What you'll learn

Assess and improve data quality using Copilot's analysis tools
Generate synthetic datasets for various applications, such as model training or privacy preservation
Clean and prepare data for analysis, automating tasks like formatting, deduplication, and standardization
Develop strategies for integrating Copilot into existing data workflows

Details to know

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Assessments

6 assignments

Taught in English

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This course is part of the Microsoft Copilot for Data Science Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 3 modules in this course

This module explores how Copilot's natural language processing and generative AI capabilities can be leveraged to assess data quality, identify anomalies, and generate actionable insights for data improvement.

What's included

10 videos6 readings2 assignments

10 videosTotal 46 minutes

The foundations of data quality6 minutesPreview module
Spotting the unusual: Anomaly detection with generative AI2 minutes
Comparing anomaly detection methods: Traditional vs. generative5 minutes
High-Level Use Case: Anomaly Detection3 minutes
Copilot: The AI-powered data analyst2 minutes
Demo: Data analysis with Copilot5 minutes
Demo: Data quality assessment2 minutes
Choosing the right tool for the job6 minutes
Copilot's ROI on data quality: A business case2 minutes
Building your data quality strategy with Copilot8 minutes

6 readingsTotal 60 minutes

Data anomalies: A field guide10 minutes
Choosing the right anomaly detection method10 minutes
NLP and generative AI: The power behind Copilot10 minutes
Data quality reports: Deciphering the insights10 minutes
The cost of bad data: A business perspective10 minutes
Blueprint for data quality: A step-by-step guide10 minutes

2 assignmentsTotal 45 minutes

Can you identify data quality, ROI, and how to build a data strategy?30 minutes
Can you spot the anomaly?15 minutes

This module dives into using Copilot to generate synthetic datasets for various purposes, exploring its strengths and limitations, and discussing the ethical considerations and potential risks of utilizing synthetic data.

What's included

13 videos4 readings2 assignments

13 videosTotal 57 minutes

The art of data augmentation6 minutesPreview module
Synthetic data in action3 minutes
Copilot and synthetic data3 minutes
Demo: Data augmentation with Copilot5 minutes
Demo: Building a synthetic customer data generator5 minutes
Copilot's synthetic data engine3 minutes
Synthetic data tips4 minutes
Copilot for model training6 minutes
Dangers of low-quality synthetic data3 minutes
Case study: Synthetic data success4 minutes
Synthetic data and privacy3 minutes
How Do We Safely Create Synthetic Data?5 minutes
Synthetic data's future3 minutes

4 readingsTotal 40 minutes

Synthetic data 10110 minutes
Copilot's advanced techniques10 minutes
Evaluating synthetic data10 minutes
Ethics of synthetic data10 minutes

2 assignmentsTotal 45 minutes

Can you spot quality synthetic datasets?30 minutes
Can you generate synthetic data?15 minutes

This module focuses on harnessing Copilot's capabilities to automate and streamline data cleaning and preparation tasks, enhancing data quality and readiness for analysis, while minimizing manual effort.