Learner Profiles

Alex — Graduate Researcher in Biology

Alex is a second-year PhD student who trains random forest and XGBoost models on tabular genomics data using scikit-learn on their laptop. Their datasets are growing beyond what fits in RAM, and their advisor has suggested moving to cloud compute. Alex has basic Python skills and has heard of GCP but has never used it. They want to learn how to store data in the cloud, run training jobs without babysitting a notebook, and keep costs under control.

Jordan — Data Scientist at a Research Lab

Jordan has 3 years of experience training deep learning models with PyTorch on a local GPU workstation. They are comfortable with the command line and Git. Their lab has GCP credits and wants to scale up hyperparameter tuning for a new project. Jordan needs to learn how to submit managed training jobs, attach GPUs, and compare tuning trial results without managing infrastructure manually.

Sam — Postdoc Exploring LLMs for Literature Review

Sam is a postdoc in environmental science who wants to use retrieval-augmented generation (RAG) to extract information from research papers. They have intermediate Python skills and have used Jupyter notebooks extensively, but have no cloud experience. Sam is primarily interested in the RAG episode but needs the foundational GCP knowledge from earlier episodes to set up their environment and manage costs responsibly.