{"id":2174,"date":"2026-01-23T09:07:48","date_gmt":"2026-01-23T14:07:48","guid":{"rendered":"https:\/\/www.ramapo.edu\/dmc\/?p=2174"},"modified":"2026-03-11T19:38:44","modified_gmt":"2026-03-11T23:38:44","slug":"summer-of-ai-2026","status":"publish","type":"post","link":"https:\/\/www.ramapo.edu\/dmc\/2026\/01\/23\/summer-of-ai-2026\/","title":{"rendered":"Summer of AI 2026"},"content":{"rendered":"
Online \u2022 Asynchronous \u2022 12 Transferable Credits<\/strong><\/p>\n Master artificial intelligence, machine learning, and agentic systems in one intensive summer. Three 4-credit courses designed to take you from foundations to building autonomous AI agents\u2014all online and asynchronous.<\/p>\n \u2192 Register for Summer 2026<\/strong><\/a><\/p>\n Session 1 (May 27 \u2013 June 30):<\/strong> <\/p>\n \nSession 2 (July 9 \u2013 August 11):<\/strong> <\/p>\n Take one, two, or all three courses!<\/p>\n Session 1 (May 27 \u2013 June 30) \u2022 4 Credits<\/em><\/p>\n Build the mathematical and algorithmic foundation for modern AI. Implement regression, classification, and neural networks from scratch. Master the complete ML pipeline from data preprocessing to model evaluation and deployment.<\/p>\n Topics include:<\/strong> Linear & Logistic Regression, Decision Trees & Ensembles, Neural Networks & Backpropagation, Support Vector Machines, K-Means Clustering, Dimensionality Reduction (PCA), XGBoost & LightGBM, Deep Learning Foundations, Model Evaluation & Cross-Validation<\/p>\n Session 2 (July 9 \u2013 August 11) \u2022 4 Credits<\/em><\/p>\n Explore the core reasoning and representation techniques of AI. From search algorithms and game-playing to probabilistic reasoning and expert systems. Build intelligent systems that reason, plan, and make decisions under uncertainty.<\/p>\n Topics include:<\/strong> Search Algorithms (BFS, DFS, A*), Adversarial Search & Minimax, Alpha-Beta Pruning, Propositional & Predicate Logic, Bayesian Networks, Fuzzy Logic, Expert Systems, Planning & STRIPS, Knowledge Representation<\/p>\n Session 2 (July 9 \u2013 August 11) \u2022 4 Credits<\/em><\/p>\n The cutting edge of AI engineering.<\/strong> Build autonomous AI agents that perceive, reason, and act. Master LLM integration, tool use, RAG systems, memory architectures, and multi-agent coordination. You’ll build a production-ready coding agent from scratch\u2014then extend it with retrieval, memory, and skills systems.<\/p>\n Topics include:<\/strong> Transformer Architecture & LLMs, Agent Loop Design, Tool Use & Function Calling, Prompt Engineering & Context Engineering, Retrieval-Augmented Generation (RAG), Memory Systems (Conversation, Episodic, Semantic), Multi-Agent Patterns, Model Context Protocol (MCP), LangChain & Framework Evaluation, Guardrails & AI Safety<\/p>\n Ramapo Students:<\/strong> You should have completed CMPS 231 (Data Structures) or CMPS 240 (Programming II). These courses are designed for Computer Science, Data Science, and Cybersecurity majors.<\/p>\n Students from Other Institutions:<\/strong> If you have coursework in programming (Python, Java, C++, or similar), you’re likely prepared. Earn 12 transferable credits applicable to your CS or related major. Contact us with questions about your preparation.<\/p>\n Technical Requirements:<\/strong> Basic programming proficiency is required. Familiarity with Python is helpful but not required\u2014you’ll gain extensive Python experience throughout the sequence. All courses are fully online and asynchronous.<\/p>\n Wondering if this sequence is right for you? Curious about transferring credits or your preparation level? Reach out\u2014we’re happy to help.<\/p>\n Scott Frees, Ph.D.<\/strong>\n
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CMPS 320: Machine Learning<\/h3>\n
CMPS 331: Artificial Intelligence<\/h3>\n
CMPS 367: Agent Engineering<\/a><\/h3>\n
Prerequisites<\/h2>\n
Questions?<\/h2>\n
\nConvenor, Computer Science & Cybersecurity
\nRamapo College of New Jersey
\nsfrees@ramapo.edu<\/a><\/p>\n