric
Learn Data Wrangler features, and its role in the data science workflow
Perform different types of preprocessing operations in data science
Learn how to handle missing values, and imputation strategies
Use one-hot encoding and other techniques to convert categorical data into a format suitable for machine learning algorithms
Lab: Preprocess data with Data Wrangler in Microsoft Fabric
Train and track machine learning models with MLflow in Microsoft Fabric
Train machine learning models with open-source frameworks
Train models with notebooks in Microsoft Fabric
Track model training metrics with MLflow and experiments in Microsoft Fabric
Lab: Train and track a model in Microsoft Fabric
Generate batch predictions using a deployed model in Microsoft Fabric
Save a model in the Microsoft Fabric workspace
Prepare a dataset for batch predictions
Apply the model to dataset to generate new predictions
The DP-604T00: Implement a Data Science and Machine Learning Solution for AI with Microsoft Fabric course covers the implementation of data science and machine learning workflows in Microsoft Fabric, with a focus on AI model training and deployment.
Course Objectives:
Get started with data science in Microsoft Fabric
Explore data for data science with notebooks in Microsoft Fabric
Preprocess data with Data Wrangler in Microsoft Fabric
Train and track machine learning models with MLflow in Microsoft Fabric
Generate batch predictions using a deployed model in Microsoft Fabric
Target Audience:
Data Scientists
AI Professionals
Machine Learning Engineers
IT Specialists working with Data Science
Developers implementing AI solutions
Technical Personnel exploring Microsoft Azure
Individuals seeking expertise in Microsoft Azure Machine Learning services
Course Outline:
Get started with data science in Microsoft Fabric
Understand the data science process
Train models with notebooks in Microsoft Fabric
Track model training metrics with MLflow and experiments
Lab: Explore data science in Microsoft Fabric
Explore data for data science with notebooks in Microsoft Fabric
Load data and perform initial data exploration
Gain knowledge about different types of data distributions
Understand the concept of missing data, and strategies to handle missing data effectively
Visualize data using various data visualization techniques and libraries
Lab: Use notebook for data exploration in Microsoft Fabric
Preprocess data with Data Wrangler in Microsoft Fabric
Learn Data Wrangler features, and its role in the data science workflow
Perform different types of preprocessing operations in data science
Learn how to handle missing values, and imputation strategies
Use one-hot encoding and other techniques to convert categorical data into a format suitable for machine learning algorithms
Lab: Preprocess data with Data Wrangler in Microsoft Fabric
Train and track machine learning models with MLflow in Microsoft Fabric
Train machine learning models with open-source frameworks
Train models with notebooks in Microsoft Fabric
Track model training metrics with MLflow and experiments in Microsoft Fabric
Lab: Train and track a model in Microsoft Fabric
Generate batch predictions using a deployed model in Microsoft Fabric
Save a model in the Microsoft Fabric workspace
Prepare a dataset for batch predictions
Apply the model to dataset to generate new predictions
Save the predictions to a Delta table
Lab: Generate and save batch predictions
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