The goal of this course is to equip students with the foundational calculus skills necessary for problem-solving in data science and related fields. Upon successful completion of this course, students will be able to: • Compute limits and derivatives to understand the behavior of functions, with an introductory treatment of area approximation. • Analyze and model data using calculus-based methods such as limits, derivatives, and integrals. • Identify and apply appropriate calculus tools to solve applied problems in data science, including optimization, rates of change, curve analysis, and introductory area approximation. Students will utilize these analytical tools to address real-world data science challenges, with applications in fields such as physics, biology, business, economics, and machine learning.

Temps présentiel : 45 heures

Charge de travail étudiant : 150 heures

Méthode(s) d'évaluation : Evaluation - Examen final, Evaluation - Examen partiel, Evaluation - TC