About This Program
Earn a Master in Data Science at CSUN with our fully online, two year program. Our dynamic curriculum provides students with a foundation in data theory, programming, and engineering through hands-on coursework and real-world skills application.
...Our program reaches beyond the conventional classroom, teaching you to:
- Master both data analytics and data engineering for improved job market potential
- Explore real-word examples from multiple application domains from the data science field
- Build and use data science methods, models, and algorithms to solve real problems
- Learn state-of-the-art programming for data science and analytics with a focus on Python.
The program’s robust curriculum includes lectures, classroom activities, online modules, simulations and a graduate project. Find the course curriculum.
Program Highlights
The U.S. Bureau of Labor Statistics predicts the amount of data science jobs will increase by 34% in the next decade. Our program equips you to excel in programming, data analysis, and optimization, ensuring you’ll remain competitive in the evolving field of data science.
Students develop a project plan and select modeling techniques, generate test designs, and practice data understanding and analytical problem-solving.
Throughout the program, you’ll receive the one-on-one support of a team dedicated to your personal and professional success. Whether it’s enrollment, grading or financial aid, our team of experts will help you stay on track and graduate on time.
On our convenient online platform, you can earn your professional experience and credentials without ever leaving the comfort of your home. This platform allows flexibility for working professionals and students interested in enhancing their careers in the data science field.
Job Outlook: Data Science
About the Master of Science in Data Science Program at CSUN
The CSUN program is designed to equip students with the necessary concepts, techniques, and tools to navigate the complexities of data science. With data volumes continuously increasing, the importance of AI-driven decision-making is paramount. Companies must adapt and employ data science tools and techniques or risk becoming obsolete. Notably, the data analytics market is projected to exceed $300 billion by 2030, according to Yahoo News and Global Newswire.
What do MDS graduates do?
Industries require data scientists to assist in making smarter decisions and creating better products. The role demands a diverse skill set that includes:
- Data analytics
- Data engineering
- Mathematics
- Statistics
- Machine learning
- Other branches of computer science
Additionally, a strong understanding of problem formulation is crucial for engineering effective solutions.
Program learning outcomes:
Upon successful completion of the program, students will have achieved below program educational objectives with respect to Data Science. Specifically, students will:
- Demonstrate competence in programming, analyzing, and optimizing Data Science applications.
- Analyze large datasets in the context of real-world problems using machine learning and statistical inference, obtain actionable insights, and present results using data visualization techniques.
- Identify, assess, and select appropriate data science methods, models, and algorithms for solving real-world problems, weighing their advantages and disadvantages.
- Demonstrate competence in data engineering techniques on data of various sizes and types.
- Analyze, evaluate, and synthesize research, and apply theoretical ideas to practical settings.
- Recognize the need for and show an ability to adapt to the latest data science technologies and continuing professional development.
Student learning outcomes:
- Analyze a complex computing problem and apply principles of computing and other relevant disciplines to identify solutions.
- Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program's discipline.
- Communicate effectively in a variety of professional contexts.
- Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
- Function effectively as a member or leader of a team engaged in activities appropriate to the program's discipline.
- Apply theory, techniques, and tools throughout the data science lifecycle and employ the resulting knowledge to satisfy stakeholders' needs.
