We may earn an affiliate commission when you visit our partners.
Course image
Microsoft

Did you know that integrating AI with cybersecurity can reduce incident response times by up to 70%?

This Short Course was created to help cybersecurity professionals harness the power of Microsoft Security Copilot to enhance their security strategies.

By completing this course you'll be able to integrate advanced AI capabilities into your security operations, enabling faster and more effective responses to threats.

Read more

Did you know that integrating AI with cybersecurity can reduce incident response times by up to 70%?

This Short Course was created to help cybersecurity professionals harness the power of Microsoft Security Copilot to enhance their security strategies.

By completing this course you'll be able to integrate advanced AI capabilities into your security operations, enabling faster and more effective responses to threats.

More specifically, in this 3-hour-long commitment, you will learn how to understand the functionalities of Microsoft Security Copilot, integrate it with various security tools, and apply its capabilities in practical security scenarios.

This project is unique because it bridges the gap between AI technology and practical security needs. To be successful in this project, you will need at least 2 years of experience in cloud security, 1 year with Microsoft security products like Sentinel and Defender XDR, and foundational knowledge of KQL.

Enroll now

What's inside

Syllabus

Microsoft Copilot for Security
By the end of this lesson, you will become familiar with the course objectives, syllabus and will have met the instructor.
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Makes use of AI in cybersecurity to reduce incident response times
Created in collaboration with Microsoft, a global leader in the technology industry
Provides foundational knowledge in key concepts such as KQL
In-depth coverage of Microsoft Security Copilot, spanning its integration and application across multiple Microsoft security products
Emphasis on optimizing AI capabilities for enhanced security results

