Below are upcoming training opportunities for the fall that may be of interest to faculty and students. Most sessions are online and free of charge.
REGISTER: https://www.ace-net.ca/training/

Introduction to Computational Thinking
7 October, 1300-1600hrs NL (in-person, Memorial University)
9 October, 0900-1200hrs Atlantic (in-person, Dalhousie University)
Note that there is no online option.
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.

Machine Learning Foundations
14, 15, 16 October, 0900-1730hrs Atlantic (In-person, Dalhousie University)
Note that there is no online option and space is limited to 30 participants.
Machine learning and AI technologies are transforming science, but knowing how to get started can feel overwhelming. This intensive 3-day hands-on workshop offered by the Canadian Bioinformatics Workshops through bioinformatics.ca introduces foundational concepts and methods of machine learning with practical examples and exercises. You will gain experience in: applications and limitations of machine learning and deep learning; decision trees and random forests; artificial neural networks (ANNs); fundamentals of clustering as an unsupervised machine learning method; machine learning operations principles; and, applying these machine learning techniques for biomarker discovery, secondary structure prediction and more. This workshop targets biologists and other life scientists.

Microcredential in Practical Foundations for Data Analytics
20 October to 10 November, Tuesdays and Thursdays, 1400-1700hrs Atlantic | 1430-1730hrs NL (online)
Note that space is limited and participants must submit an application.
This microcredential provides a comprehensive introduction to the essential tools and techniques required for modern computational data analysis. The program combines classroom and self-study learning to build foundational skills in Linux, Python, version control with Git, cybersecurity, and high performance computing (HPC). Participants gain hands-on experience with essential computational tools and methods and develop practical skills. Whether you are beginning to integrate computational tools into your workflow or seek to expand your knowledge, this microcredential offers a structured pathway to becoming proficient in key areas of data analytics. Participants need basic math skills and intermediate experience with computers, including working with documents and spreadsheets.

Using Spreadsheets to Organize Data
28 October, 1300-1600hrs Atlantic | 1330-1630hrs NL (online)
We use spreadsheet programs for entering, organizing, subsetting, and sorting data, for generating statistics and plots, and more. This course shows you some best practices that will result in fewer mistakes, greater reproducibility, and easier use of other software tools with data exported from spreadsheets. Learn how to: decide whether a spreadsheet or a database is the more suitable tool for a project; reorganize and reformat a spreadsheet to avoid common problems; parse and format dates using spreadsheet functions; detect and correct some kinds of data errors in spreadsheets; export spreadsheet data in portable formats; and, use a pivot table to summarize data in different ways. Participants should be comfortable using a computer and navigating files and folders. No prior programming experience is necessary.