Course Schedule - Fall Semester 2022

     

RCEL 506 001 (CRN: 14207)

STATS & DATA FOR ENGINEERS

Long Title: APPLIED STATISTICS AND DATA SCIENCE FOR ENGINEERING LEADERS
Department: Center Engineering Leadership
Instructor: Avalos Gauna, Edgar
Meeting: 6:15PM - 9:15PM W SEW 133 (22-AUG-2022 - 2-DEC-2022) 
Session: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
 
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 30
Section Enrolled: 20
Enrollment data as of: 1-MAR-2024 12:01PM
 
Additional Fees: None
 
Final Exam: No Final Exam
 
Description: Data Science has taken the world by storm. Examples of great success can be seen everywhere. This has opened the way for myriad industries and sectors to try to develop their own best practices. Especially since the COVID pandemic, data science, machine learning, artificial intelligence, and other computational technologies have grown rapidly during the past couple of years. However, not everyone knows which, how, when, or why to implement these techniques. Many engineers, for example, oversee or work with daily streams of data and want to use them in the most efficient way possible. The main objective of this course is to provide a comprehensive introduction to statistical and computational methods for modern data problems faced by engineers and engineering managers. By using statistical frameworks and data science as main drivers, the student will survey and compare algorithms for various data applications, learning how to select the most suitable according to real life scenarios. In order to enroll in an online section of this course, you are expected to have a working camera and microphone. During class sessions, you must be able to participate using your microphone and you are expected to have your camera on for the duration of the class so that you are visible to the instructor and other students in the class, just as you would be in an in person class.