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.
Save

Reviews summary

Practical ai for cybersecurity professionals

According to learners, this course offers a highly relevant and practical introduction to Microsoft Copilot for Security, specifically designed for cybersecurity professionals. It excels at bridging AI technology with security operations, enabling faster incident response. Many found the content on integration and provisioning with existing tools, and effective prompt engineering particularly useful, providing actionable insights. While its 3-hour format is concise, some felt it serves best as a foundational overview, requiring prior experience with Microsoft security products and KQL. It's praised for equipping students with skills for immediate application in real-world scenarios.
A concise overview, best suited for experienced professionals.
"The 3-hour format is excellent for a quick grasp, but it's clearly designed for someone with <span class="neutral">prior cloud security experience and <span class="neutral">KQL knowledge."
"As someone new to <span class="warning">Microsoft security products, I felt the pace was a bit fast; it's definitely for experienced professionals."
"It provides a <span class="neutral">strong overview, but don't expect deep dives into every single feature; it's more about understanding <span class="neutral">Copilot's core capabilities."
Well-organized presentation of complex information.
"The <span class="neutral">syllabus is logical and the lessons flow seamlessly, making complex topics easy to follow."
"I found the <span class="neutral">instructor's explanations to be very clear and concise, which is vital for new technologies like Copilot."
"Each <span class="neutral">lesson objective was met, providing a solid step-by-step understanding of <span class="neutral">Copilot for Security's functionalities."
Provides essential techniques for leveraging AI capabilities.
"The <span class="neutral">prompt engineering lesson alone was worth it; it clarified how to get the most out of <span class="neutral">Copilot for Security."
"I appreciate the deep dive into <span class="neutral">crafting effective prompts and utilizing <span class="neutral">built-in promptbooks for specific tasks."
"Understanding how to <span class="neutral">bridge AI technology with practical security needs through prompting was a game changer for me."
Equips professionals with timely, applicable skills.
"This course is incredibly timely; learning <span class="neutral">Microsoft Copilot for Security immediately boosts my capability in the current threat landscape."
"I found the content directly applicable to my job, especially the sections on <span class="neutral">integrating Copilot with Defender XDR and <span class="neutral">Sentinel."
"The focus on <span class="neutral">practical security scenarios and <span class="neutral">real-world application made this a highly valuable 3 hours."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Microsoft Copilot for Security with these activities:
Understanding Cybersecurity Fundamentals
Review foundational concepts in cybersecurity to strengthen understanding of advanced AI and cybersecurity integration techniques.
Show steps
  • Revisit core cybersecurity concepts such as network security, cryptography, and threat analysis.
  • Review best practices for data protection and incident response.
Find a Cybersecurity Mentor
Connect with an experienced cybersecurity professional who can guide you and provide support as you navigate your learning journey in this field.
Show steps
  • Identify potential mentors through online platforms, industry events, or professional networks.
  • Reach out to your chosen mentors and introduce yourself, expressing your interest in their guidance.
  • Establish regular communication channels and schedule meetings to discuss your progress and seek advice.
Attend a Security Copilot Workshop
Accelerate your learning and connect with experts by attending a workshop dedicated to Microsoft Security Copilot, where you can delve into its features, applications, and best practices.
Show steps
  • Research and identify upcoming workshops on Microsoft Security Copilot.
  • Register for a workshop that aligns with your schedule and learning objectives.
  • Attend the workshop, actively participate in discussions, and engage with the instructors and fellow attendees.
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Navigating Microsoft Security Copilot
Familiarize yourself with the functionalities and features of Microsoft Security Copilot.
Show steps
  • Follow Microsoft's official documentation and tutorials on Microsoft Security Copilot.
  • Explore the Microsoft Security Copilot interface and its various features.
Follow tutorials on using Microsoft Security Copilot
There are many tutorials that can help you learn how to use Microsoft Security Copilot more effectively.
Show steps
  • Search for tutorials on Microsoft Security Copilot
  • Choose a tutorial that fits your level of experience
  • Follow the steps in the tutorial
Attend networking events related to cybersecurity
Networking events are a great way to meet other cybersecurity professionals and learn about new technologies and trends.
Browse courses on Cybersecurity
Show steps
  • Find networking events in your area
  • Register for the events
  • Attend the events and network with other attendees
Attend workshops on Microsoft Security Copilot
Workshops are a great way to learn more about Microsoft Security Copilot and how to use it effectively.
Show steps
  • Find workshops on Microsoft Security Copilot
  • Register for the workshops
  • Attend the workshops and learn from the experts
Explore Copilot for Security's GitHub Repository
Deepen your understanding of Microsoft Copilot for Security by delving into its open-source repository and exploring its codebase, documentation, and examples.
Show steps
  • Navigate to the official GitHub repository for Microsoft Copilot for Security.
  • Review the documentation, code samples, and issue tracker to gain insights into its implementation and usage.
  • Consider contributing to the project by reporting issues or suggesting improvements.
KQL Query Practice
Sharpen KQL skills essential for effective use of Microsoft Security Copilot.
Browse courses on KQL
Show steps
  • Work through KQL tutorials and exercises.
  • Practice crafting queries to extract security-related insights from logs.
  • Create custom KQL queries to address specific security scenarios.
Practice Prompt Engineering
Enhance your ability to effectively utilize Microsoft Copilot for Security by honing your prompt engineering skills through repeated practice.
Browse courses on Prompt Engineering
Show steps
  • Generate different types of prompts based on security scenarios you encounter.
  • Experiment with various prompt formats and lengths to determine optimal outcomes.
  • Analyze the results generated by Copilot for Security and identify areas for improvement in your prompts.
Practice using Microsoft Security Copilot to respond to security threats
Practice using Microsoft Security Copilot to respond to security threats and improve your incident response time.
Browse courses on Security Threats
Show steps
  • Set up a test environment
  • Create a security scenario
  • Use Microsoft Security Copilot to respond to the security scenario
  • Evaluate the results
Volunteer at a cybersecurity organization
Volunteering is a great way to give back to the community and learn more about cybersecurity.
Browse courses on Cybersecurity
Show steps
  • Find a cybersecurity organization to volunteer for
  • Contact the organization and express your interest in volunteering
  • Attend training and orientation sessions
  • Volunteer your time and skills to help the organization
Contribute to Open-Source Security Projects
Enhance your cybersecurity skills and make valuable contributions to the community by actively engaging in open-source security projects that align with your interests and skillset.
Show steps
  • Identify open-source security projects that resonate with you and your areas of expertise.
  • Familiarize yourself with the project's codebase, documentation, and contribution guidelines.
  • Propose changes, bug fixes, or new features, and submit pull requests for review.
  • Collaborate with other contributors and maintainers to refine and improve the project.

