Arama sonuçları: 3193
- Öğretmen: Mahommad Karimi
This course introduces the principles and applications of water resources engineering, focusing on how water moves, is stored, and can be managed in natural and human-made systems. Students will learn how to analyze catchments, estimate runoff, and design systems for water supply, irrigation, and flood control.
The course combines theory with practical tools such as HEC-HMS for hydrologic modeling and decision-making. It also emphasizes sustainable management, showing how engineering solutions connect with environmental and social needs. By the end of the course, students will understand the main components of the hydrologic cycle, evaluate water demands, and apply engineering approaches to solve real-world water challenges.
- Öğretmen: Mehrnoush Kohandel
This course aims to provide graduate students with the information and practices in project appraisal, life cycle costing, value management and envirnonmental management. This course covers a wide range of subjects that are required in the daily operations in the construction industry. Students will gain valueable experience through different types of projects which will require the application of life cycle costing methods, value management, envirnonmental appraisal and management and an overall project appraisal.
- Öğretmen: Tahir Celik
This course provides to reduce the carbon
footprint of organisations and encourage the conservation of energy, energy
efficiency has become an integral part of building services design, maintenance
and upgrade. This course consists of four modules that, together, provide an
introduction to energy efficiency in buildings. It is a comprehensive tutorial,
meant to engage and challenge students to consider the many decision levels and
options involved in advancing energy efficiency in buildings. The course covers
the fundamental technical, design, policy and financial dimensions necessary to
practically engage on the topic. Energy efficient buildings are a cornerstone
of a prosperous, sustainable and healthy society. This course aims to prepare
participants to successfully advance energy efficient building construction and
retrofits by equipping them.
- Öğretmen: Reza Goldaran
Construction projects are risky. Things can and do go wrong
regularly. In this course, we explore the fundamentals of risk
management in construction projects. The purpose of this course is to
learn the tools and techniques to manage uncertain events and
circumstances that can influence the project. The course is designed for
engineers, quantity surveyors, and construction management
professionals looking to further develop their learning.
By the end of this course, you should be able to:
Understand the fundamentals of risk management including key terms and definitions
Apply and use the risk management process to properly identify, analyze and manage uncertain events and circumstances
Understand
the specific risks applicable to construction projects including
technical, construction, health and safety, environmental, commercial,
and external
This course focuses on learning data science through the interest to development and improvement of capability of solving rich problems from data point of view in a systematic and principled way by using high quality instructions and basic level data science techniques. Students will be introduced to what data science is, will discover the applicability of data science across fields, and will learn how data analysis can help them make data driven decisions. Students will gain familiarity with various open source tools and data science programs used by data scientists, like Jupyter Notebooks, RStudio, GitHub, and SQL. This course provides the students with the required structure and responsibilities in order to educate them as data scientists progressing a right way with high concluding capabilities.
- Öğretmen: Jana Alhajj
- Öğretmen: Kian Jazayeri
- Öğretmen: Daniel Okpala
This course looks into internet and global network concepts are taken up in detail. This course also deals with the most popular topics such as the history of Internet, a general overview of the internet based opportunities and applications (such as e-mail, internet browsers, file transfer opportunities, list drivers, etc.) internet based research and information resources, the global network services, creation of web pages using HTML. A history of the technologies appeared upon development of internet and an overview of the mentioned technologies together with the methods of utilization of these technologies for personal and business purposes is provided to the students.
- Öğretmen: Andre Sena
Data mining, which is the study of algorithms and computational paradigms that enable computers to search datasets for patterns and regularities and make predictions and forecasts is covered in this course. Knowledge discovery is introduced comprehensively. The course explores data selection, cleaning, coding, the application of various statistical and machine learning approaches, and visualization of the resulting structures, which are all steps in knowledge discovery. Students who successfully complete this course are supposed to learn about several data mining techniques, including classification, rule-based learning, decision trees, and association rules. Additionally, students are expected to learn about selection and cleaning of data, machine learning methods for "learning" about "hidden" patterns in data, and reporting and visualizing the resulting knowledge.
- Öğretmen: Yasemin Bay
- Öğretmen: Kian Jazayeri
This course covers the algorithmic techniques and approaches required to handle various types of structured, semi-structured and unstructured data. The goal of the course is to teach algorithmic methods that serve as the cornerstones for handling and analyzing large datasets in a variety of formats. The course specifically covers how to pre-process big datasets, store big datasets effectively, design quick algorithms for big datasets, and evaluate the performance of designed algorithms. Algorithms for sorting, searching and matching as well as graph and streaming algorithms will be introduced. Upon completion of this course, students will have a broad knowledge of different algorithms for pre-processing, organizing, manipulating and storing different data types. Students will also be able to carry out performance analysis of each algorithm.