Academic
Records
provider: univ_maryland
architecture: computer_science
query_time: 0.02ms
Operating Systems
//Design and implementation of Operating Systems, i.e. The Ground Truth.
Computer and Network Security
//Introduction to software security, network security, web security, cryptography, and several types of attacks and defenses
High Performance Computing
//Introduction to parallel computing, parallel architectures and networks, distributed memory programming (MPI), shared-memory programming (OpenMP) and GPU programming (CUDA).
Computer Networks
//Introduction to Internet architecture, HTTP, DNS, P2P, Sockets, TCP/IP, BGP, Routing protocols, wireless and sensor networking, WiFi, cellular and satellite networks, and security.
Software Engineering
//State-of-the-art techniques in software design and development. The development of a capstone software project.
Distributed Systems & Cloud Computing
//Exploration of cloud and distributed systems, including IaaS (e.g., Open Stack, Kubernetes), key big data platforms (e.g., Apache Spark, Ceph), data center networking (e.g., DCTCP, Fat-Tree), and ML-Systems (e.g., vLLM, SGLang).
Multimodal Deep Learning
//Introduction to fundamental concepts of key modalities and algorithms for multimodal representation learning, alignment, and fusion.
Advanced Cloud & ML-Systems
//Graduate seminar on large-scale ML systems, covering distributed training, LLM serving, speculative decoding, RLHF, and modern ML infrastructure.
Large Language Models in Engineering AI
//Foundations and frontiers of Large Language Models (LLMs) and extensions like Vision-Language Models (VLMs), exploring the full LLM pipeline—from training to deployment.
Cloud Computing
//In-depth exploration of the fundamentals of cloud computing, its architecture, deployment models, and various services offered by major cloud providers with a focus on AWS training.