DP-604: Implement a Data Science and Machine Learning Solution for AI with Microsoft
LOCATION | October | November | December | January |
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Auckland | ||||
Hamilton | ||||
Christchurch | ||||
Wellington | ||||
Virtual Class |
In this one-day course students explore the data science process and learn how to train machine learning models to accomplish artificial intelligence in Microsoft Fabric.
This one-day course prepares you for an Applied Skills credential.
For more than 30 years, Microsoft's industry-recognised certifications have provided proof of world-class technical proficiency for in-demand job roles. In today’s ever-changing business environment, there are also times when you need verified project-specific skills. Microsoft Applied Skills is a new verifiable credential that validates that you have the targeted skills needed to implement critical projects aligned to business goals and objectives. Applied Skills gives you a new opportunity to put your skills centre-stage, empowering you to showcase what you can do and what you can bring to key projects in your organisation.
- Data Scientists
- Data Analysts
- Data Engineer
- You should be familiar with basic data concepts and terminology.
After completing this course, students will be able to:
- Understand the data science process
- Train models with notebooks in Microsoft Fabric
- Track model training metrics with MLflow and experiments
- 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
- Visualise data using various data visualisation techniques and libraries
- 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 strategie
- Use one-hot encoding and other techniques to convert categorical data into a format suitable for machine learning algorithms.
- 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
- 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
- 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