Microsoft Copilot for Data Evaluation and Data Engineering from Udemy

*Designed for the latest version of Copilot in 2025*

What if you could profile, clean, and transform data with just a few natural language prompts? What if you could write entire pipelines, clean/profile datasets, train Machine Learning models, generate synthetic data, generate code (in multiple languages), and even build reports - all WITHOUT writing a single line of code? With Microsoft Copilot, that’s now possible - and in this course, you’ll learn exactly how.

Whether you're a data analyst, business user, or an aspiring AI-savvy professional, this is the only course you need to truly leverage Microsoft Copilot and M365 Copilot for your data-related work. We'll learn how to use Copilot in Excel (Formulas, Python based analysis, filtering) as well as Microsoft Fabric (SQL code for databases, pipelines, data Warehouse/Lakehouse, writing code in Notebooks) and so much more without writing a single line of code.

Why This Course Stands Out

Built for the New Era of Work: While most Copilot courses focus on Office productivity tools like Word and PowerPoint, this one takes you deeper - into the core of data quality, preparation, transformation, and engineering. This is where Copilot truly shines. Be it a an Excel worksheet, or Big Data pipelines within Microsoft Fabric, we'll learn how to use Copilot to simplify our tasks.
Learn by Doing, Not Just Watching: Each module is hands-on. You’ll interact with real datasets, write prompts, debug AI outputs, and explore how to guide Copilot to get high-quality results. From data profiling to synthetic data generation, this course shows exactly how to make Copilot work for you.
AI-Powered Data Engineering, Demystified: Understand the why behind Copilot’s suggestions. Learn how to control, guide, and refine it using prompt engineering so you get better, faster results - every single time.

What You’ll Be Able to Do by the End

Clean and prepare messy datasets with intelligent prompts in Excel, and Fabric
Generate reports and data visuals using natural language
Impute missing values, fix data types, and transform tables
Create realistic synthetic datasets for testing and prototyping
Understand data quality metrics like completeness, consistency, and validity
Evaluate the risks of synthetic data, and how to use it responsibly
Engineer entire data workflows using Copilot’s built-in intelligence in the MS Fabric environment (DataFlow Gen2 Pipelines, Notebooks, Data Lakehouses/Warehouses and even SQL databases. )
Train ML & statistical models in the Fabric environment (Notebooks), as well as Excel.

Tools we'll Use

Microsoft Copilot Chat (Free version)
Microsoft Copilot for M365 (With access to your OneDrive & Sharepoint files, emails, and Teams data)
Microsoft Fabric

You’ll learn the distinctions between these tools and how to apply them to your specific needs. We'll take care of both personal as well as business users in this course.

Structured for Success

Beginner-Friendly to Advanced: We start with the basics of data quality and build up to advanced use cases involving synthetic data and prompt engineering.
Modular Format: Each section is concise and laser-focused, letting you jump in where you need help most.
Instructor Access - Stuck somewhere? I’ll personally help you out.

If you're ready to future-proof your data skills and work smarter, not harder with Microsoft Copilot, then enroll today and start transforming the way you work.

What's inside

Learning objectives

Use copilot to generate transformation pipelines using dataflow gen2 in ms fabric
Use copilot to write excel formulas, generate synthetic data, sort and filter data!
Use copilot to generate sql queries for sql dbs, lakehouse and warehouse in ms fabric!

Use copilot to generate pivot tables, and perform advanced analysis using python
Generate transformation pipelines, train ml models using copilot in fabric notebooks!
Difference between the various copilot versions and choose the one best for our use case

Use copilot to generate transformation pipelines using dataflow gen2 in ms fabric
Use copilot to write excel formulas, generate synthetic data, sort and filter data!
Use copilot to generate sql queries for sql dbs, lakehouse and warehouse in ms fabric!
Use copilot to generate pivot tables, and perform advanced analysis using python
Generate transformation pipelines, train ml models using copilot in fabric notebooks!
Difference between the various copilot versions and choose the one best for our use case

Syllabus

Introduction

Download the course content

Data Quality Elements

Tools in Copilot to Evaluate Data Quality

Career center

Learners who complete Microsoft Copilot for Data Evaluation and Data Engineering will develop knowledge and skills that may be useful to these careers:

Data Quality Analyst

A Data Quality Analyst is dedicated to ensuring the accuracy, consistency, and reliability of an organization's data. This role involves identifying data issues, implementing data quality standards, and developing processes to maintain data integrity. The Microsoft Copilot for Data Evaluation and Data Engineering course provides a direct and powerful toolkit for a Data Quality Analyst. It focuses heavily on data quality elements, teaching how to clean and prepare messy datasets with intelligent prompts in Excel and Fabric, and to impute missing values and fix data types. Learners will understand data quality metrics like completeness, consistency, and validity, and how to generate data quality pipelines and reports using Copilot, making them exceptionally proficient in addressing and resolving data quality challenges.

