ISLR interview,
in this course we will learn about key concepts, models, and techniques from the renowned book "Introduction to Statistical Learning (ISLR)" and how they apply to real-world data science and machine learning interviews. The course will guide you through fundamental topics such as linear and logistic regression, classification techniques, resampling methods, model selection, regularization (Ridge, Lasso), and tree-based methods including decision trees and random forests. You’ll practice interpreting statistical outputs, explaining model assumptions, comparing algorithms, and answering conceptual and practical interview questions based on ISLR chapters. We’ll also tackle hands-on exercises and case studies similar to what top companies use in their hiring process. Whether you're preparing for a data analyst, data scientist, or ML engineer role, this course will help you confidently articulate your understanding of ISLR topics in interviews. Basic statistics and R/Python knowledge recommended. Data School
