Overview
Machine Learning, Artificial Intelligence, Big Data, Data Mining, Neural Networks, Generative Models (ChatGPT) are all a part of Data Science.
Data Scientists don't just learn how to use Machine Learning and Artificial Intelligence tools, they build the models and solve problems by building their own tools.
The Masters in Science in Computer Science: Data Science (Machine Learning and Artificial Intelligence) Program is a STEM-designated program designed to equip students with the skills and knowledge necessary to analyze, interpret, and manage complex data. Students will gain expertise in statistical analysis, machine learning, artificial intelligence, programming and data management, preparing them for a wide range of careers in industries where data-driven decision-making is essential. This is a technical degree, you will learn to write the code, build the models and do a deep dive into Data Science.
Career Opportunities
Due to the rise of tools like ChatGPT, Gemini, CoPilot and others Data Scientist have been in high demand. (). With the demand for data scientists growing across industries, graduates can pursue roles such as Data Scientist, Data Analyst, Machine Learning Engineer, and Business Intelligence Analyst, among others.
Program Objectives
- Core Competencies: Students will learn the principles of data collection, cleaning, and transformation, building foundational skills in programming (Python, R) and statistical techniques.
- Analytical Skills: The curriculum emphasizes critical thinking and analytical skills, enabling students to derive actionable insights from large data sets.
- Model Construction: Students will build their own Machine Learning and AI models to solve problems.
- Ethics & Communication: Courses on data ethics, privacy, and data-driven communication prepare students to navigate the social implications of data science and present findings effectively to stakeholders.
Learning Outcomes
Graduates will be able to:
- Design and implement data analysis workflows.
- Apply machine learning algorithms to solve real-world problems.
- Communicate findings and insights effectively to technical and non-technical audiences.
- Uphold ethical standards in data management and analysis.
Curriculum
Master of Science in Computer Science (33 CH) - Data Science (Machine Learning & Artificial Intelligence)
Core Requirements (21 CH):
- CSCI 5003 Object-Oriented Programming Design & Patterns
- CSCI 5403 Software Engineering
- CSCI 5413 Algorithm Design and Analysis
- CSCI 5603 Database Design
- CSCI 6583 Internship (16 weeks) OR
- CSCI 6883-6 M.S. Degree Project (16 weeks) OR
- CSCI 6983-6 M.S. Degree Research (16 weeks)
- CSCI 5-6xxx CSCI elective outside of chosen track
- CSCI 5-6xxx CSCI elective outside of chosen track
Data Science (12 hours)
- CSCI 6213 Data Science Fundamentals - Introduction to probability and statistical inference used in data science; random variables, sampling distributions, statistical significance, analysis of variance, hypothesis testing, regression, and classification.
- CSCI 6223 Practical Data Science - Hands-on introduction to the complete data science pipeline; Python data acquisition and cleansing, data storage and exploration, missing data treatment, feature engineering, modeling, interpretation, and visualization.
- CSCI 6233 Machine Learning (16 weeks) - Machine learning including Scikit-learn techniques and algorithms; classification and regression modeling, cross validation, hyperparameter tuning, overfitting and underfitting, supervised learning methods (linear models, polynomial regression, regularization, support vector machines, decision trees and random forests) and unsupervised learning algorithms (clustering, density estimation, and anomaly detection).
- CSCI 6243 Artificial Intelligence (16 weeks) - Covers deep learning and neural networks using TensorFlow and Keras: neural network architectures, convolution neural networks for image recognition, recurrent neural networks, natural language processing, autoencoders, generative adversarial networks, and reinforcement learning.
Admission Requirements
- Bachelor’s Degree with a cumulative GPA of 3.00 or above (preference given to applicants with Bachelor's degree in Computer Science or related area, or applicants with significant relevant experience)
- Personal statement and purpose for seeking the degree
- One letter of recommendation from an employer, supervisor, or professor
- Professional resume including academic and professional accomplishments
- Students must provide their own computer/laptop
Transferring from another Masters Program
- Students may transfer up to nine hours from another Computer Science Masters program
- Only grades of a "B" or higher will be transferred
- Need to include an Official transcript when applying to Â鶹´«Ã½
Graduate Admissions can be reached at [email protected] or by calling (405) 208-5351. If you are an International student seeking a visa, please contact [email protected] or 405-208-5358.
Related Programs
The Computer Science department at Â鶹´«Ã½ City University offer several engaging Masters Programs including:
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