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Data Engineer

A Data Engineer is responsible for designing, building, and maintaining the infrastructure and systems that collect, store, and process large volumes of data. This critical role ensures data is available, reliable, and optimized for various applications, including analytics and machine learning. The Microsoft Copilot for Data Evaluation and Data Engineering course provides a powerful pathway into or advancement within this field. Learners will master engineering entire data workflows using Copilot's built-in intelligence within the MS Fabric environment, including DataFlow Gen2 Pipelines, Notebooks, Data Lakehouses, and Data Warehouses. The proficiency in using Copilot to generate SQL queries for database interactions and train machine learning models directly addresses core data engineering tasks, allowing for the construction of robust data pipelines with unprecedented efficiency and reduced manual coding.

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Data Analyst

A Data Analyst plays a pivotal role in transforming raw data into actionable insights for organizations. This professional gathers, cleans, analyzes, and interprets complex datasets, often presenting findings through reports and visualizations to inform strategic decisions. The Microsoft Copilot for Data Evaluation and Data Engineering course can significantly enhance a Data Analyst's capabilities by enabling them to profile, clean, and transform data efficiently using natural language prompts within Excel and Microsoft Fabric. The ability to generate formulas, create pivot tables, perform Python-based analysis, and produce data quality reports without extensive coding empowers analysts to work smarter and faster. This course helps individuals master the tools to impute missing values, fix data types, and generate compelling data visuals, leading to more robust and reliable analytical outcomes. Success in this field is greatly aided by the course's hands-on approach to prompt engineering for high-quality results.

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Reporting Analyst

A Reporting Analyst is responsible for creating and distributing comprehensive reports that translate complex data into understandable information for stakeholders. This professional ensures that business performance is tracked, analyzed, and communicated effectively through various reporting tools and formats. The Microsoft Copilot for Data Evaluation and Data Engineering course directly equips individuals with essential skills for a Reporting Analyst role. The course explicitly teaches how to generate reports and data visuals using natural language, and how to produce data quality visuals and reports. By leveraging Copilot in Excel for creating pivot tables, sorting, filtering data, and performing advanced analysis, learners can significantly streamline their reporting processes and deliver high-quality, insightful reports with unparalleled speed and accuracy.

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AI Prompt Engineer

An AI Prompt Engineer is a specialist at crafting, refining, and optimizing natural language prompts to guide AI models, such as large language models, to achieve desired outputs. This role requires a deep understanding of how AI interprets instructions and how to iterate on prompts for precision and quality. The Microsoft Copilot for Data Evaluation and Data Engineering course provides direct, hands-on experience in this emerging and critical field for an AI Prompt Engineer. The course explicitly teaches prompt engineering, allowing learners to understand the 'why' behind Copilot's suggestions and how to control, guide, and refine its outputs to get better, faster results every single time. This includes generating specific code, transforming data, and producing reports, all by mastering the art of effective AI prompting and debugging AI outputs.

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Business Intelligence Analyst

A Business Intelligence Analyst is crucial for helping organizations make informed decisions by transforming data into meaningful insights. This role involves designing and developing dashboards, reports, and data models that provide a clear view of business performance. The Microsoft Copilot for Data Evaluation and Data Engineering course is highly relevant for aspiring or current Business Intelligence Analyst professionals. It teaches how to generate reports and data visuals using natural language, a direct skill for this role. Furthermore, the course's focus on profiling, cleaning, and transforming data, combined with its application in Microsoft Fabric, empowers analysts to ensure the underlying data for their BI solutions is accurate and reliable. The ability to manipulate data in Excel and within Fabric environments with Copilot streamlines the entire BI development lifecycle, fostering efficiency and precision.

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Analytics Engineer

An Analytics Engineer bridges the gap between data engineering and data analysis, focusing on optimizing data for consumption by downstream users. This professional builds robust and scalable data models, transformations, and pipelines to ensure high-quality, trustworthy data for reporting and analytical tools. The Microsoft Copilot for Data Evaluation and Data Engineering course is exceptionally well-suited for an Analytics Engineer. The course directly addresses the core functions of this role by teaching how to generate transformation pipelines using DataFlow Gen2 in MS Fabric and how to clean and prepare messy datasets. Through prompt engineering, individuals can guide Copilot to impute missing values, fix data types, and engineer entire data workflows for maximum accuracy and efficiency, thereby building a strong foundation for reliable analytical products.

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Data Scientist

A Data Scientist is a multidisciplinary professional who uses statistical methods, machine learning, and computational tools to extract knowledge and insights from data. This role often involves extensive data cleaning, modeling, and interpretation to solve complex business problems. The Microsoft Copilot for Data Evaluation and Data Engineering course can be highly beneficial for an aspiring or practicing Data Scientist. While Data Scientists often delve deep into algorithms, this course provides powerful capabilities for the crucial initial and ongoing data preparation phases. It teaches how to clean and prepare messy datasets, apply various data transformations, and even train machine learning and statistical models using Copilot in Fabric Notebooks and Excel, accelerating the experimental and modeling aspects of the Data Scientist's work. This includes generating realistic synthetic data for testing models.

