Session Details

Session 1: Machine Learning Introduction and Classification

In this session, we’ll lay the foundation by introducing you to the fundamental concept of machine learning. You’ll gain a clear understanding of the key distinctions between Supervised and Unsupervised learning, setting the stage for our focus on supervised learning. Through a captivating classification example, you’ll dive into the realm of supervised learning, where data is labelled and models are trained to make predictions. We’ll demystify essential concepts like train, validation, and test datasets, crucial pillars of the machine learning workflow. But we won’t stop at theory. Get ready for an immersive hands-on experience! Our demo lab will guide you through the process of splitting data into train and test sets, and you’ll witness firsthand how to train a model using the training set.

By the end of Session 1, you’ll not only grasp the core principles of machine learning but may also find yourself celebrating your first ML model trained right before your eyes

Session 2: Regression and Model Evaluation

We’ll kick off this session with an exploration of Regression, unraveling the mysteries of predicting continuous outcomes. Through a hands-on demo lab, you’ll learn how to train a regression model, equipping you with invaluable skills for real-world data analysis.
But that’s just the beginning. We’ll then shift our focus to the vital process of model evaluation.
Discover the key activities in the iterative lifecycle of ML projects and unravel the intricacies of evaluating a trained model. From understanding various test strategies to mastering the concept of cross-validation, you’ll gain insights that are essential for building robust ML solutions.
In our immersive demo lab, you’ll put theory into practice as you learn how to implement different test strategies and visualize model performance with confusion matrix.

By the end of Session 2, you’ll not only grasp the nuances of regression and model evaluation but will also be empowered to tackle ML projects with confidence and precision.

Session 3: Exploratory Data Analysis and Clustering

Building on our exploration of the ML project lifecycle, this session delves into the essential practice of Exploratory Data Analysis (EDA). Through a compelling case study example, you’ll unravel the mysteries hidden within datasets and uncover valuable insights. Our hands-on demo lab will guide you through the process of visualizing data for exploratory analysis, empowering you to extract meaningful patterns and trends.
But that’s not all. Prepare to venture into the realm of unsupervised learning as we explore the transformative power of clustering. Discover the problems solved by clustering and unlock the potential of unsupervised learning algorithms. In our immersive demo lab, you’ll learn how to cluster data effectively, equipping you with the skills to uncover hidden structures and relationships within your datasets.