Program Overview

  • Duration

    3-5 Years (Self-Paced) Program

  • Total Courses

    09

  • Total Credit Hours

    54

At University of North Carolina, our Computer Science program equips students with the fundamental principles and advanced skills needed to excel in the dynamic world of computer science. Our curriculum covers a broad spectrum of topics, from algorithms and data structures to artificial intelligence and software development. With a focus on problem-solving and innovation, students embark on a journey to become adept programmers, software architects, and tech visionaries.

Study qualitative and quantitative research, covering research methods and data analysis techniques in a research context. Analyze research design, data collection, and the application of research in various fields.


Learn about preparing a thesis, focusing on the process of thesis development, research planning, and academic writing. Analyze thesis structure, literature review, and the steps involved in thesis preparation.


Explore econometrics, emphasizing the application of statistical and mathematical methods in economic analysis. Analyze regression analysis, econometric models, and their use in economic research.

Work on a short thesis project, conducting independent research and analysis on a selected topic within your field of study. Analyze the chosen topic, conduct research, and present your findings in a concise thesis document.


This program is designed to provide advanced graduate students with the comprehensive skills and knowledge necessary to undertake original research and produce a high-quality doctoral thesis in their chosen field of study.

TUITION

Fees Breakdown Cost
DOCTORATE DEGREE (DCS) $42,120
Medical Insurance $0.00
Personal Expenses $0.00
Study Materials $0.00
Food Cost $0.00
Total Tuition Fee $42,120
WHERE AFFORDABILITY

Meets Opportunity

At the University of North Carolina, we champion the synergy of affordability and opportunity. Our unwavering dedication to accessible education ensures that exceptional learning doesn't come with an exorbitant price. We unlock the gates to knowledge, extending students the opportunity to flourish without the heavy weight of overwhelming tuition costs, empowering them for a brighter, more promising future.

Our Eligibility Criteria

Explore UONC’s Eligibility Criteria for Students Worldwide

Eligibility Criteria

Min. Master's Degree

Credit Hours

54

Course Duration

3-5 Years (Self-Paced) Program

Courses Offered

09

TECHNICAL FOUNDATION AND PROGRAMMING PROFICIENCY:

The College of Computer Science is designed to establish a strong technical foundation and proficiency in programming. Students start by building a solid understanding of computer science fundamentals and gain hands-on experience in coding and software development. This technical base prepares students for a successful career in the ever-evolving world of technology.

INDUSTRY CONNECTIONS AND TECH COMMUNITY INVOLVEMENT:

Beyond the classroom, our Computer Sciences program places a significant emphasis on fostering industry connections and involvement in the tech community. Students have opportunities to participate in hackathons, tech conferences, and internships with leading tech companies. These experiences not only enhance their technical skills but also provide valuable insights into the tech industry.

GLOBAL TECH INNOVATION AND COLLABORATIONS:

The College of Computer Science at University of North Carolina is committed to fostering global tech innovation and promoting collaborative ventures. Our curriculum incorporates international perspectives in technology and encourages students to work on projects with global reach. Additionally, we offer study abroad programs and collaborate with tech professionals from around the world, enabling students to gain a global perspective on computer sciences.

Qualitative And Quantitative Research (PHD-910)

TOPICS COVERED IN THIS COURSE
  In Section 1 of this course you will cover these topics:
     The Process Of Conducting Research
     Quantitative And Qualitative Approaches
     Identifying A Research Problem
     Reviewing The Literature
  In Section 2 of this course you will cover these topics:
     Developing Hypothesis And Research Questions
     Collecting Quantitative Data
     Analyzing And Interpreting Quantitative Data
     Collecting Qualitative Data
  In Section 3 of this course you will cover these topics:
     Analyzing And Interpreting Qualitative Data
     Reporting And Evaluating Research
     Experimental Designs
     Correlational Designs
  In Section 4 of this course you will cover these topics:
     Survey Designs
     Grounded Theory
     Ethnographic Research
  In Section 5 of this course you will cover these topics:
     Narrative Research Designs
     Mixed Methods Designs
     Action Research Designs

Preparing A Thesis (PHD-911)

TOPICS COVERED IN THIS COURSE
  In Section 1 of this course you will cover these topics:
     Thesis Writing: Getting Started
     Discovering Possibilities
  In Section 2 of this course you will cover these topics:
     The Proposal As An Argument: A Genre Approach To The Proposal
     Mapping Text: The Reading/ Writing Connection
  In Section 3 of this course you will cover these topics:
     Writing And Revising
     Writing The Literature Review
  In Section 4 of this course you will cover these topics:
     Using Visual Materials
     The Advisor And Thesis/ Dissertation Committee
  In Section 5 of this course you will cover these topics:
     Working With Grammar And Style
     Practical Considerations

Econometrics (PHD-912)

TOPICS COVERED IN THIS COURSE
  In Section 1 of this course you will cover these topics:
     Economic Questions And Data
     Review Of Probability
     Review Of Statistics
     Linear Regression With One Regressor
  In Section 2 of this course you will cover these topics:
     Regression With A Single Regressor: Hypothesis Tests And Confidence Intervals
     Linear Regression With Multiple Regressors
     Hypothesis Tests And Confidence Intervals In Multiple Regression
     Nonlinear Regression Functions
  In Section 3 of this course you will cover these topics:
     Assessing Studies Based On Multiple Regression
     Regression With Panel Data
     Regression With A Binary Dependent Variable
     Instrumental Variables Regression
  In Section 4 of this course you will cover these topics:
     Experiments And Quasi-Experiments
     Introduction To Time Series Regression And Forecasting
     Estimation Of Dynamic Causal Effects
  In Section 5 of this course you will cover these topics:
     Additional Topics In Time Series Regression
     The Theory Of Linear Regression With One Regressor
     The Theory Of Multiple Regression

Short Thesis

TOPICS COVERED IN THIS COURSE

Detailed Thesis

TOPICS COVERED IN THIS COURSE