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5
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31770
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Laboratory
Lecture
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JH
JH
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ARRANGED
2:00PM
-3:20PM
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n.a.
TR
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Location Pending
3013 Electrical & Computer Eng Bldg
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Huang, J
Huang, J
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- Availability:
- Closed
- Part of Term:
- 1
- Date Range:
- 08/24/26-12/09/26
- Credit:
- 4 hours
- Section Title:
- AI Systems & Engineering
- Section Info:
- In this course, we focus on teaching students practical system-building skills and toolchains for developing and fine-tuning large language models (LLMs) from scratch. It covers the entire lifecycle of developing an LLM and its enabled applications, including LLM architecture implementation, model training, fine-tuning, inference, and agentic-based applications. Along with the presentation of the entire LLM development lifecycle, we will not only discuss the basic building blocks of foundation models, but also learn the essential computing techniques and engineering skills needed for enabling functionality, efficiency, and scalability. Students will have multiple programming assignments to strengthen their understanding of the basic concepts and practice their systems-building skills. Specifically, the lecture topics will include PyTorch and development tools (software setup), CUDA implementation of tensor operators, AI infrastructure (hardware setup), the basics of foundation models (e.g., tokens, embeddings, attention mechanism, and mixtures of experts), LLM training methods, training parallelisms, data engineering, fine-tuning methods, inference engine development and deployment, prompt engineering, agent development, RAG-based LLM and applications. It is worth noting that this course focuses on exploring problem-solving approaches for LLM development. Due to limited computing resources in academia, some programming assignments of this course may not reach the industrial scale, however, the development approaches are generic. Students will obtain hands-on experience of developing and deploying LLMs throughout this course. Prerequisites: Python programming. Prior exposure to CUDA programming and machine learning will be beneficial."
- Restriction(s):
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Restricted to students with Senior class standing. Restricted to Graduate - Urbana-Champaign or Undergrad - Urbana-Champaign.
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5
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55024
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Lecture
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OS
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11:00AM
-12:20PM
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TR
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3017 Electrical & Computer Eng Bldg
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Levchenko, K
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- Availability:
- Closed
- Part of Term:
- 1
- Date Range:
- 08/24/26-12/09/26
- Credit:
- 3 hours
- Section Title:
- OS Design & Implementation
- Section Info:
- In this course you will further develop your operating system from ECE 391. In particular, in the first half of the course, you will add the following features: a C standard library, user-space threading, multiprocessor support, performance benchmarking, signals and orderly process termination, and advanced virtual memory features (shared memory, memory-mapped files, unified buffer cache). In the second half of the course, you will implement one of: networking, an advanced file system, user and kernel ASLR, complex hardware configuration (USB or PCI), accelerators, dynamic linking, and power management. Prerequisites: ECE 391
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