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SUMMARY:Introduction to Computational Thinking (NL)
DESCRIPTION:Computational thinking is an essential skill for anyone wanting to learn to program computers and write code. This workshop takes you through the steps involved in computational thinking\, learning how to break down complex problems into smaller parts\, identify patterns\, and design logical solutions that a computer can execute. Through hands-on activities\, you practice techniques such as problem decomposition\, abstraction\, and algorithmic thinking. By the end of the session\, you have a stronger foundation for approaching programming tasks with confidence\, setting the stage for future coding and data-driven learning. This session is designed for beginners who are curious about programming but may not know where to start. It’s especially valuable for those exploring computer science or data science for the first time\, or for people in non-technical fields who want to build problem-solving and coding skills.
URL:https://ccdhhn.ca/workshop/introduction-to-computational-thinking-nl/
LOCATION:Memorial University\, St John's\, Newfoundland\, A1C 5S7\, Canada
CATEGORIES:1-4 hour workshop
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SUMMARY:Data Bites - Optimize Directory Structures for Research Data
DESCRIPTION:Workshop: Optimize Directory Structures for Research Data \n\n\n\nThis practical workshop\, delivered by the UBC Library Research Data Management team\, focuses on strategies for organizing research data using clear and logical directory structures. Designed for graduate students\, researchers\, and staff\, the session helps participants manage files more effectively to support collaboration\, reproducibility\, and long-term data stewardship. \n\n\n\nParticipants will learn how to: \n\n\n\n\nDesign directory structures that reflect research workflows and support project organization\n\n\n\nImplement naming and hierarchy conventions for easy navigation and version control\n\n\n\nApply best practices to maintain consistency and clarity throughout the research lifecycle\n\n\n\n\nLocation: ONLINE\n\n\n\n(A zoom link will be sent to registrants 3 hours before event start.) \n\n\n\nPresenter(s):Eugene Barsky\, Vanessa Choy
URL:https://ccdhhn.ca/workshop/data-bites-optimize-directory-structures-for-research-data-6/
CATEGORIES:30 minute workshop
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DTSTAMP:20261002T134419Z
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SUMMARY:Introduction to Machine Learning: Classification and Clustering
DESCRIPTION:October 7th 2026 \n\n\n\nThis workshop offers an exploration of machine learning models for clustering and classification. With the increasing availability of large datasets\, these models play a crucial role in extracting valuable insights and making informed decisions. In this workshop\, participants will gain insight into clustering algorithms such as K-means\, explore popular classification algorithms like decision trees\, and learn about anomaly detection. Through a combination of lectures and hands-on exercises\, participants will learn how to preprocess data\, select relevant features\, and evaluate model performance. By the conclusion of the workshop\, participants will have a solid foundation in building and deploying machine learning models for clustering and classification tasks. \n\n\n\nIn this workshop\, we will use cloud-based platforms\, so you don’t need to have Python installed. Please make sure that you have a Google Colaboratory (https://colab.research.google.com/) account. This workshop will involve hands-on exercises that require the use of programming tools and libraries commonly used in machine learning\, such as Python and Scikit-learn. As such\, prior familiarity with Python programming is recommended for participants to fully benefit from the practical component of the workshop. \n\n\n\nPresenter(s):Kendra Oudyk
URL:https://ccdhhn.ca/workshop/introduction-to-machine-learning-classification-and-clustering-4/
CATEGORIES:1-4 hour workshop
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