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Quantitative Model Checking
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Quantitative Model Checking

Master formal verification: Learn to model and analyze probabilistic systems using Markov chains and temporal logics.

Course Cost

₹ 2,699

Intermediate

Skill Level

12 Hours

Self-paced lessons

This course introduces quantitative model checking for Markov chains, a powerful technique for verifying probabilistic systems. It covers the fundamentals of computational tree logic (CTL), discrete-time and continuous-time Markov chains, and their respective temporal logics: PCTL and CSL. Students will learn to model complex systems, express dependability properties, and use algorithms to verify these properties. The course emphasizes both theoretical understanding and practical application, teaching students to analyze and compute satisfaction sets for various properties in probabilistic systems.

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4.2

6,407 Enrolled

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English

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olive-leaves-logo

4.2

6,407 Enrolled

olive-leaves-logo

English

What you'll learn

  • Understand and apply Computational Tree Logic (CTL) for modeling system properties

  • Master the concepts of Discrete-Time and Continuous-Time Markov Chains

  • Learn to express and verify probabilistic properties using PCTL and CSL

  • Develop skills in model checking algorithms for various temporal logic formulas

  • Analyze the temporal evolution of Markov chains and compute transient probabilities

  • Understand state classification and compute steady-state probabilities

  • Apply uniformization techniques for efficient model checking

  • Gain practical experience in verifying dependability properties of complex systems

Skills you'll gain

Model Checking
Markov Chains
Temporal Logic
CTL
PCTL
CSL
Formal Verification
Probabilistic Systems

This course includes:

4 Hours PreRecorded video

27 assignments

Access on Mobile, Tablet, Desktop

FullTime access

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There are 5 modules in this course

This course provides a comprehensive introduction to quantitative model checking for Markov chains. It is structured into five modules, covering Computational Tree Logic (CTL), Discrete-Time Markov Chains (DTMCs), Probabilistic CTL (PCTL), Continuous-Time Markov Chains (CTMCs), and Continuous Stochastic Logic (CSL). The curriculum progresses from basic concepts to advanced techniques, teaching students how to model complex systems, express dependability properties, and verify these properties using sophisticated algorithms. Throughout the course, students will learn to analyze the temporal evolution of Markov chains, compute transient and steady-state probabilities, and apply uniformization techniques for efficient model checking. By the end of the course, students will be equipped with the skills to formally verify probabilistic systems in various domains, including embedded systems, cyber-physical systems, and communication protocols.

Computational Tree Logic

Module 1 · 3 Hours to complete

Discrete Time Markov Chains

Module 2 · 3 Hours to complete

Probabilistic Computational Tree Logic

Module 3 · 2 Hours to complete

Continuous Time Markov Chains

Module 4 · 2 Hours to complete

Continuous Stochastic Logic

Module 5 · 2 Hours to complete

Fee Structure

Payment options

Financial Aid

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Quantitative Model Checking

Intermediate

Skill Level

12 Hours

Self-paced lessons

Course Cost

₹ 2,699

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.