Subject Area | Signals, Communications, and Networking |
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Semester | Semester 3 – Fall |
Type | Required |
Teaching Hours | 4 |
ECTS | 6 |
Prerequisites |
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Recommended Courses |
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Course Site | http://eclass.uth.gr/ |
Course Director |
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Course Instructor |
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Scientific Responsible |
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Title | MLSysOps: Machine Learning for Autonomic System Operation in the Heterogeneous Edge-Cloud Continuum |
Duration | 2023 – 2025 |
Site | https://csl.e-ce.uth.gr/projects/mlsysops |
Department of Electrical and Computer Engineering | |
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Tel. | +30 24210 74967, +30 24210 74934 |
gece ΑΤ e-ce.uth.gr | |
PGS Tel. | +30 24210 74933 |
PGS e-mail | pgsec ΑΤ e-ce.uth.gr |
URL | https://www.e-ce.uth.gr/contact-info/?lang=en |
Subject Area | Signals, Communications, and Networking |
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Semester | Semester 3 – Fall |
Type | Required |
Teaching Hours | 4 |
ECTS | 6 |
Prerequisites |
|
Recommended Courses |
|
Course Site | http://eclass.uth.gr/ |
Course Director |
|
Course Instructor |
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This is an introductory course in Probability Theory. It treats discrete and continuous random variables as well as basic theorems and methods and tools for problem that involve uncertainty. The student is exposed to a variety of problems mainly in the area of Electrical and Computer Engineering. Probability is a basic tool in many scientific areas as well.
Upon completion the student will be able to: