There are nine essential skills you should have in order to find, acquire, maintain, and grow within a job.

Essential skills build through majoring in Data Science and Machine Learning include:

• Technology
• Quantitative Reasoning
• Critical Thinking

Click here to learn more about each essential skill.

Students graduating from Data Science and Machine Learning find themselves most often in Aerospace and Defense, Telecommunications, Technology and Software.

Click here to explore career opportunities by major.

Click here to learn more about applying to graduate school.

Major milestones consist of activities students should complete during their first year, middle years and last year at MSU Denver. These milestones will help prospective and current students explore major and career options and create a year-by-year plan to integrate curricular (what happens inside the classroom), co-curricular (what happens inside and outside the classroom, and non-curricular (what happens outside the classroom) experiences. For example, milestones might list specific classes student should take at specific times along their journey or may suggest when students should participate in research opportunities with faculty members.

Simply put, Major Milestones are meant to enhance your student experience and set you up for success.

To use this tool to the fullest, follow these steps

1. Click on your year in school from the list below.
2. Read the steps listed in each category: Cultivate, Engage and Prepare.
3. Complete any necessary steps listed.
4. Check out further resources by connecting with your academic advisor, the Classroom to Career Hub, and your department faculty.

All options listed below are available in-person and online unless noted otherwise.

• Attend orientation and register for classes.
• Meet with your Academic Advisor.
• Complete FAFSA/CASFA/COF and the General Scholarship Application.

• Join a student organization and get connected to support on campus.
• Declare a major, (explore our fully online programs!) or meet with an exploratory advisor to learn about options.
• Attend signature events on campus (Convocation, Fall Fest, Spring Fling, etc.).

• Attend CS and/or MAST Community Events and Seminars.
• Attend a tutoring session or meet 1-1 with a student learning assistant.
• Meet with an instructor (during office hours).

• Join the MSU Denver student chapter of the Association for Computing Machinery (ACM)
• Join women in computing local or national organizations.
• Consider a minor, (explore our fully online programs!) to gain expertise in a field in which you can apply Data Science and/or Machine Learning.

• Meet with your advisor and draft a path to your graduation.
• Learn about areas of specialization within Data Science, Machine Learning, and related fields.
• Learn about faculty-led research projects.

• Consider adding a minor or certificate to your chosen major.
• Explore resources like the tutoring program or the writing center.
• Get familiar with MSU Denver’s Academic Planning Tool.

• Explore student leadership on campus and volunteering in your community.
• Earn credit and gain experience through an internship, study abroad, or community-engaged learning.
• Attend identity or interest-based campus events like the Richard T. Castro speaker series.

• Connect with the Undergraduate Research and Scholarship program.
• Attend an in-person Career Fair to network and secure a professional headshot.
• Connect with the Classroom to Career Hub (C2Hub) for opportunities for professional mentoring and job shadowing.

• Participate in programming events like hackathons and programming competitions.
• Apply for a student assistant position.
• Create study groups with your classmates.

• Visit MSU Denver’s Classroom to Career Hub (C2Hub).
• Build your LinkedIn Portfolio.
• Meet with faculty for career advice.

• Attend job fairs.
• Apply for jobs.
• Organize mock interviews with classmates.

• Meet with your advisor to complete remaining graduation requirements.
• Ready to Graduate? Check out this guide from the registrar!
• Attend or present in-person at a major-specific or industry-specific conference or networking event.

• Attend in-person alumni and campus-wide networking events.
• Submit a proposal to present in-person at the Undergraduate Research Conference.
• Seek to collaborate with local civic organizations.

• Finalize your portfolio of relevant projects and skills.
• Attend in-person career-focused events with an industry-ready resume.
• Identify needs for Professional Certifications or MCAT/LSAT etc. and prepare for professional school admissions.
• Prepare and submit applications for jobs, graduate school, or relevant post-grad training.

• Attend conferences and events in the area of your preference.
• Create study groups on topics of your preference in computer science or technology-related fields.
• Join or create your own open-source machine learning-based software project, or compete in data science competitions like those hosted on Kaggle.

• Reach out to alumni of the program who are making a difference in their community.
• Learn about new AI or technology-related legislation/initiatives that may impact your area of interest.
• Develop a summer program to increase the interest of women in data science and machine learning.

• Attend job fairs.
• Apply for jobs.
• Organize mock interviews with classmates.