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M.S. in Artificial Intelligence
Vermillion, South Dakota
INTAKE: Jan & Aug
Program Overview
The M.S. in AI at USD is a deep dive into the development and application of AI-driven tools for various purposes, including machine vision/robotics, machine learning for big data, data analytics, the Internet of Things (IoT), and information retrieval. The program emphasizes a strong foundation in critical thought, reasoning, and ethics, ensuring that AI technologies are developed and deployed responsibly. It is designed to prepare graduates for leadership roles in AI research, development, and application across diverse industries, such as business, finance, healthcare, and computational sciences. The program generally requires 30 credit hours and offers both thesis and non-thesis tracks, providing flexibility for students with different career aspirations.
Curriculum: The curriculum offers an advanced exploration of AI, encompassing core foundations in computer science, mathematics, and statistics, as well as contemporary AI models and frameworks. Key areas of study include machine learning, computer vision, intelligent systems, robotics, agent-based systems, knowledge discovery, and data mining. Students gain expertise in leveraging high-performance computing for AI applications. The program aims to develop the skills necessary for designing and implementing practical AI solutions, with courses exploring how AI can be used in data analytics with machine learning models, computational chemistry, physics, business, finance, and health sciences.
Research Focus: USD's Computer Science Department has a strong research focus in AI, with faculty actively contributing to scholarship in algorithms, artificial intelligence, machine vision, machine learning, pattern recognition, data science, information retrieval, Internet of Things, cybersecurity, and big data. Graduate students are encouraged to actively pursue unique research and present their findings at local and national conferences. The university also hosts initiatives like the Artificial Intelligence Symposium, which brings together AI and data engineering experts from academia, industry, and government to collaborate on solving complex problems. This research-intensive environment ensures that the curriculum is informed by cutting-edge advancements and provides students with opportunities to engage in impactful research.
Industry Engagement: The University of South Dakota emphasizes preparing graduates for the workforce by collaborating closely with industry and government stakeholders. The M.S. in AI program is designed to meet market needs, with faculty members often possessing real-world industry experience. While specific formalized partnerships solely for the AI program are not extensively detailed, the broader university and the Computer Science Department aim to provide practical, hands-on experience. This includes leveraging the university's high-performance computing center for coursework and projects. The program's focus on developing "trustworthy AI" also highlights its commitment to ethical and responsible AI deployment, a critical aspect valued by industries.
Global Perspective: The M.S. in Artificial Intelligence at USD inherently adopts a global perspective due to the universal applicability and transformative nature of AI across all sectors of the global economy. The program prepares students to become leaders in an expanding field with global implications. The curriculum's emphasis on critical thinking, reasoning, and ethics ensures that graduates are prepared to develop and deploy AI technologies responsibly on a global scale. The demand for AI and machine learning specialists is projected to grow significantly worldwide, making this program highly relevant for international career opportunities. USD's commitment to a strong foundation in liberal arts further prepares students to consider the broader societal impacts of AI, which is crucial in a globally interconnected world.
Location
Vermillion, South Dakota
Score
IELTS 6.5
Tuition Fee
USD 12800
Postgraduate Entry Requirements
Application Fee: $38
Academic Qualifications: Applicants for postgraduate programs typically require a minimum academic achievement of 70% or above in their bachelor's degree.
English Language Proficiency:
- IELTS: Overall band score of 6.5 or 7.0 with a minimum of 6.0 in each component.
- TOEFL: Overall score of 79 or higher.
- PTE: Overall score of 53 or higher.
- DET (Duolingo English Test): Minimum score of 110.
The University of South Dakota (USD) offers a variety of scholarship opportunities specifically designed to support international students in achieving their academic goals. These scholarships help reduce the financial burden of studying abroad and make quality education at USD more accessible to talented students from around the world.
Merit-Based Scholarships: USD awards merit-based scholarships to international students based on their academic achievements, leadership potential, and extracurricular involvement. These scholarships recognize outstanding high school or previous college performance and are renewable for multiple years, provided students maintain satisfactory academic progress.
International Student Academic Scholarships: These scholarships are specifically tailored for international undergraduate students and can cover a significant portion of tuition fees. Eligibility is typically based on a combination of academic excellence and the completion of the admission process by specified deadlines. Many of these scholarships are automatically considered upon application, so no separate application is required.
Graduate Assistantships and Fellowships: For international graduate students, USD provides graduate assistantships and fellowships that offer financial support alongside valuable professional experience. These opportunities often include tuition waivers and a stipend in exchange for research, teaching, or administrative work within the university.
Departmental Scholarships: Certain USD academic departments and colleges offer specialized scholarships for international students pursuing specific fields of study, such as business, health sciences, or fine arts. These scholarships often reward exceptional talent and dedication within those disciplines.
Graduates with an M.S. in Artificial Intelligence (AI) from the University of South Dakota (USD) are highly prepared to enter a rapidly expanding job market. The program's emphasis on both theoretical foundations and practical applications in areas like machine learning, computer vision, and data science equips them for diverse and cutting-edge roles across numerous industries. The demand for AI professionals is projected to grow significantly, with roles like AI engineer and machine learning engineer being particularly sought after.
AI Engineer: This is a core role where graduates design, develop, and deploy AI models and systems. They work on building the tools and infrastructure that enable AI applications, focusing on areas like machine learning, deep learning, and natural language processing.
Machine Learning Engineer: Specializing in machine learning, these engineers build, train, and deploy machine learning models. They are responsible for optimizing algorithms, conducting experiments, and ensuring the reliability and scalability of AI systems.
Data Scientist: Data Scientists leverage AI and machine learning techniques to analyze complex datasets, identify patterns, and extract actionable insights. They develop predictive models and use statistical methods to solve business problems and inform strategic decisions across various sectors like finance, healthcare, and marketing.
AI Research Scientist: For those interested in advancing the field, AI Research Scientists focus on developing new AI methods, algorithms, and theoretical frameworks. This role often involves extensive research, experimentation, and publication of findings, and may require a Ph.D. for senior positions.
Computer Vision Engineer: Specializing in AI systems that interpret visual data, Computer Vision Engineers develop applications for facial recognition, object detection, image processing, and augmented reality. They are crucial in fields like autonomous vehicles, security, and healthcare imaging.
Natural Language Processing (NLP) Specialist/Engineer: NLP specialists build AI systems that can understand, interpret, and generate human language. This includes developing chatbots, virtual assistants, language translation tools, and text analytics platforms.
Robotics Engineer: Combining AI with mechanical and electrical engineering, Robotics Engineers design, build, and program robots to perform various tasks. Their work spans industrial automation, healthcare (surgical robots), and autonomous systems.
AI Software Developer: These professionals focus on developing software applications that integrate AI functionalities. They blend traditional software engineering skills with AI expertise to create intelligent systems for various purposes.
AI Ethics Specialist: As AI becomes more pervasive, the need for ethical development and deployment is critical. AI Ethics Specialists ensure that AI technologies are developed and used responsibly, adhering to ethical guidelines, legal frameworks, and societal values, addressing issues like bias and fairness.
Big Data Engineer: While not purely AI, Big Data Engineers are crucial for AI initiatives. They design and build robust data pipelines and systems that collect, manage, and transform raw data into usable formats for AI models. Their work ensures that AI engineers and data scientists have access to clean and organized data for training and analysis.
