Duration: 8 hours
Price: Contact us for pricing.
Prerequisites: Basic knowledge of a standard data science workflow on tabular data. To gain an adequate understanding, we recommend this article.
Knowledge of distributed computing using Dask. To gain an adequate understanding, we recommend the “Get Started” guide from Dask.
Completion of the DLI’s Fundamentals of Accelerated Data Science course or an ability to manipulate data using cuDF and some experience building machine learning models using cuML.
Tools, libraries and frameworks: Python, cuDF, Dask, Plotly, NVTabular, cuML, Forest Inference Library, PyTorch, and NVIDIA Triton™ Inference Server
Assessment Type: Skills-based coding assessments evaluate learners’ ability to train deep learning models on multiple GPUs.
Certificate: Upon successful completion of the assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth..
Hardware Requirements: Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated workstation in the cloud.
Languages: English