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X-WR-CALDESC:Events for LFU
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DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260218T120000
DTEND;TZID=UTC:20260218T140000
DTSTAMP:20260521T193351
CREATED:20260216T115228Z
LAST-MODIFIED:20260216T115229Z
UID:52411-1771416000-1771423200@lfu.edu.krd
SUMMARY:پانێڵی رۆژی  جیهانی زمانی دایک
DESCRIPTION:
URL:https://lfu.edu.krd/event/%d9%be%d8%a7%d9%86%db%8e%da%b5%db%8c-%d8%b1%db%86%da%98%db%8c-%d8%ac%db%8c%d9%87%d8%a7%d9%86%db%8c-%d8%b2%d9%85%d8%a7%d9%86%db%8c-%d8%af%d8%a7%db%8c%da%a9/
CATEGORIES:College of Education and Languages
ATTACH;FMTTYPE=image/png:https://lfu.edu.krd/wp-content/uploads/2026/02/Screenshot-2026-02-16-143331.png
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260222T080000
DTEND;TZID=UTC:20260222T170000
DTSTAMP:20260521T193351
CREATED:20260210T093012Z
LAST-MODIFIED:20260210T101105Z
UID:52017-1771747200-1771779600@lfu.edu.krd
SUMMARY:Training :-  Machine Learning Using Python
DESCRIPTION:Proposal for Training on Machine Learning Using PythonTraining Instructor: Dr. Ashish SharmaTotal Sessions: 06Session Duration: 30 – 45 minutes eachMode: Offline mode \n\n\n\n\nIntroductionMachine Learning (ML) has become a core component of modern technology\, enabling systemsto learn from data and make intelligent decisions without explicit programming. From healthcareand finance to education and engineering\, ML applications are transforming industries and creatingnew opportunities.Python is the most widely used programming language for Machine Learning due to its simplicity\,readability\, and powerful ecosystem of libraries such as NumPy\, Pandas\, Matplotlib\, and Scikitlearn. This short-term training program is designed to introduce participants to the fundamentalsof Machine Learning using Python in a concise\, structured\, and practical manner.Given the limited duration of each session (30 – 45 minutes)\, the training focuses on conceptualclarity\, essential algorithms\, and hands-on exposure\, ensuring that learners gain meaningfulunderstanding without being overwhelmed.\n\n\n\nObjectives of the TrainingThe primary objectives of this training program are to:\n\n\n\n\n\nIntroduce the basic concepts and terminology of Machine Learning\n\n\n\nFamiliarize participants with Python as a tool for ML\n\n\n\nExplain different types of Machine Learning techniques\n\n\n\nDemonstrate simple ML workflows using real-world datasets\n\n\n\nEnable participants to understand how ML models are built\, trained\, and evaluated\n\n\n\nBuild confidence to explore advanced ML topics independently after the training\n\n\n\n\n\nExpected OutcomesAfter completing the six-session training\, participants will be able to:\n\n\n\n\nImplement simple Machine Learning models using Scikit-learn \n\n\n\nUnderstand the fundamentals and importance of Machine Learning \n\n\n\nDifferentiate between supervised\, unsupervised\, and basic learning approaches \n\n\n\nUse Python libraries for data handling and visualization \n\n\n\n\nApply foundational ML knowledge to academic\, research\, or practical problem-solvingcontexts\n\n\n\n\n\nTarget AudienceThis training is suitable for:\n\n\n\n\n\nUndergraduate and postgraduate students\n\n\n\nResearch scholars\n\n\n\nFaculty members\n\n\n\nProfessionals from technical and non-technical backgrounds\n\n\n\nAnyone with basic programming knowledge or interest in Machine LearningBasic familiarity with Python is helpful but not mandatory.\n\n\n\n\n\nTraining Structure and Session-wise PlanSession 1: Introduction to Machine LearningContent:\n\n\n\n\n\nWhat is Machine Learning?