595.758.81 - Data Science for the Technical Leader

Engineering Management
Fall 2024

Description

The course provides an immersive introduction to data science for scientists and engineers who are in technical leadership positions and recognize the need to lead their organizations into a data-driven future. Through lectures, hands-on exercises, and project assignments, the course illustrates the fundamental concepts of data science and introduces the students to the skills required to apply the tools and techniques through the data science process to problems in support of fulfilling mission objectives. The course exposes the students to data management, data science tools and techniques, the basics of Artificial Intelligence (AI) and Machine Learning (ML), creating and delivering data-driven solutions, evaluating their efficacy, policy, and ethical considerations. Familiarity with desktop operating systems and software is required for this course. While students will perform hands-on coding exercises, only basic familiarity with software coding concepts is required.

Instructors

Profile photo of Michael Kramer.

Michael Kramer

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Matthew Dinmore

Course Structure

The course materials are divided into modules which can be accessed by clicking Modules on the course menu. A module will have several sections including the overview, content, readings, discussions, and assignments. You are encouraged to preview all sections of the module before starting. Modules run for 7 days You should regularly check the Calendar and Announcements for assignment due dates; some modules may have multiple parts due on different days, and a few modules allow for more than one week to complete portions of the assignment.

Course Topics

Course Goals

Textbooks


There is no required single textbook for this course, due to the diversity of topics and the survey nature of the course. Throughout the course, students will be assigned to read almost all the sections of the book "Data Science" by Kelleher and Tierney, 2018, MIT Press (237 pages). A link to specific sections will be provided with each reading assignment.
This book is available as an e-book through the JHU library at: Kelleher J.D., & Tierney, B. (2018). Data science. MIT Press [https://catalyst.library.jhu.edu/catalog/bib_7262400.]
It is also available for purchase at Amazon for usually under $10, here: Amazon.  

Articles are available at provided links in the reading assignments. Some of these links connect you with Oreilly Online, which you should have access to through your JHU library privileges.
If you have trouble accessing an article please first try the "eReserves" menu item from the left menu, and then contact the instructors for assistance. 
There is one reference - Toomey - which is available as a PDF on the ereserves link. 

Student Coursework Requirements

Students are expected to complete each module in order. Some modules have an assignment or a project, a discussion, and a self-check quiz.

The final grade is weighted as follows:

Note: self-check quizzes do not count toward the grade, but are required.

Grading Policy

Most assignments include a rubric with the following structure: 95% of the grade is focused on demonstrating understanding of the content, and an additional 5% goes toward demonstration of deeper insights and applications of the content, and effective integration with other course topics.



Course Evaluation

A final project team evaluation form will be provided in Module 14. The submission of this form is mandatory for completion of the course.
There will also be opportunities provided by the school to offer course feedback; we regularly review these and have incorporated many suggestions, which has helped us continually improve the course.

 

Course Policies

Assignment Timeliness of Submission Policy:

This course is designed as an immersive experience, with both passive learning and active learning modalities. Students are expected to participate in a timely manner, particularly as both discussions and group work depend on everyone being involved. As such, late submissions will be graded as follows:

After 1 week due date – 25% reduction in earned credit*

After 2 weeks – 50% reduction in earned credit

After 3 weeks late – 75% reduction in earned credit

After 4 weeks  - No assignment credit

We recognize that students may encounter unexpected and extenuating circumstances. Students are encouraged to contact the professors as soon as possible in these cases to request an extension.

* Earned credit means the reduction is applied after grading to whatever grade was earned for the work.

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.