Interdisciplinary Engineering Courses

Of the following courses, some may be requirements for degree programs, and others may be taken as electives. See your departmental program of study or consult with an adviser for more information.

ENGI E1102x and y The art of engineering
4 pts. Lect: 4. Professor Vallancourt.
Core requirement for all entering SEAS students. This course is a bridge between the science-oriented, high school way of thinking and the engineering point of view. Fundamental concepts of math and science are reviewed and re-framed in an engineering context, with numerous examples of each concept drawn from all disciplines of engineering represented at Columbia. Non-technical issues of importance in professional engineering practice such as ethics, engineering project management, and societal impact are addressed. Lab fee: $350.

ORCA E2500x or y Foundations of data science
3 pts. Lect: 3. Professor Zhang
Prerequisites: Calculus I and II, some familiarity with programming. Designed to provide an introduction to data science for sophomore SEAS majors. Combines three perspectives: inferential thinking, computational thinking, and real-world applications. Given data arising from some realworld phenomenon, how does one analyze that data so as to understand that phenomenon? Teaches critical concepts and skills in computer programming, statistical inference and machine learning, in conjunction with hands-on analysis of real-world datasets such as economic data, document collections, geographical data, and social networks. At least one project will address a problem relevant to New York City.

EEHS E3900y History of telecommunications: from the telegraph to the internet
3 pts. Lect: 3.
Historical development of telecommunications from the telegraphy of the mid-1800s to the Internet at present. Included are the technologies of telephony, radio, and computer communications. The coverage includes both the technologies themselves and the historical events that shaped, and in turn were shaped by, the technologies. The historical development, both the general context and the particular events concerning communications, is presented chronologically. The social needs that elicited new technologies and the consequences of their adoption are examined. Throughout the course, relevant scientific and engineering principles are explained as needed. These include, among others, the concept and effective use of spectrum, multiplexing to improve capacity, digital coding, and networking principles. There are no prerequisites, and no prior scientific or engineering knowledge is required. Engineering students may not count this course as a technical elective.

ENGI W4100y Research to revenue 
3 pts. Lect: 3. Professors Sia and Toubia.
An interschool course with Columbia Business School that trains engineering and business students to identify and pursue innovation opportunities that rely on intellectual property coming out of academic research. Idea generation, market research, product development, and financing. Teams develop and present business model for a technological invention. This course has limited enrollment by application and is open to advanced undergraduate students and graduate students. Consult with department for questions on fulfillment of technical elective requirement.

ORCA E4500x or y Foundations of data science 
3 pts. Lect: 3. Professor Zhang.
Prerequisites: Calculus I and II, some familiarity with programming. Introduction to data science. Perspectives in inferential thinking, computational thinking, real-world applications. Given data arising from some real-world phenomenon, analyze data to understand phenomenon. Critical concepts and skills in computer programming, statistical inference and machine learning, hands-on analysis of real-world datasets, economic data, document collections, geographical data, social networks. Note: for M.S. students only.

ENGI E4990x and y Advanced master's research 
1-6 pts.
Advanced master's research for students within departments that offer master's research specialization. Students may enroll for 1–6 credits per semester, for a maximum of 12 credits required for the master's program. Note: open to students in master's research only.

ENGI E8000 Doctoral Field Work
1 pts. Professor Kachani and Associate Dean Simon
Field work is integral to the academic preparation and professional development of doctoral students. This course provides the academic framework for field work experience required for the student’s program of study. Field work documentation and faculty advisor approval is required prior to registration. A final written report must be submitted. This course will count towards the degree program and cannot be taken for pass/fail credit or audited. With approval from the department chair or the doctoral program director, doctoral students can register for this course at most twice. In rare situations, exceptions may be granted by the Dean's Office to register for the course more than twice (e.g. doctoral students funded by industrial grants who wish to perform doctoral field work for their corporate sponsor). The doctoral student must be registered for this course during the same term as the field work experience.

ENGI E8000x, y, and s Doctoral fieldwork 
1 pts. Professor Kachani
Fieldwork is integral to the academic preparation and professional development of doctoral students. This course provides the academic framework for fieldwork experience required for the student’s program of study. Fieldwork documentation and faculty advisor approval is required prior to registration. A final written report must be submitted. This course will count toward the degree program and cannot be taken for pass/fail credit or audited. With approval from the department chair or the doctoral program director, doctoral students can register for this course at most twice. In rare situations, exceptions may be granted by the Dean's Office to register for the course more than twice (e.g., doctoral students funded by industrial grants who wish to perform doctoral fieldwork for their corporate sponsor). The doctoral student must be registered for this course during the same term as the fieldwork experience.

COSA E9800x and y Data Science Doctoral Seminar
1 pts. Professor Blei.
Prerequisite and Corequisite: Faculty approval. Course required for all Data Science Doctoral students. Others by faculty approval. The Data Science Doctoral Seminar is a 1 credit course that meets weekly. The purpose is to expose the doctoral students to a breadth of ideas in data science across disciplinary domains. The syllabus combines guest lectures from academic data scientists in the greater NYC area and faculty at Columbia, along with a selection of related readings chosen by the guest lecturers. As part of this seminar, students will be expected to engage in active open discussion about the topics and readings covered in class, as well as discuss how such topics apply to their own respective research areas.

For information on courses in other divisions of the University, please consult the bulletins of Columbia College and the Graduate School of Arts and Sciences.