Core CS & AI Tracks
Tailored instruction for students, software engineers, and researchers seeking mastery in modern computational methods.
Core CS & Software Engineering
Algorithms, Systems & Clean Code
Build rigorous foundations in algorithmic problem solving, memory management, and enterprise software architecture using Python, C++, and Rust.
- Data Structures & Algorithms: Trees, Graphs, Dynamic Programming, and Space/Time Complexity Analysis.
- Object-Oriented & Functional Design: Clean code, design patterns, and modular software architecture.
- Operating Systems & Concurrency: Process scheduling, multithreading, async programming, and memory management.
- System Design Foundations: Scalable web architectures, database indexing (SQL/NoSQL), and API design.
Machine Learning & Generative AI
Deep Learning, LLMs & AI Pipelines
Move beyond theory into building, training, and deploying neural networks and Generative AI solutions using modern frameworks.
- Applied Machine Learning: Regression, Classification, SVMs, Ensemble Methods, and PyTorch/TensorFlow.
- Deep Learning Architecture: CNNs for Computer Vision, RNNs, and Transformer Networks.
- Large Language Models (LLMs): Prompt Engineering, Fine-Tuning (LoRA/QLoRA), and Retrieval-Augmented Generation (RAG).
- MLOps & AI Deployment: Model quantization, ONNX runtime, Docker containerization, and API deployment.
Our Lab Pedagogy
We bridge theoretical computer science with real-world technical execution, ensuring code is written, tested, and deployed in every session.
Code-First Learning
Live pair-programming sessions with direct feedback on performance, readability, and edge-case handling.
Portfolio-Driven Projects
Build custom applications, AI pipelines, or technical papers to showcase in engineering interviews.
Bilingual Tech Mentorship
Technical instruction available in English or Japanese to prepare for global and Tokyo tech roles.