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Moodle is an open-source Learning Management System (LMS) that provides educators with the tools and features to create and manage online courses. It allows educators to organize course materials, create quizzes and assignments, host discussion forums, and track student progress. Moodle is highly flexible and can be customized to meet the specific needs of different institutions and learning environments.

Moodle supports both synchronous and asynchronous learning environments, enabling educators to host live webinars, video conferences, and chat sessions, as well as providing a variety of tools that support self-paced learning, including videos, interactive quizzes, and discussion forums. The platform also integrates with other tools and systems, such as Google Apps and plagiarism detection software, to provide a seamless learning experience.

Moodle is widely used in educational institutions, including universities, K-12 schools, and corporate training programs. It is well-suited to online and blended learning environments and distance education programs. Additionally, Moodle's accessibility features make it a popular choice for learners with disabilities, ensuring that courses are inclusive and accessible to all learners.

The Moodle community is an active group of users, developers, and educators who contribute to the platform's development and improvement. The community provides support, resources, and documentation for users, as well as a forum for sharing ideas and best practices. Moodle releases regular updates and improvements, ensuring that the platform remains up-to-date with the latest technologies and best practices.

Links of interest:

Moodle docs

Moodle community forums

Moodle release notes

The free Moodle hosting service at Gnomio

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Available courses

Agile Development Methodologies

This comprehensive course provides an in-depth exploration of agile software development methodologies, focusing on their principles, values, and practical applications. By framing agile within the context of the Agile Manifesto, students will gain a solid understanding of its fundamental philosophy while comparing it to traditional software development approaches like Waterfall and Spiral.

Throughout the course, participants will delve into significant agile methodologies, including Scrum, Kanban, eXtreme Programming (XP), Feature-Driven Development (FDD), and Dynamic Systems Development Method (DSDM). Emphasis will be placed on real-world application through agile practices such as user stories, sprints, and ceremonies, including sprint planning and retrospectives.

Students will also investigate emerging trends in agility, such as DevOps and enterprise agility, and contemplate the broader implications of agility beyond software, encompassing business and research contexts. Through hands-on projects and case studies, participants will develop the skills necessary to implement agile practices effectively and pursue innovative research directions in the field.

Teacher: Hussien Seid

Advanced Machine Learning

Teacher: Hussien Seid

Advanced Natural Language Processing

This course covers a broad range of advanced level topics in natural language processing. It is intended for graduate students in computer science who have familiarity with machine learning fundamentals, but may be new to NLP. It may also be appropriate for computationally sophisticated students in linguistics and related areas. Topics include probabilistic models of language, computationally tractable linguistic representations for syntax and semantics, and selected topics in discourse and text mining. After completing the course, students should be able to read and evaluate current NLP research papers.

Teacher: Hussien Seid

Natural Language Processing

Course Description:

The intent of the course is to present a fairly broad graduate-level introduction to Natural Language Processing (NLP, a.k.a. computational linguistics), the study of computing systems that can process, understand, or communicate in human language. The primary focus of the course will be on understanding various NLP tasks as listed on the course syllabus, algorithms for effectively solving these problems, and methods for evaluating their performance. There will be a focus on statistical and neural-network learning algorithms that train on (annotated) text corpora to automatically acquire the knowledge needed to perform the task.

Course Objectives:

Upon successful completion of the course, the student will be able to:

Understand the basic principles and challenges of natural language processing.
Explore the core NLP tasks, such as text preprocessing, language modeling, named entity recognition, and sentiment analysis.
Gain hands-on experience in implementing and applying NLP techniques using popular libraries and frameworks.
Analyze and critically evaluate the performance and limitations of NLP systems.
Understand the ethical considerations and societal implications of NLP technology.

Teacher: Hussien Seid

Software Architecture and Design

This course explores software architecture and design principles, practices, and tools. It emphasizes the use of architectural styles, design patterns, and best practices to build scalable, maintainable, and efficient software systems. Students will engage in case studies, discussions, and hands-on projects to develop practical skills.

By the end of this course, students will be able to:

Understand foundational concepts of software architecture and design.
Analyze and apply a variety of architectural styles and patterns.
Use design principles to create high-quality software systems.
Evaluate and document software architectures effectively.
Tackle complex design challenges through collaboration and creativity.

Teacher: Hussien Seid

Fondations of Software Engineering

This course provides an overview of fundamental principles, methodologies, and tools in software engineering. It explores the foundational principles of software engineering, emphasizing the scientific and engineering concepts essential for research in the field. Students will learn about the software development lifecycle, requirements engineering, software design, testing, and project management They will examine theoretical frameworks, methodologies, and the interplay between software engineering and computer science.
Learning Outcomes