\n\n\n\nDifference between AI\, ML\, and Data Science\n\n\n\nReal-world applications of ML\n\n\n\nTypes of Machine Learning (Supervised\, Unsupervised\, Reinforcement – overview)Outcome:Participants will gain a clear understanding of what Machine Learning is and where it is used.Session 2: Python for Machine LearningContent:\n\n\n\nWhy Python for Machine Learning?\n\n\n\nOverview of essential libraries: NumPy\, Pandas\, Matplotlib\n\n\n\nWorking with datasets (loading and inspecting data)\n\n\n\nBasic data operations and visualization\n\n\n\n\nOutcome:Participants will be able to handle and explore datasets using Python.Session 3: Data Preprocessing and ExplorationContent: \n\n\n\n\nImportance of data preprocessing\n\n\n\nHandling missing values\n\n\n\nFeature selection and scaling (conceptual overview)\n\n\n\nExploratory Data Analysis (EDA)Outcome:Participants will understand how raw data is prepared for Machine Learning models.Session 4: Supervised Learning – RegressionContent:\n\n\n\nConcept of supervised learning\n\n\n\nIntroduction to regression problems\n\n\n\nLinear Regression: concept and example\n\n\n\nModel training and prediction using Scikit-learnOutcome:Participants will be able to build a basic regression model using Python.Session 5: Supervised Learning – ClassificationContent:\n\n\n\nClassification problems and use cases\n\n\n\nCommon algorithms (Logistic Regression\, KNN – conceptual overview)\n\n\n\nSimple classification example using Scikit-learn\n\n\n\nModel evaluation (accuracy\, confusion matrix – basic idea)Outcome:Participants will understand how classification models work and how their performance ismeasured.\n\n\n\nSession 6: Unsupervised Learning and Conclusion\n\n\n\nContent:\n\n\n\nIntroduction to unsupervised learning\n\n\n\nClustering concepts (K-Means – overview)\n\n\n\nSimple clustering demonstration\n\n\n\nSummary of the complete ML workflow\n\n\n\nCareer paths and next steps in Machine LearningOutcome:Participants will gain exposure to unsupervised learning and understand how to continue learningML.\n\n\n\nTraining Methodology\n\n\n\nShort conceptual explanations\n\n\n\nLive coding demonstrations\n\n\n\nReal-world examples and datasets\n\n\n\nInteractive discussions and Q&A\n\n\n\nStep-by-step explanation of ML workflows\n\n\n\nConclusionThis six-session training program on Machine Learning using Python is designed to provide astrong foundation within a limited time frame. By combining clear explanations with practicaldemonstrations\, the training ensures that participants not only understand the theory but also seehow Machine Learning is applied in practice. Under the guidance of Dr. Ashish Sharma\,participants will be well-prepared to explore advanced Machine Learning concepts andapplications in the future.Proposed by:Asst. Prof. (Dr.) Ashish Sharma\,College of Engineering & Computer Science\,Lebanese French University\, Erbil\, Kurdistan.Training Instructor – Machine Learning using Python
URL:https://lfu.edu.krd/event/training-machine-learning-using-python/
CATEGORIES:College of Engineering and Computer Science
ATTACH;FMTTYPE=image/jpeg:https://lfu.edu.krd/wp-content/uploads/2026/02/poster.jpg
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260222T080000
DTEND;TZID=UTC:20260222T170000
DTSTAMP:20260521T193351
CREATED:20260222T063019Z
LAST-MODIFIED:20260222T063401Z
UID:52603-1771747200-1771779600@lfu.edu.krd
SUMMARY:Nutrition During Fasting: Ramadan and Intermittent Fasting
DESCRIPTION:
URL:https://lfu.edu.krd/event/nutrition-during-fasting-ramadan-and-intermittent-fasting/
CATEGORIES:College of Administration and Economics,College of Health Science
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260224T130000
DTEND;TZID=UTC:20260224T140000
DTSTAMP:20260521T193351
CREATED:20260201T120000Z
LAST-MODIFIED:20260224T083351Z
UID:52816-1771938000-1771941600@lfu.edu.krd
SUMMARY:A National Workshop "Factors influencing the low level of insurance culture in the region.”
