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Learning

Graduate coursework in software engineering, cloud computing, and UX/requirements design at CMU — plus self-study in deep learning.

Carnegie Mellon University · 15-319
6 interactive projects →

Cloud Computing

Hands-on projects across AWS, GCP, and Azure — spanning cloud elasticity, container orchestration, distributed Spark batch processing, cloud storage, stream processing, and ML on the cloud.

AWSGCPAzureDockerKubernetesTerraformPythonApache SparkScalaLangChainRAG
Carnegie Mellon University · 18-652
6 interactive iterations →

Foundation of Software Engineering

Six 2-week Scrum iterations building a social network app with a 5-person team — covering OO architecture, design patterns, TDD, code review, and requirements engineering, with features including real-time chat, marketplace, and an OpenAI chatbot.

Node.jsExpress.jsMongoDBSocket.ioJavaScriptOpenAI APIScrumCI/CDTDDDesign Patterns
Carnegie Mellon University · 18-658
5 interactive tasks →

Software Requirements & Interaction Design

Five tasks covering the full UX and requirements engineering process — from needs elicitation and conceptual design through Kano/MAUT envisioning, Figma prototyping, and dual-track agile delivery with heuristic evaluation.

UX ResearchDual-Track AgileUser StoriesPrototypingPersonasFigmaKano ModelUsability TestingRequirements EngineeringDesign Thinking
Self-Study · O'Reilly
6 interactive parts →

Learning Deep Learning

Six parts covering the full deep learning stack — from perceptrons, sigmoid neurons, and backpropagation through CNNs, LSTMs, seq2seq with attention, and the Transformer architecture, applied to NLP translation and image captioning.

TensorFlowPythonNeural NetworksCNNRNNLSTMTransformersNLPBackpropagationAttentionDeep Learning