Career center

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

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Microsoft Copilot for Security.
This widely recognized and comprehensive textbook that provides a deep dive into the subject of language processing. It is suitable for both undergraduate and graduate-level courses and is considered a must-read for gaining a strong theoretical and applied understanding of NLP. The authors are leading researchers in the field, and the book is frequently updated to reflect advancements. The latest draft is available online.
The premier applied machine learning masterwork, taking practitioners through intuitive concept breakdowns, production-grade Scikit-Learn workflows, and deep neural architecture implementations.
A timeless mathematical masterpiece that provides an uncompromising Bayesian and probabilistic foundation for linear classifiers, graphical models, kernel methods, and sampling algorithms.
Provides a comprehensive guide to prompt engineering, covering techniques for crafting effective inputs to generative AI models. It's particularly useful for understanding how to obtain reliable and predictable results, which is crucial for both beginners and those looking to deepen their practical skills. This book is valuable as a current reference for anyone working with generative AI.
This practical book dives into using transformers, the dominant architecture for many state-of-the-art NLP tasks, with the Hugging Face Transformers library. , It's ideal for data scientists and coders who want to learn how to build and scale models for various NLP applications using this popular library. It covers contemporary topics and is highly relevant for current NLP practice.
The definitive mathematical and theoretical canon of statistical learning, establishing the rigorous analytical foundations of regularized regression, tree ensembles, and high-dimensional inference.
A distilled practitioner field guide outlining best practices for the entire machine learning lifecycle, from problem formulation and feature engineering to model deployment and monitoring.
Delivers an end-to-end systems architecture guide for building reliable production ML systems, addressing data engineering trade-offs, real-time feature computation, and model drift mitigation.
Bridges linear algebra, multivariable calculus, vector geometry, and probability directly to fundamental machine learning algorithms like PCA, Gaussian mixture models, and support vector machines.
Provides the monumental mathematical foundation of modern neural networks, connecting deep representation learning, backpropagation dynamics, and sequence modeling to empirical machine learning.
Instructs data scientists on applied model evaluation, cross-validation, hyperparameter tuning, and pipeline construction through Scikit-Learn maintainers Andreas Müller and Sarah Guido.
Takes a deep dive into advanced threat hunting and detection techniques using Microsoft Defender XDR. It covers topics such as threat hunting strategies, leveraging threat intelligence, and using machine learning for detection.
This comprehensive guide provides a deep dive into Elasticsearch, covering its architecture, data ingestion, querying, and analytics capabilities. Its relevance to KQL stems from Elasticsearch being the underlying data store that KQL interacts with.
Collection of recipes for solving common KQL problems. It valuable resource for experienced users who want to learn how to use KQL to solve specific problems.
Provides a comprehensive overview of cloud security, covering everything from basic concepts to advanced topics such as threat detection and incident response. It is an excellent resource for anyone who wants to learn more about cloud security.
This foundational text offers a comprehensive introduction to statistical methods in NLP. It covers the necessary theory and algorithms for building NLP tools, with a rigorous treatment of mathematical and linguistic foundations. While published in 1999, it remains highly relevant for understanding the statistical underpinnings of many NLP techniques and valuable reference for researchers and students alike.
Provides a deep dive into the technical aspects of cloud security. It covers topics such as cloud security architectures, security controls, and threat detection and response.
Serves as a practical introduction to NLP with a strong focus on using the Natural Language Toolkit (NLTK) library in Python. It's excellent for beginners and those who want a hands-on approach to learning NLP concepts through programming examples. It's widely used as a textbook and provides a solid foundation for implementing basic NLP tasks.
Provides a hands-on approach to prompt engineering with a focus on using the OpenAI API. It's particularly relevant for undergraduate students, graduate students, and working professionals who want to programmatically interact with LLMs. It serves as a practical guide for implementing prompt engineering techniques in applications.
Offers a practical, hands-on approach to prompt engineering specifically with ChatGPT. It's an excellent resource for high school and undergraduate students getting started, providing clear examples and exercises. It serves as a useful introductory guide and additional reading to complement foundational AI courses.
Investigates the engineering realities of running automated ML pipelines in production, addressing data drift detection, automated retraining loops, telemetry infrastructure, and continuous validation.
Details cloud-native DevOps architectures for orchestrating automated machine learning lifecycles, integrating CI/CD triggers, model registry synchronization, and automated hyperparameter sweep workers.
This textbook offers a technical perspective on NLP, synthesizing classical methods with contemporary machine learning techniques. , It covers topics from basic textual analysis to structured representations and semantic analysis, making it suitable for advanced undergraduate and graduate courses. It requires a background in programming and college-level mathematics.
Focuses on the creative aspects of prompt engineering and generating diverse language outputs. It's a good fit for students and professionals looking to go beyond basic prompting and explore more advanced techniques for creative content generation. It adds breadth by covering applications in areas like creative writing and podcasting.
Guides engineers step-by-step through implementing, training, and fine-tuning complete generative transformer architectures in pure PyTorch, providing crystal-clear low-level insight into modern models.
Provides a comprehensive guide to security operations for the modern enterprise using Microsoft Defender XDR. It covers a variety of topics, including threat monitoring, threat investigation, and incident response.
A comprehensive guide aimed at making prompt engineering accessible to a wide audience. It covers various techniques and applications for leveraging AI language models effectively. is useful for high school students through working professionals seeking a thorough introduction and practical guidance.