DESCRIPTION:
URL:https://lfu.edu.krd/event/a-national-workshop-factors-influencing-the-low-level-of-insurance-culture-in-the-region/
CATEGORIES:College of Administration and Economics
ATTACH;FMTTYPE=image/png:https://lfu.edu.krd/wp-content/uploads/2026/02/A.-L.-Shangar-jamal-workshop.png
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260423T080000
DTEND;TZID=UTC:20260423T170000
DTSTAMP:20260521T193351
CREATED:20260422T101944Z
LAST-MODIFIED:20260422T101944Z
UID:54661-1776931200-1776963600@lfu.edu.krd
SUMMARY:National Workshop: Violence and Loss Of Innocence Psychologic Dimensions in The Novel Lord Of the Files
DESCRIPTION:
URL:https://lfu.edu.krd/event/national-workshop-violence-and-loss-of-innocence-psychologic-dimensions-in-the-novel-lord-of-the-files/
CATEGORIES:College of Engineering and Computer Science
ATTACH;FMTTYPE=image/jpeg:https://lfu.edu.krd/wp-content/uploads/2026/04/mon.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260429T080000
DTEND;TZID=UTC:20260429T170000
DTSTAMP:20260521T193351
CREATED:20260428T111602Z
LAST-MODIFIED:20260428T111603Z
UID:55231-1777449600-1777482000@lfu.edu.krd
SUMMARY:Scientific Activity :ECS Vision  Web EXPO2026
DESCRIPTION:1. Event Overview \n\n\n\nItemDetailsEvent TitleECS Vision  Web EXPO2026DateApril 29\, 2026Time11:00 AM – 3:00 PM (suggested)VenueEngineering & Computer Science College Hall / Exhibition HallOrganizerDepartment of Information Technology / ECS (College of Engineering & Computer Science)Target AudienceUniversity students\, faculty members\, academic staff\, invited guests\n\n\n\n\n\n\n\n2. Event Objectives\n\n\n\n\nShowcase the best student projects completed during the first semester of the academic year 2025–2026.\n\n\n\nHighlight student innovations in Computer Science\, Mechatronics\, and Automation.\n\n\n\nProvide a platform for knowledge exchange between students and faculty.\n\n\n\nDemonstrate the integration of ECS (Engineering & Computer Science) vision with modern web technologies.\n\n\n\nEncourage future interdisciplinary collaboration and project-based learning.\n\n\n\n\n\n\n\n\n3. Exhibition Content Domains\n\n\n\nThe exhibition will feature student work in the following areas: \n\n\n\nDomainExample Project TopicsComputer ScienceWeb applications\, databases\, software engineering projectsComputer EngineeringComputer vison \, Image Processing\n\n\n\n\n\n\n\n4. Opening Ceremony Plan\n\n\n\nTimeActivity11:00 – 11:10Welcome speech by the Head of Department of Information Technology11:10 – 11:20Official opening by the University President and Assistant for Scientific Affairs11:20 – 11:30Ribbon cutting / symbolic inauguration; brief tour of selected exhibits\n\n\n\n\n\n\n\n5. Exhibition Program (11:00 AM – 3:00 PM)\n\n\n\nTimeActivityLocation11:00 – 12:30Open exhibition: Students present their projects to faculty and peersMain Hall 12:30 – 13:00Best Project Award Session – Jury evaluation (3–5 faculty members)Presentation corner 13:00 – 13:30Lunch / refreshment breakLounge area 13:30 – 14:30Panel discussion: “From Semester Projects to Real-World Solutions: ECS Vision & Web Future”Seminar room 14:30 – 14:45Award ceremony for top 3 projects (certificates & prizes)Main stage 14:45 – 15:00Closing remarks by the Dean of the CollegeMain stage \n\n\n\n6. Expected Outcomes\n\n\n\n\nIncreased student motivation through public recognition of their work.\n\n\n\nStrengthened collaboration between Computer Science\, Mechatronics\, and Automation disciplines.\n\n\n\nDemonstration of the ECS vision (innovation\, integration\, real-world readiness) combined with web technologies.\n\n\n\nPositive feedback from faculty and administration for future semesters.
URL:https://lfu.edu.krd/event/scientific-activity-ecs-vision-web-expo2026/
CATEGORIES:College of Engineering and Computer Science
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260504T080000
DTEND;TZID=UTC:20260504T170000
DTSTAMP:20260521T193351
CREATED:20260503T111451Z
LAST-MODIFIED:20260503T111452Z
UID:55373-1777881600-1777914000@lfu.edu.krd
SUMMARY:Sports Activities: Chess
DESCRIPTION:Sports activities in the Department of Information Technology in the College of Engineering and Computer Science\, under the title of (Chess) on (04/05/2026) at (1:00) pm in the building (B3 #) will be held.
URL:https://lfu.edu.krd/event/sports-activities-chess/
CATEGORIES:College of Engineering and Computer Science
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260507T080000
DTEND;TZID=UTC:20260507T170000
DTSTAMP:20260521T193351
CREATED:20260507T054908Z
LAST-MODIFIED:20260507T054909Z
UID:55577-1778140800-1778173200@lfu.edu.krd
SUMMARY:National Workshop: Evidence-Based AI for Researchers
DESCRIPTION:
URL:https://lfu.edu.krd/event/national-workshop-evidence-based-ai-for-researchers/
CATEGORIES:College of Engineering and Computer Science
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