Bachelor of Science in Artificial Intelligence: Florida Memorial University

Written By Gideon Gartner

Recommended Program Overview

A four-year undergraduate degree preparing students for careers in AI development, machine learning engineering, and AI research. Total Credits: 120

Core Competencies

  • AI/ML Algorithm Development

  • Deep Learning & Neural Networks

  • Data Science & Analytics

  • Software Engineering

  • AI Ethics & Responsibility

  • Research Methods

Year 1: Foundation (30 credits)

Fall Semester

  • Introduction to Computer Science (4)

  • Calculus I (4)

  • Linear Algebra (4)

  • Introduction to AI & Ethics (3)

  • Academic Writing (3)

Spring Semester

  • Data Structures & Algorithms (4)

  • Calculus II (4)

  • Statistics for AI (4)

  • Python Programming for AI (4)

Year 2: Core Concepts (30 credits)

Fall Semester

  • Machine Learning Fundamentals (4)

  • Probability Theory (3)

  • Database Systems (3)

  • Computer Architecture (3)

  • AI Programming Languages (Java/C++) (3)

Spring Semester

  • Neural Networks & Deep Learning (4)

  • Data Mining & Analysis (4)

  • Operating Systems (3)

  • Discrete Mathematics (3)

  • Technical Communication (3)

Year 3: Advanced Topics (30 credits)

Fall Semester

  • Advanced Machine Learning (4)

  • Natural Language Processing (4)

  • Computer Vision (3)

  • Distributed Computing (3)

  • AI Ethics & Social Impact (3)

Spring Semester

  • Reinforcement Learning (4)

  • Big Data Analytics (3)

  • Cloud Computing for AI (3)

  • Research Methods in AI (3)

  • AI Systems Design (3)

Year 4: Specialization & Application (30 credits)

Fall Semester

  • Deep Learning Architectures (4)

  • AI Project Management (3)

  • Quantum Computing Fundamentals (3)

  • Advanced AI Programming (3)

  • AI Capstone I (3)

Spring Semester

  • AI in Practice (Industry Applications) (3)

  • AI Security & Privacy (3)

  • Emerging AI Technologies (2)

  • AI Capstone II (3)

  • Technical Electives (3)

Technical Electives (Choose 2)

  • Robotics & AI

  • Autonomous Systems

  • Healthcare AI

  • Financial AI

  • Gaming AI

  • Edge Computing

  • AI for IoT

  • Bioinformatics

Required Programming Languages & Tools

  • Python (Primary)

  • Java

  • C++

  • R

  • Julia

  • TensorFlow

  • PyTorch

  • Scikit-learn

  • Git/GitHub

  • Docker

  • Cloud Platforms (AWS/Azure/GCP)

Industry Certifications Integration

  • TensorFlow Developer Certificate

  • AWS Machine Learning Specialty

  • Microsoft Azure AI Engineer

  • Google Cloud Professional Machine Learning Engineer

Research Requirements

  • Mandatory research project in Year 3

  • Capstone project spanning Year 4

  • Publication/presentation encouraged

Internship

Required 8-week minimum industry internship between Year 3 and 4

Learning Outcomes

  1. Design and implement AI systems using current and emerging technologies

  2. Apply mathematical and statistical concepts to solve AI problems

  3. Develop ethical AI solutions considering societal impact

  4. Conduct independent AI research and development

  5. Collaborate effectively in cross-functional technical teams

  6. Adapt to evolving AI technologies and methodologies

Career Paths

  • AI Engineer

  • Machine Learning Engineer

  • Data Scientist

  • AI Research Scientist

  • AI Systems Architect

  • AI Product Manager

  • AI Ethics Officer

  • AI Security Specialist

  • NVIDIA

  • OpenAI

Gideon Gartner https://GartnorGroup.com
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