This interactive course is an introduction to the world of Machine Learning (ML). It discovers some supervised learning algorithms and discusses when and how to use them. It begins by introducing the data pipeline and its processes, before moving on to statistical and visualization approaches to conduct exploratory and descriptive analytics on data in an effort to answer the question “what happened in the past?”. From there, you will explore the art of data preparation, including data cleaning, missing values, outlier detection, and feature transformation and engineering. Next, we will introduce predictive analytics to answer the question “What will happen in the future?”. We will cover techniques for classifying and predicting data for the supervised learning algorithm, such as k-NN, Naïve Bayes, Decision Tree and Random Forest, and provide guidance in deciding which ones to use. Finally, participants will learn about statistical evaluation methods used in comparing the performance of predictive modelling techniques. This course balances theory and practice. You will use practical concepts of ML applications to understand real-world situations. Topics include Data preparation, ML theory, ML process, ML algorithms, and Model evaluation.

**Important Note: Registration closes on November 5, 2024.

This introductory course offers you a comprehensive introduction to the field of bioinformatics and its applications in analyzing biological big data. You will gain experience utilizing bioinformatics tools and techniques within an HPC environment, including the CAC’s HPC platform, Frontenac, and the other resources available throughout the national compute ecosystem of the Digital Research Alliance of Canada.

By the end of the course, you will have the necessary skills to effectively navigate and analyze biological data using bioinformatics approaches, enabling you to uncover meaningful insights and contribute to advancements in the field of life sciences.

Important Note: Registration closes on October 29, 2024.

Introduction to Parallel Programming with Python using MPI

Parallel programming is key in High Performance Computing. It allows us to run big jobs in a timely manner and leverage a cluster’s resources. In this workshop, you will learn about parallelization, how to write parallel programs, and run them on a parallel system. MPI (Message Passing Interface) will be used in combination with Python.

Important Note: Registration closes on October 25, 2024.

This course provides you with essential knowledge and skills to effectively prepare data for analysis. Starting with an overview of the Data Analytics pipeline and processes, the course explores various statistical and visualization techniques used in Exploratory and Descriptive Analytics to understand historical data. You will then delve into the art of Data Preparation, gaining expertise in data cleaning, handling missing values, detecting and handling outliers, as well as transforming and engineering features.

By the end of the course, you will be equipped with the necessary tools to ensure data quality and integrity, enabling you to make informed decisions and derive valuable insights from their data.

**Important Note: Registration closes on October 24, 2024.

Text mining is the process of extracting meaning, patterns, and trends from unstructured textual data. Massive amounts of unstructured text are prevalent in research. Traditional machine learning algorithms handle only numerical or categorical data. Existing data analytical platforms provide special components to facilitate the analysis of textual data.

This workshop introduces the topic of text mining and provides a tour with hands-on exercises and demonstrations of four text mining tools, each of which supports an interesting and diverse set of features.

**Important Note: Registration closes on October 25, 2024.

This course is designed to provide you with a solid foundation in Python programming language. Through a comprehensive curriculum and hands-on coding exercises, you will learn the fundamentals of Python syntax, data types, functions, and working with data.

By the end of the course, you will have gained the essential skills to write Python programs, solve problems, and build the foundation for more advanced Python development. Whether you are a beginner or have some programming experience, this course will equip you with the necessary tools to start your journey in Python programming.

**Important Note: Registration closes on October 14, 2024.

This course provides you with a foundational understanding of the Linux command line interface. Through a combination of theoretical knowledge and hands-on practical exercises, you will learn essential concepts such as file navigation, command-line operations, file permissions, text editing, and basic scripting.

By the end of the course, you will have the necessary skills to confidently work in a Linux environment and leverage its power for various computing tasks.

**Important Note: Registration closes on October 11, 2024.

What is REDCap?

REDCap is a web-based data capture tool used to create, manage, and deploy research databases and surveys. It has built-in functionalities for data importing and exporting, quality checking, reporting, and basic statistics summarization.

This course will include an overview of the REDCap tool, a demonstration of core features, and hands-on exercises. This course is delivered in 4 parts, 1 hour each.

• October 16, 2024 – Session 1: Introduction to REDCap Forms. This session provides an overview of the lifecycle of a REDCap project and introduces the basics of a REDCap form.
  Registration closes on October 9, 2024.
• October 23, 2024 – Session 2: REDCap Branching Logic and Data Piping. This session focuses on how to write the logic to conditionally show and hide parts of a form and how to use the data piping feature to customize questions by displaying previously collected data in their wording.
  Registration closes on October 16, 2024.
• October 30, 2024 – Session 3: REDCap Longitudinal Studies. This session describes how to utilize the repeatable instruments and events features to set up REDCap projects that require multiple follow-ups over time.
  Registration closes on October 23, 2024.
• November 6, 2024 – Session 4: REDCap Surveys. This session covers how to set up REDCap surveys with automated invitations for follow-ups.
  Registration closes on October 30, 2024.

Registration for each session to close one week prior.