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DTSTART;TZID=Europe/Stockholm:20250909T110000
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DTSTAMP:20260419T004001
CREATED:20250828T065609Z
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UID:37764-1757415600-1757604600@enccs.se
SUMMARY:CodeRefinery Workshop on Coding Tools and Techniques for Reproducible Research [In-person & online]
DESCRIPTION:Register here\n\n\n\n\n\n\nAbout the course\n\n\n\nAre you writing code for your research? Do you want to make your research results more reproducible Do you struggle to reproduce results of your own or others computations? Join the CodeRefinery workshop on coding tools and techniques. \n\n\n\nJoin the CodeRefinery workshop in September and October!It takes place online on 9 half days (you can pick and choose) \n\n\n\n\nWhat: Intro to git and collaborative git\, on githubWhen: 3 days in the second week of September (9+10+11 September 11:00-13:00 + 14:00-15:30 (CEST))\n\n\n\nWhat: Reproducible research\, tools for documentation and testing\, modular code developmentWhen: spread over 6 following weeks Wednesdays starting on 17th of September until the 22nd of October.\n\n\n\n\nThe intended audience for this workshop are researchers of all domains\, levels and preferred programming languages who write code in their research\, and the aim is to improve the reproducibility of our research by deepening the knowledge of the tools that enable better code development and sharing. \n\n\n\nThe workshop is held online (streamed on Twitch) with hands-on sessions. \n\n\n\nThe event is free of charge. More info and registration on the CodeRefinery Workshop site. \n\n\n\nIn-person hybrid event\n\n\n\nIn addition to the option to participate online\, this edition of the workshop also offers limited seats to a local exercise group at KTH library for participants in Sweden for the first 3 days (9+10+11 September). Secure your spots here: \n\n\n\nhttps://www.kth.se/en/👍 biblioteket/kalender/git-github-och-samarbeta-med-kod-coderefinery-workshop-1.1417624 \n\n\n\nDuring the CodeRefinery workshop on coding tools and techniques you will get the opportunity to interact with trainers from ENCCS\, KTH and other partner organizations.Time: Tue 2025-09-09 11.00 – Thu 2025-09-11 15.30 \n\n\n\nLocation: Geisendorf\, KTH Library and/or online  \n\n\n\n\n\n\n\nMore events & contact\n\n\n\nCheck out more upcoming events from ENCCS and our European network at https://enccs.se/events\, as well as our lessons\, suitable also for self-learning. \n\n\n\nFor questions regarding this workshop or general questions about ENNCS training events\, please contact training@enccs.se \n\n\n\nSchedules can change!\n\n\n\nTo ensure that everyone has the opportunity to participate\, we kindly request that you let us know as soon as possible if you are unable to attend an event after registering. \n\n\n\nPlease send us an email at training@enccs.se to cancel your attendance. \n\n\n\nWe understand things can change\, but repeated cancellations without notice may unfortunately result in your name being removed from future event registration lists. \n\n\n\n\n\n\n\nRegulations\n\n\n\nDue to EuroCC2 regulations\, we CAN NOT ACCEPT generic or private email addresses. Please use your official university or company email address for registration. \n\n\n\nThis training is for users who live and work in the European Union or a country associated with Horizon 2020. You can read more about the countries associated with Horizon2020 HERE.