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Data Governance Specialist

A Data Governance Specialist develops and enforces policies, standards, and procedures to ensure the accuracy, security, and integrity of an organization's data assets. This role is fundamental in establishing trust in data and ensuring compliance with regulations. The Microsoft Copilot for Data Evaluation and Data Engineering course aligns well with the objectives of a Data Governance Specialist. It provides detailed insight into data quality elements, understanding critical metrics like completeness, consistency, and validity. Furthermore, the course addresses the risks associated with synthetic data and best practices for its responsible generation and use. By gaining proficiency in using Copilot to profile, clean, and transform data, individuals can actively contribute to maintaining high data quality standards, which is a cornerstone of effective data governance and regulatory adherence.

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BI Developer

A BI Developer specializes in creating and managing business intelligence solutions, including data warehouses, data marts, and reporting infrastructure. This professional is instrumental in designing and implementing data models and ETL Extract Transform Load processes that facilitate data analysis and reporting. The Microsoft Copilot for Data Evaluation and Data Engineering course is highly pertinent for a BI Developer. The course teaches how to engineer entire data workflows using Copilot within the MS Fabric environment, specifically focusing on DataFlow Gen2 Pipelines, Data Lakehouses, and Data Warehouses. The ability to generate SQL queries for these environments and to clean and prepare messy datasets with intelligent prompts allows BI Developers to construct more efficient and robust data pipelines and models, significantly accelerating development cycles for comprehensive BI solutions.

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Data Steward

A Data Steward is responsible for the day-to-day management and oversight of specific data assets within an organization, ensuring data quality, integrity, and adherence to governance policies. This role involves working closely with data owners and users to resolve data issues and promote best practices. The Microsoft Copilot for Data Evaluation and Data Engineering course is highly relevant for a Data Steward. It provides comprehensive training on data quality elements, showing how to profile, clean, and transform data with intelligent prompts in Excel and Fabric. Learners will gain practical skills in imputing missing values, fixing data types, and generating synthetic data responsibly, which are all critical for maintaining high data quality standards and supporting effective data governance initiatives. This empowers Data Stewards to actively manage and improve their data domains and ensure data trustworthiness.

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Machine Learning Engineer

A Machine Learning Engineer focuses on designing, building, and deploying scalable machine learning systems. This role often requires strong programming skills and a deep understanding of ML algorithms, but also heavily relies on robust data pipelines and proper data preparation for model training and inference. The Microsoft Copilot for Data Evaluation and Data Engineering course can significantly augment the capabilities of a Machine Learning Engineer by streamlining the data-centric aspects of their work. Learners will gain proficiency in using Copilot to engineer entire data workflows, generate SQL queries for data access, and train ML and statistical models in the Fabric environment (Notebooks), as well as Excel. The ability to generate synthetic data for model testing and prototyping is also a substantial advantage, enhancing efficiency in the ML model development lifecycle.

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Solutions Architect

A Solutions Architect designs and defines the overall structure of a solution to meet specific business requirements. For data-intensive projects, this involves selecting appropriate technologies, designing data flows, and ensuring scalability and integration. The Microsoft Copilot for Data Evaluation and Data Engineering course can be highly beneficial for a Solutions Architect, particularly one focusing on modern data platforms. Understanding how Copilot enables profiling, cleaning, transforming data, and engineering entire data workflows within Microsoft Fabric (DataFlow Gen2, Lakehouse, Warehouse) provides architects with insights into building efficient, AI-augmented data solutions. This course helps in designing architectures that leverage low-code or no-code AI capabilities to accelerate development and improve data quality, offering new strategies for solution delivery in a rapidly evolving technological landscape.

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Technical Product Manager Data Products

A Technical Product Manager for Data Products leads the strategy and development of data-focused products or features. This role requires a blend of technical understanding, business acumen, and an ability to translate market needs into product roadmaps. The Microsoft Copilot for Data Evaluation and Data Engineering course is useful for a Technical Product Manager Data Products. Understanding how Copilot can profile, clean, and transform data, generate synthetic data, and engineer entire data workflows in Microsoft Fabric provides valuable insights into the capabilities and limitations of AI-driven data development. This knowledge helps in defining product requirements, evaluating development effort, and understanding how to leverage new AI tools to accelerate the creation and delivery of innovative data products, from conception to deployment, and effectively communicating technical capabilities.

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Business Systems Analyst

A Business Systems Analyst focuses on improving business processes by analyzing system requirements and designing solutions that integrate technology with business needs. This role often involves working with data, understanding data flows, and generating reports to support operational improvements. The Microsoft Copilot for Data Evaluation and Data Engineering course may be helpful for a Business Systems Analyst. The course's emphasis on using Copilot in Excel for data analysis, filtering, generating formulas, and creating pivot tables directly supports many business analysis tasks. Additionally, understanding how to clean and prepare messy datasets and generate reports using natural language can significantly enhance their ability to analyze business data and articulate requirements for system enhancements, particularly within the Microsoft ecosystem, potentially accelerating business process optimization.

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