ENSF 444 - Machine Learning Systems (Winter 2024)
Undergraduate course, University of Calgary, Department of Electrical and Computer Engineering, 2024
This course offers a comprehensive exploration of data science techniques tailored for engineering contexts. It covers the essential processes of extracting, cleaning, and visualizing data to make informed decisions based on engineering datasets. The course also delves into the fundamental numerical computation techniques that form the foundation of machine learning algorithms. Students will gain a solid understanding of both supervised and unsupervised learning algorithms, crucial for predictive modeling and pattern discovery in data. A significant focus of the course is on the practical application of these concepts, with an emphasis on utilizing existing software libraries and frameworks. This practical approach ensures that students are not only versed in the theoretical aspects of machine learning but also become proficient in applying these techniques to solve real-world problems across various engineering fields. By the end of the course, students will be equipped with the skills to leverage data science in their engineering discipline, enhancing their problem-solving capabilities and opening up new avenues for innovation.