Machine Learning & Python Programming

Instructor for an applied Machine Learning and Python Programming course, October 2023 to April 2024.

Overview

Designed and taught a hands-on curriculum introducing students to programming in Python and the foundations of modern machine learning. The course was structured to take students with limited prior experience to the point of building, training, and evaluating their own predictive models on real datasets.

Responsibilities

• Developed the full course syllabus, lecture materials, coding notebooks, and assessments from the ground up.
• Delivered lectures and live-coding sessions covering Python fundamentals through applied machine learning.
• Created and graded weekly assignments, quizzes, and a capstone project, with individualized feedback.
• Guided students through a complete machine learning workflow, from data cleaning to model deployment-ready code.

Topics Covered

• Python programming: data structures, functions, object-oriented programming, and the scientific stack (NumPy, pandas, Matplotlib).
• Data preprocessing, feature engineering, and exploratory data analysis.
• Core machine learning algorithms: regression, classification, clustering, and an introduction to neural networks.
• Model training, validation, hyperparameter tuning, and performance evaluation with scikit-learn.

Outcomes

Equipped students with practical, portfolio-ready skills in Python and machine learning, enabling them to independently implement and evaluate data-driven solutions.