In Defense of LLMsArtificial Neurophilosopher Serdal Tümkaya Return to the main site

Undergraduate Curriculum Draft

Department of Artificial Wisdom, Philosophy, and Cognitive Sciences

An eight-semester programme combining artificial wisdom, agentic AI, philosophy, cognitive sciences, neural networks, cybernetics, robotics, and open science.

Draft status: this is a conceptual curriculum, not an accredited or institution-approved degree programme.

Four-year structure

Eight Semesters, 47 Courses

Courses are presented in their intended semester and order, from the first-year foundations to the final thesis or project.

Year 1

Semester

Year 1 · Fall

5 courses
  1. Introduction to Contemporary Artificial Wisdom, Agentic AI, Autonomous Agents, and Developmental Robotics
  2. The 42,000-Year-Long History of Artificial Wisdom and Robots
  3. Programming for Philosophers: Python and Vibe Coding
  4. Calculus for Artificial Wisdom
  5. Cognitive Fallacies and Reasoning Errors: Low-Argumentation and Vibe-Argumentation
Semester

Year 1 · Spring

6 courses
  1. From Hume to Pragmatism: Empiricism, Naturalism, and Scientific Philosophy
  2. Prompt and System Engineering: Artificial Reading and Writing with Artificial Wisdom II
  3. Programming for Philosophers II: Data, Algorithms, and Objects
  4. Linear Algebra for Artificial Wisdom
  5. Discrete Mathematics and Proof Techniques
  6. Transformers and Large Language Models

Year 2

Semester

Year 2 · Fall

6 courses
  1. Neural Networks and Connectionism: Cognitive Science and Cybernetics
  2. Cognitive Psychology and Cognitive Neuroscience
  3. Data Structures and Algorithms
  4. Probability and Statistics for Artificial Wisdom
  5. The Science of Uncertainty: Probability, Past and Present
  6. Technology Ethics
Semester

Year 2 · Spring

6 courses
  1. Philosophy of Science and Naturalism
  2. Machine Learning I
  3. Databases and Data Management
  4. Computer Systems for Artificial Wisdom
  5. Bayesian Reasoning, Hidden Markov Models, and Probabilistic Programming
  6. Research Methods, Replication, and Open Science

Year 3

Semester

Year 3 · Fall

6 courses
  1. Artificial Wisdom: Principles and Techniques
  2. Machine Learning II: Deep Learning
  3. Natural Language Processing
  4. Philosophy of Language and Computation
  5. Neuroscience: Foundations for Philosophy and Artificial Wisdom
  6. Data Analytics, Text Mining, and Digital Humanities
Semester

Year 3 · Spring

6 courses
  1. Large Language Models and Generative Artificial Wisdom
  2. Computer Vision and Multimodal Perception
  3. Reinforcement Learning and Decision-Making
  4. Philosophy of Artificial Wisdom: Agency, Understanding, and Intentionality
  5. Human–Artificial Wisdom Interaction and Experimental Design
  6. Interdisciplinary Artificial Wisdom Laboratory I

Year 4

Semester

Year 4 · Fall

6 courses
  1. Artificial Wisdom Governance
  2. Discovery and Validation in AI-Driven Science: Causality, Explainability, and Scientific Modeling
  3. Artificial Wisdom + X Elective I (Cognitive Robotics and Neurorobotics)
  4. Artificial Wisdom + X Elective II (Biohybrid Animals and Biohybrid Robotics)
  5. Philosophical Article and Thesis Writing Seminar
  6. Automated Laboratories, Autonomous Research, and Industry Project
Semester

Year 4 · Spring

6 courses
  1. Consciousness, LLMs, and Naturalism: Advanced Seminar
  2. Artificial Wisdom Systems, MLOps, and Model Deployment
  3. Artificial Wisdom + X Elective III (Automation, Dark Factories, and Their Social Impacts)
  4. Artificial Wisdom + X Elective IV (Technology Policy and Democracy)
  5. Artificial Wisdom + X Elective V (History of Philosophy: The Last 5,000 Years)
  6. Graduation Thesis or Project