DATA-310-christina.myers-2025-09-24-02-34-45
Professional Development for Data Analytics
Semester and Year [tbd]
Number of Credit Hours 1
Prerequisites DATA 219 or concurrent enrollment if junior standing; admitted to major in Data Analytics.
Course Details
Day and Time: [tbd]
Meeting Location: [tbd]
Instructor Contact Information
Instructor Name: [tbd]
Instructor Contact Information: [office location, phone, email] [tbd]
Instructor Office Hours: [click here for best practices] [tbd]
TA Name: [tbd]
TA Contact Information: [office location, phone, email]: [tbd]
TA Office Hours: [click here for best practices] [tbd]
Course Description
This course is designed to provide data analytics students with professional development opportunities and insight specific to the field, including tools to prepare for seeking internships and post-graduation work. Class sessions will help students gain a deeper understanding of researching prospective internships and work sites that are a fit for their skills sets, while practicing how to communicate and highlight what they can bring to a work setting. The course will include access to professionals in the field, who represent sites that utilize data analysts in a range of work settings, to offer students’ deeper insight into steps needed to prepare for entry into the profession while completing their program. Course content will address work and professional expectations, include guidance and practice to analyze position descriptions and navigate search sites, write data analytics focused resumes, and prepare for interviews.
Course Materials
Books: N/A
Other Materials: N/A
Fees: N/A
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Course Learning Outcomes (students will be able to:) |
Activities Supporting the Learning Outcomes | Assessment of the Learning Outcomes |
|---|---|---|
| Review and search for internships, jobs, and graduate programs that align with their skills and career trajectory. |
Weeks: 1, 2, 4, 6, 10, 12, 13 |
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| Clarify skills and background to effectively highlight the qualifications they bring to a work setting. |
Weeks: 3, 4, 5, 7 |
|
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Engage in conversations with alumni and employers to build networking skills. |
Weeks: 8, 9, 10, 11, 14, 15 |
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Prepare for experiential learning and employment opportunities through a series of preparation activities including resume building, cover letters, and mock interview preparation. |
Ongoing |
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| Dates | Lesson Topic | Assignment |
|---|---|---|
|
Week 1 |
Course introduction Syllabus Quiz |
Submit syllabus quiz |
| Week 2 [dates] |
Deconstructing an Internship/Job Description |
Submission of relevant |
| Week 3 [dates] |
Resume Writing |
Work on resume |
| Week 4 [dates] |
Preparing for Career Fair |
Research career fair attendees |
| Week 5 [dates] |
Cover Letter Writing |
Mock- up cover letter for prospective internship/job site |
| Week 6 [dates] |
Guest Speaker Industry partner (e.g. PNNL) |
Three take-aways |
| Week 7 [dates] |
Best Practices for using LinkedIn |
Work on mockup items for LinkedIn site (does not need to be set up yet) |
| Week 8 [dates] |
Industry Mentor Workshop (Panel of Industry Mentors) |
Attend DA workshop (or identify approved alternative to attend). |
| Week 9 [dates] |
Alumni Sharing Job Search Experience and Recommendations Create elevator speech |
Create elevator speech |
| Week 10 [dates] |
Student interns, traveling for internships, and turning jobs into internships. |
Three take-aways |
| Week 11 [dates] |
Meet with Alumni from Prospective Employer |
Three take-aways |
| Week 12 [dates] |
Best Practices for Applying for Scholarships and the Student Fulbright |
Three take-aways |
| Week 13 [dates] |
Meet with Alumni to Discuss Graduate School |
Three take-aways |
| Week 14 [dates] |
Preparing for Interviews or Mock Interview Session |
Practice Three take-aways |
| Week 15 [dates] |
Guest Speaker from Company hiring DA interns/Alumni |
Three take-aways speakers |
| Alternative topics: Portfolios, GitHub, Study Abroad Opportunities |
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Expectations for Student Effort
Students should expect to spend a minimum of 3 hours per week for each online 1-credit course, engaged in the following types of activities: reading, listening to/viewing media, discussion, or conversation in the LMS or other academic technology, conducting research, completing assignments, and reviewing instructor feedback, studying for and completing assessments, etc.
Grading
| Type of Assignment (tests, papers, etc) | Percent of Overall Grade |
|---|---|
|
Class Participation - completing daily in-class assignments |
70% |
|
Submission of peer review for Resume |
5% |
|
Submission of resume |
5% |
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Submission of Practice cover letter |
5% |
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Submission of three job postings and responses |
5% |
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Participation in out-of-class career development events, e.g. Data Analytics Industry Mentor Workshop, Career Fair event, other department hosted event. |
10% |
|
TOTAL |
100% |
| Grade | |
|---|---|
| Satisfactory | S |
| Fail | F |
Grading Option: DATA 310 is a Satisfactory/Fail course.
Grading policy: Students need to submit all assignments to pass the course.
Attendance and Make-Up Policy
The course is delivered in-person and through videoconference. Students are expected to attend each 50-minute class per week in person or synchronously through videoconference and manage the course/assignment items per the LMS schedule.
Academic Integrity Statement
You are responsible for reading WSU's Academic Integrity Policy, which is based on Washington State law.
Academic integrity is the cornerstone of higher education. As such, all members of the university community share responsibility for maintaining and promoting the principles of integrity in all activities, including academic integrity and honest scholarship. Academic integrity will be strongly enforced in this course. Students who violate WSU’s Academic Integrity Policy (identified in Washington Administrative Code (WAC) 504-26-010(4) will receive an ‘F’ grade in the course, will not have the option to withdraw from the course pending an appeal, and will be reported to the Center for Community Standards.
Cheating includes, but is not limited to, plagiarism and unauthorized collaboration as defined in the Standards of Conduct for Students, WAC 504-26-010(3). Read and understand all of the definitions of cheating. If you have any questions about what is and is not allowed, ask your course instructor.
If you wish to appeal an instructor’s decision relating to academic integrity, please use the form available at communitystandards.wsu.edu. Make sure you submit your appeal within 21 calendar days of the instructor’s decision.
If you have any questions about what you can and cannot do in this course, ask me.
If you want to ask for a change in my decision about academic integrity, use the form at the Center for Community Standards website. You must submit this request within 21 calendar days of the decision.