MS Data Science
New York, USA
DURATION
2 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
15 Dec 2024
EARLIEST START DATE
Sep 2025
TUITION FEES
USD 1,460 / per credit
STUDY FORMAT
Distance Learning, On-Campus
Introduction
Conduct original research across a vast field with expert faculty and industry professionals. Gain the skills needed to use analytical programming languages, data science tools, and applications. Learn how to create knowledge from data.
The Value Proposition
- Learn the fundamentals of data science, then apply that knowledge through practical exercises and projects that will get you ready to join the tech workforce.
- Work with real data sets to get to grips with the data life cycle in class and innovative labs like the Applied Networking and Data Science Lab.
- Become an essential part of any strategic decision-making team as you learn how to use data to provide insights that can take organizations to the next level.
- You can also complete the MS in Data Science online.
Add Opportunities and Experiences
The capstone project in the MS in Data Science is designed specifically to prepare you for conducting data science tasks in the real world. During the course, you will apply the skills and knowledge gained during your master’s experience to a project involving actual data in a real-world setting. You’ll begin by identifying a problem or opportunity in a real-world domain. You’ll then collect and process data and apply the appropriate analytic methods to find a solution. Both the problem statement and the datasets will come from scenarios similar to those you might encounter in industry, government, or academia. Your final presentation will demonstrate your integration of the knowledge and experience gained over the program and will result in a powerful portfolio piece you can use when applying for data science jobs.
To seriously prepare for a career in data science, you must become familiar with the ethical issues associated with the field. How do we collect data in a way that is ethical and that protects people’s privacy? How does our use of data impact our values as a society, such as what is fair and how accountability should be viewed? What does transparency look like when sensitive information is in the mix? Considering these questions and more will help you understand the power of data, how you can use it, and, importantly, how you should use it.
Admissions
Scholarships and Funding
Pace University offers students as much financial assistance as possible. Financial Aid can come in many forms, including scholarships and grants, work-study, and student loans. Financial Aid award packages offered by Pace University typically consist of a combination of awards from these types of aid programs.
General Rules Covering All Financial Aid
- Any combination of tuition-specific Pace-funded scholarships, grants, or awards and New York State or other tuition-specific funding cannot exceed your actual tuition charges.
- All financial aid combined may not exceed your Cost of Attendance.
- You must be matriculated in a degree program at Pace University to receive any financial aid other than Alternative Loans. (Note that some certificate program students also qualify). Matriculated means that you are admitted to and enrolled in a degree or applicable certificate program.
- Generally, students must be enrolled at least half-time (6 credits per semester) to qualify for aid. Exceptions are Federal Pell Grants and Alternative Loans.
- To review basic eligibility criteria for Pace University, Federal, and New York State aid programs please visit our General Eligibility section.
Pace Scholarships and Resources
- Institutional Scholarships and Grants
- Federal Grants
- New York State Scholarships and Grants
- Third-Party Scholarship Resources
Curriculum
Bridge Courses (Required if no previous background)
- CS 623 Database Management Systems: 3 credits
- CS 661 Python Programming: 3 credits
Core Courses
- CS 660 Mathematical Foundations of Analytics: 3 credits
- CS 673 Scalable Databases: 3 credits
- CS 675 Introduction to Data Science: 3 credits
- CS 619 Data Mining: 3 credits
- CS 677 Machine Learning: 3 credits
- CS 676 Algorithms for Data Science: 3 credits
Data Science Capstone Module
- CS 667 Practical Data Science: 3 credits
- CS 668 Analytics Capstone Project: 3 credits
Electives
- Choose two courses/6 credits with advising consultation: 6 credits
Career Opportunities
Choose Your Career
Data Scientist was the #2 best job in America in Glassdoor’s 2021 listing, with thousands of jobs actively hiring. For several years, the need for data scientists has been growing—and it continues to do so. The world needs data scientists who can collect, maintain, process, analyze, and communicate meaning from datasets. The career options for those with an MS in Data Science are immense.
Career Options for Graduates of This Degree Program
- Data Scientist
- Data Analyst
- Data Engineer
- Machine Learning Engineer
- Quantitative Analyst
English Language Requirements
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