This guide aims to make prompt engineering accessible with a step-by-step approach. It is well-suited for beginners and those new to the field, including high school students and those in introductory undergraduate programs. It provides practical tips and is useful for gaining a broad understanding of how to formulate effective AI prompts.
Presents the foundational treatise on Markov decision processes, temporal-difference learning, and policy gradient methods that underpin autonomous decision-making and modern post-training alignment.
This guide offers quick tips and tricks for prompt engineering across different generative AI models, including text and image generation models. It's a practical resource for users who want to improve their immediate results with various AI tools. It's suitable for all levels looking for actionable advice.
Combines interactive Jupyter notebooks with rigorous mathematical explanations to teach machine learning practitioners how modern neural architectures are designed, implemented, and trained.
Takes a practical, code-first approach to deep learning, including applications in NLP, using the fastai library and PyTorch. , It's designed for programmers who want to achieve impressive results in deep learning with less emphasis on the underlying mathematics. It's a great resource for quickly getting hands-on experience with modern deep learning techniques in NLP.
Focuses on implementing NLP models using the PyTorch deep learning library. It's a practical guide for those who prefer PyTorch and want to learn how to build various NLP applications using this framework. It's suitable for developers and researchers.
This handbook is geared towards engineers working with LLMs, covering the process from concept to production. It provides a deeper technical understanding of integrating and managing LLMs, which is relevant for prompt engineers working in a development context. It is best suited for graduate students and working professionals.
Provides a comprehensive overview of cloud security risks and best practices. It is an excellent resource for anyone who wants to learn more about how to protect data and applications in the cloud.
Takes a practical, project-based approach to learning NLP, guiding readers through building various NLP applications using Python libraries. It's focused on applying NLP concepts to solve real-world problems and is suitable for developers and practitioners who want to gain hands-on experience.
Save
This practical book focuses on applying text analysis techniques using Python and machine learning. , It's geared towards data scientists and developers who want to build real-world NLP applications. It covers various aspects of the NLP pipeline and is valuable for its applied approach.
Explores prompt engineering within the broader context of generative AI and touches upon ethical considerations. It's relevant for all levels, providing a balanced view of the technical aspects and the societal impact of generative AI. It's useful for gaining a broader understanding and considering the responsible use of AI.
While not solely focused on prompt engineering, this book provides a strong foundation in understanding how LLMs work, which is essential for effective prompting. It's suitable for undergraduate and graduate students, offering technical insights into language understanding and generation. It serves as valuable background reading for those wanting to understand the underlying mechanisms of the models they are prompting. Expected publication in September 2024.
Focuses on the security and privacy challenges faced by enterprises that are adopting cloud computing. It provides practical guidance on how to protect data, applications, and infrastructure in the cloud.
Provides a hands-on approach to cloud security. It covers topics such as cloud security assessment, cloud security testing, and cloud security incident response.
Provides a comprehensive overview of cloud security compliance. It covers topics such as cloud security standards, cloud security regulations, and cloud security audits.
Unifies computer science, evolutionary biology, and neuroscience to synthesize the five foundational tribes of machine learning, giving practitioners a panoramic interdisciplinary view of learning algorithms.
This comprehensive handbook provides an overview of concepts, methodologies, and applications in computational linguistics and NLP. , It covers a wide range of topics and can serve as a valuable reference for researchers and advanced students looking for detailed information on specific areas within the field.
Covers the broader field of AI engineering with a focus on foundation models, which include the LLMs used in prompt engineering. It's relevant for professionals and graduate students interested in the engineering aspects of building AI applications. It provides context on how prompt engineering fits into larger AI systems.
Focuses on the practical aspects of building NLP systems. While prompt engineering specific technique, understanding the entire NLP pipeline is beneficial for professionals. It's a good reference for those looking to implement prompt engineering within larger NLP applications.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Microsoft Copilot for Security.
Microsoft Security Solutions Capabilities
Most relevant
Cloud Computing Security - Master's
Most relevant
AWS Databases, Messaging, and Event Driven Architecture
Most relevant
Design security solutions for applications and data
Most relevant
SC-200 Microsoft Security Operations Analyst
Most relevant
Increasing Application Security: Bedrock Guardrails &...
Most relevant
Preparing for the AZ-900 Microsoft Azure Fundamentals Exam
Most relevant
Microsoft 365 Security Admin Course with practice SIMs
Most relevant
SC-200: Microsoft Security Operations Analyst
Most relevant

Coursera Buyer Protection & Guarantee

Verified partner policies & purchase protections

Accredited University Partner
Free Trial & Audit

7-Day Free Trial & Free Audit

7-day free trial on monthly Coursera Plus subscriptions; free audit option available on most individual courses to explore video lectures and readings at no charge.

Return & Refund Policy

14-Day Refund Guarantee

14-day refund window on annual Coursera Plus subscriptions and single-course purchases prior to certificate issuance. Monthly subscriptions do not offer refunds once billed.

Buyer Protections

Verified Academic & Industry Partner

Accredited university and industry certifications (e.g. Stanford, Google, IBM, Yale), secure SSL payment processing, and verifiable digital certificate links.

Key Purchase Protections
14-day refund window on annual Coursera Plus and single courses
7-day free trial on monthly Coursera Plus subscriptions
Free course audit option for lectures and readings
Verified certificates from top universities & companies
OpenCourser Verified Partner Policy details last reviewed: 2026-10-22
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser