Beyond the Classroom: Data Science
Key Resources
Academic Advisors
Visit the NatSci Advising page for contact information and instructions for scheduling an appointment
Department Website
Visit the department website for important updates and information
Major Requirements
Visit the Office of the Registrar's website for detailed information about requirements
Students learn the skills to program, communicate with colleagues, and present information as a data scientist. Students gain strong foundations in mathematics, probability and statistics, R programming, Python programming, and C++ programming, as well as in algorithm development and data visualization.
Skills and Competencies
- Computational Proficiency – Master programming in R, Python, and C++, and develop algorithms. Apply mathematical and statistical methods to analyze data
- Data Analysis & Visualization – Use statistical techniques and data visualization to interpret and present complex datasets, making insights actionable for various audiences
- Interdisciplinary Communication – Communicate technical findings effectively to diverse audiences and
collaborate across disciplines to solve problems
This Major Could Be For You If:
- You are interested in learning about mathematical and statistical techniques for analyzing large datasets
- You are excited about applying data-driven insights to real-world challenges and interdisciplinary projects
- You want to learn about programming and working with computational tools in languages like R, Python, and C++
Common Questions
What is data science?
Data science involves using computational techniques and statistical methods to analyze and interpret complex data. It's important because it helps organizations make data-driven decisions, uncover insights, and solve real-world problems across various industries, from healthcare to finance.
What makes this major unique?
This major is unique because the curriculum integrates advanced computational techniques, statistical analysis, and data visualization. It combines mathematics and programming with hands-on experience in data science methods, preparing students to tackle complex data challenges in various fields.
Skill Development
Building your skills takes exploration and experience. These opportunities below are options you may be interested in. These are ideas to get you started; you have the freedom to find what aligns with your goals.
Research Opportunities
- Consider faculty-directed research or off-campus summer programs
- Connect with the Undergraduate Research Office for assistance
Work-Based Learning
- Develop professional skills through on- or off- campus work or internships with the help of the Career Services Network
- Gain experience through volunteer work via the Center for Community Engaged Learning
Career Growth
- Engage with NatSci’s Career Exploration workshops and resources
Campus Involvement
- Connect with other students in clubs like the plethora of Data Science Student Clubs & Organizations
Education Abroad Ideas
University of New South Wales
- 12-15 weeks | Fall/Spring
- Direct Enroll
Arcadia Research Abroad (Various Locations)
- 6-8 weeks | Summer
- Direct Enroll
To get started with Education Abroad and to explore other programs that suit your goals, check out the MSU Education Abroad website or visit the Education Abroad Advising Center.
Career Exploration
Career exploration is all about discovering the paths that align with your interests, personality, lifestyle, values and skills. Remember, your major doesn’t define your career, and the career cluster examples provided are just a starting point—not an exhaustive list. Explore widely, and keep an open mind as you shape your future!
Data Analysis & Business Intelligence
Careers
- Data Analyst
- Business Intelligence Analyst
- Data Visualization Specialist
- Market Research Analyst
Key Employers
- Technology companies
- Financial institutions
- Retail corporations
- Consulting firms
- Healthcare organizations
- Government agencies
Strategies
- Develop proficiency in data visualization tools such as Tableau or Power BI
- Gain experience with data analysis software and programming languages like R and Python
- Join relevant student organizations or clubs focused on data science and analytics
- Consider coursework in business and economics to understand industry-specific data applications
Machine Learning & Artificial Intelligence
Careers
- Machine Learning Engineer
- AI Research Scientist
- Data Scientist
- Robotics Engineer
- Computer Vision Engineer
Key Employers
- Technology companies
- Research institutions
- AI startups
- Healthcare technology firms
- Automotive companies
- Financial services firms
Strategies
- Build a strong foundation in machine learning algorithms and techniques
- Engage in hands-on projects and contribute to open-source machine learning initiatives.
- Take advanced courses in artificial intelligence and deep learning
- Participate in hackathons or coding competitions to apply your skills
Data Engineering & Infrastructure
Careers
- Data Engineer
- Database Administrator
- Data Architect
- ETL Developer
- Big Data Engineer
Key Employers
- Cloud service providers
- Tech companies with large-scale data operations
- Financial institutions
- Telecommunications companies
- E-commerce platforms
- Government data agencies
Strategies
- Gain experience with database management systems and data warehousing solutions
- Develop strong programming skills in languages used for data
engineering, such as SQL and Python
Looking for more options?