B.S. in Artificial Intelligence

Undergraduate Entry Requirements

Academic Qualifications: Applicants for undergraduate programs typically require a minimum academic achievement of 70% or above in their previous academic qualifications.

English Language Proficiency:

• IELTS: Overall band score of 6.0 with a minimum of 5.5 in each component.
• TOEFL: Overall score of 75 or higher.
• PTE: Overall score of 50 or higher.
• DET (Duolingo English Test): Overall score of 100.

The university offers various scholarships and financial aid options to help ease the financial burden of tuition and make education more accessible. 

International Achievement Scholarship: This scholarship is awarded to outstanding international undergraduate students who demonstrate strong academic achievements. The scholarship amount varies and is typically based on academic merit. Eligibility criteria may include GPA requirements and standardized test scores.

International Transfer Student Scholarship: Designed for international students transferring to LIU Post from another institution, this scholarship recognizes academic achievement at the college level. The scholarship amount may vary based on transfer credits and academic performance.

Global Opportunities Scholarship: LIU Post offers the Global Opportunities Scholarship to international students who have shown a global engagement and cultural diversity. This scholarship may support activities such as study abroad programs or international internships.

Athletic Scholarships: Talented international student-athletes may be eligible for athletic scholarships based on their performance in specific sports. These scholarships can help cover tuition and related expenses.

Private Scholarships: LIU Post encourages international students to explore private scholarship opportunities available from external organizations, foundations, and government programs. These scholarships may have varying eligibility criteria and application deadlines.

Work-Study Programs: International students studying in the United States on certain visa types may be eligible for work-study programs, allowing them to work on campus to help cover educational expenses.

Graduates of the Bachelor of Science in Artificial Intelligence (B.S. in Artificial Intelligence) program at Long Island University Post are well-equipped to pursue a range of exciting and high-demand career paths in the technology sector. The program’s rigorous curriculum and hands-on experience prepare students for roles that leverage artificial intelligence and data science across various industries.

Machine Learning Engineer: Machine Learning Engineers design and implement machine learning models and algorithms to solve complex problems. They work on developing systems that can learn from and make predictions based on data. This role often involves coding, testing, and optimizing algorithms, and it can be found in tech companies, financial institutions, and research organizations.

Data Scientist: Data Scientists analyze large datasets to extract meaningful insights and inform decision-making. They use statistical methods, machine learning, and data visualization tools to interpret complex data and communicate findings to stakeholders. Data Scientists are in high demand across various sectors, including healthcare, finance, and e-commerce.

Artificial Intelligence Researcher: AI Researchers conduct studies and experiments to advance the field of artificial intelligence. They explore new algorithms, techniques, and applications of AI, often working in academic institutions, research labs, or tech companies. This role involves publishing research findings, collaborating with other researchers, and contributing to the development of innovative AI technologies.

Software Engineer: Software Engineers design, develop, and maintain software applications and systems. With a focus on AI, they may work on integrating AI technologies into software solutions, creating intelligent features, and ensuring that applications perform effectively. Software Engineers can be employed in a variety of industries, including technology, finance, and healthcare.

Robotics Engineer: Robotics Engineers develop and design robotic systems and automation technologies. They work on creating robots that can perform tasks autonomously or assist humans in various environments. This role combines knowledge of AI, machine learning, and mechanical engineering, and it is relevant in industries such as manufacturing, healthcare, and defense.

Natural Language Processing (NLP) Specialist: NLP Specialists focus on the development of systems that can understand, interpret, and generate human language. They work on technologies such as chatbots, virtual assistants, and language translation tools. This role is crucial in tech companies, research institutions, and organizations working on AI-driven communication technologies.

Business Intelligence Analyst: Business Intelligence Analysts use AI and data analysis tools to help organizations make informed business decisions. They analyze trends, generate reports, and provide strategic recommendations based on data insights. This role is relevant in industries such as finance, retail, and consulting.

AI Product Manager: AI Product Managers oversee the development and deployment of AI-based products and solutions. They work on defining product requirements, managing development teams, and ensuring that products meet market needs and technical specifications. This role requires a blend of technical knowledge and business acumen.

Cybersecurity Analyst: Cybersecurity Analysts use AI to enhance security measures and protect systems from cyber threats. They analyze security incidents, develop AI-driven security solutions, and implement strategies to safeguard sensitive information. This role is critical in sectors such as finance, government, and technology.

Ethics Consultant for AI: Ethics Consultants for AI focus on the ethical implications of AI technologies and their impact on society. They work on developing guidelines and frameworks to ensure responsible AI practices and address issues such as bias, privacy, and transparency. This role is important in both tech companies and regulatory organizations.