1. Introduction to Machine Learning Engineer Career Path

• What It Means to Be a Machine Learning Engineer / Roadmap Orientation

• Resource: Machine Learning – Wikipedia

(This page explains the basics of ML, its applications, and the role of ML engineers.)

2. Machine Learning Fundamentals

B. Feature Engineering I: Data Transformations

• Introduction to Feature Engineering

• Resource: Feature Engineering for Machine Learning – Towards Data Science

• Numerical Transformations & Encoding Categorical Variables

• Resource: Kaggle’s Data Cleaning & Feature Engineering Micro-course
• Resource: One-Hot Encoding Explained – Machine Learning Mastery

• Normalization & Data Splitting (Training, Validation, Test)

• Resource: Normalization vs. Standardization – Towards Data Science
• Resource: Train/Test Split for Evaluating ML Algorithms – Machine Learning Mastery

C. Supervised Learning I: Regressors, Classifiers, and Trees

• Linear Regression & Multiple Linear Regression

• Resource: Linear Regression Tutorial – StatQuest (YouTube)

• Ordinary Least Squares to Gradient Descent

• Resource: Gradient Descent Explained – Towards Data Science