URL:https://enccs.se/events/coderefinery-git-coding-tools-sept-25/
CATEGORIES:ENCCS Event
ATTACH;FMTTYPE=image/jpeg:https://media.enccs.se/2025/08/CodeRefinery-Event.jpg
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DTSTART;TZID=Europe/Stockholm:20250916T090000
DTEND;TZID=Europe/Stockholm:20250918T120000
DTSTAMP:20260419T004001
CREATED:20250609T114149Z
LAST-MODIFIED:20250609T114152Z
UID:37359-1758013200-1758196800@enccs.se
SUMMARY:Practical Machine Learning (Online)
DESCRIPTION:Register here\n\n\n\n\n\n\nOverview\n\n\n\nWelcome to the online workshop on Practical Machine Learning on Sept. 16-18 (2025). Machine learning (ML) is a rapidly growing field within artificial intelligence (AI) that focuses on building systems capable of learning from data. Instead of being explicitly programmed with detailed rules\, the ML models identify patterns and make predictions or decisions based on historical data. This approach has revolutionized many industries\, including healthcare\, finance\, marketing\, and technology\, enabling applications like personalized recommendations\, fraud detection\, and speech recognition. As the volume of data continues to grow\, understanding ML concepts and techniques becomes increasingly important for anyone interested in working with data science or building intelligent systems. \n\n\n\nThis three half-day online workshop is meant to give a comprehensive introduction to the fundamental principles and practical aspects of ML. It will start from the fundamentls of ML including basic concepts\, ML types\, and representative applications of ML\, and then progress to practical techniques for data preprocessing\, model selection\, training\, evaluation\, and assessment. Participants will explore supervised (classification and regression) and unsupervised (clustering and dimensionality reduction) tasks using varied ML algorithms\, such as k-nearest neighbors (KNN)\, linear/logistic regressions\, decision tree\, random forest\, support vector machine (SVM)\, naive bayes\, k-means\, and neuron networks. \n\n\n\nThrough a combination of theory and hands-on exercises using using Python and popular libraries to construct and deploy simple ML models\, attendees will gain a solid foundation in ML\, and then apply ML knowledge in a capstone project\, developing a complete ML pipeline to solve a practical problem. \n\n\n\nWho is this workshop for?\n\n\n\nThis workshop is ideal for: \n\n\n\n\nresearchers and engineers transitioning into applied ML domain with no prior experience\n\n\n\nbeginners in data science or machine learning who want a practical starting point\n\n\n\nsoftware developers and data professionals looking to add machine learning to their skillset\n\n\n\nproduct managers and decision makers who wish to better understand the capabilities and limitations of ML systems in business applications\n\n\n\n\nPrerequisites\n\n\n\nTo ensure a smooth learning experience\, participants should have: \n\n\n\n\nbasic proficiency in Python programming (variables\, loops\, functions) and some libraries like NumPy\, Pandas\, and Matplotlib/Seaborn\n\n\n\nfamiliarity with basic statistics and linear algebra concepts (*e.g.*\, mean\, median\, standard deviation\, vectors\, matrices)\n\n\n\n\nKey Takeaways\n\n\n\nBy the end of the workshop\, participants will: \n\n\n\n\nunderstand the end-to-end ML workflow: problem definition\, data preprocessing\, model training\, evaluation\, and tuning model parameters\n\n\n\nbe able to preprocess data\, including handling missing values and feature scaling\n\n\n\ngain hands-on experience with popular ML algorithms including decision trees\, KNN\, naive bayes\, SVM\, random forest\, and gradient boosting\, etc.\n\n\n\nlearn how to handle real-world datasets\, perform feature engineering\, and avoid common pitfalls such as overfitting\n\n\n\nbe able to use essential Python libraries to build and deploy ML models\n\n\n\nleave with working code examples and the confidence to begin exploring ML/DL in their own projects\n\n\n\n\nTentative Schedule (TBA)\n\n\n\n\nDay 1\, Fundamentals of ML\n\n\n\nDay 2\, Supervised ML\n\n\n\nDay 3\, Unsupervised ML\n\n\n\n\n\n\n\n\nMore events & contact\n\n\n\nCheck out more upcoming events from ENCCS and our European network at https://enccs.se/events\, as well as our lessons\, suitable also for self-learning. \n\n\n\nFor questions regarding this workshop or general questions about ENNCS training events\, please contact training@enccs.se \n\n\n\nSchedules can change!\n\n\n\nTo ensure that everyone has the opportunity to participate\, we kindly request that you let us know as soon as possible if you are unable to attend an event after registering. \n\n\n\nPlease send us an email at training@enccs.se to cancel your attendance. \n\n\n\nWe understand things can change\, but repeated cancellations without notice may unfortunately result in your name being removed from future event registration lists. \n\n\n\n\n\n\n\nRegulations\n\n\n\nDue to EuroCC2 regulations\, we CAN NOT ACCEPT generic or private email addresses. Please use your official university or company email address for registration. \n\n\n\nThis training is for users who live and work in the European Union or a country associated with Horizon 2020. You can read more about the countries associated with Horizon2020 HERE.
URL:https://enccs.se/events/09-2025-practical-machine-learning/
CATEGORIES:ENCCS Event
ATTACH;FMTTYPE=image/webp:https://media.enccs.se/2025/06/practical-machine-learning.webp
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