About this Course
4.3
23 ratings
4 reviews
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Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 21 hours to complete

Suggested: 5 weeks of study, each with around 2.h hours work...
Available languages

English

Subtitles: English
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 21 hours to complete

Suggested: 5 weeks of study, each with around 2.h hours work...
Available languages

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
Hours to complete
3 hours to complete

Module 1: Computational Tree Logic

We introduce Labeled Transition Systems (LTS), the syntax and semantics of Computational Tree Logic (CTL) and discuss the model checking algorithms that are necessary to compute the satisfaction set for specific CTL formulas. ...
Reading
6 videos (Total 61 min), 3 readings, 4 quizzes
Video6 videos
Introduction13m
Semantics of CTL13m
Model Checking CTL9m
The Until Operator12m
The Always Operator9m
Reading3 readings
Script 1 and 2.110m
Script 2.2 and 2.310m
Script 2.420m
Quiz4 practice exercises
Formulate for yourself6m
Test your understanding of CTL semantics14m
Check your understanding of CTL20m
Model checking eventually, always and until22m
Week
2
Hours to complete
2 hours to complete

Discrete Time Markov Chains

We enhance transition systems by discrete time and add probabilities to transitions to model probabilistic choices. We discuss important properties of DTMCs, such as the memoryless property and time-homogeneity. State classification can be used to determine the existence of the limiting and / or stationary distribution. ...
Reading
5 videos (Total 49 min), 2 readings, 5 quizzes
Video5 videos
Evolution in Time13m
Transient probabilities9m
State classification5m
Steady-state probabilities12m
Reading2 readings
Script 3.1 and 3.210m
Script 3.310m
Quiz5 practice exercises
Evolution of DTMCs6m
Compute transient probabilities10m
Classification of DTMC states True or False?14m
State classification16m
Steady-state computation12m
Week
3
Hours to complete
2 hours to complete

Probabilistic Computational Tree Logic

We discuss the syntax and semantics of Probabilistic Computational Tree logic and check out the model checking algorithms that are necessary to decide the validity of different kinds of PCTL formulas. We shortly discuss the complexity of PCTL model checking. ...
Reading
5 videos (Total 36 min), 3 readings, 6 quizzes
Video5 videos
Model checking and the Next operator7m
Time-bounded Until6m
Backwards computation4m
Unbounded Until8m
Reading3 readings
Script: 4.1 and 4.210m
Script: 4.3.1 and 4.3.225m
Script 4.3.310m
Quiz6 practice exercises
PCTL Syntax8m
Checking PCTL next4m
Test your understanding of PCTL Until6m
Checking time-bounded until16m
Checking unbounded until10m
Test your understanding of PCTL6m
Week
4
Hours to complete
2 hours to complete

Continuous Time Markov Chains

We enhance Discrete-Time Markov Chains with real time and discuss how the resulting modelling formalism evolves over time. We compute the steady-state for different kinds of CMTCs and discuss how the transient probabilities can be efficiently computed using a method called uniformisation. ...
Reading
5 videos (Total 57 min), 2 readings, 6 quizzes
Video5 videos
Generator matrix11m
Steady-state probabilities11m
Triple Modular Redundancy11m
Uniformisation12m
Reading2 readings
Script: 5.1 and 5.220m
Script: 5.315m
Quiz6 practice exercises
Generator matrix6m
Test your understanding of CTMCs6m
Steady state probability in CTMCs10m
Identifying BSCCs12m
Test your understanding of Uniformisation6m
Uniformisation12m

Instructor

Avatar

Anne Remke

Prof. dr.
Computer Science

About EIT Digital

EIT Digital is a pan-European education and research-based open innovation organization founded on excellence. Its mission is to foster digital technology innovation and entrepreneurial talent for economic growth and quality of life. By linking education, research and business, EIT Digital empowers digital top talents for the future. EIT Digital provides online "blended" Innovation and Entrepreneurship education to raise quality, increase diversity and availability of the top-level content provided by 20 reputable universities of technology around Europe. The universities all together deliver a unique blend of the best of technical excellence and entrepreneurial skills and mindset to digital engineers and entrepreneurs at all stages of their careers. The academic partners support Coursera’s bold vision to enable anyone, anywhere, to transform their lives by accessing the world’s best learning experience. This means that EIT Digital gradually shares parts of its entrepreneurial and academic education programmes to demonstrate its excellence and make it accessible to a much wider audience. EIT Digital’s online education portfolio can be used as part of blended education settings, in both Master and Doctorate programmes, and for professionals as a way to update their knowledge. EIT Digital offers an online programme in 'Internet of Things through Embedded Systems'. Achieving all certificates of the online courses and the specialization provides an opportunity to enroll in the on campus program and get a double degree. These are the courses in the online programme: ...

Frequently Asked Questions

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  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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