Instiq

2Collaborating within and across teams to manage data and models

Practice questions →Glossary →
  • 2.1Exploring and preprocessing organization-wide data

    Understand exploring organization-wide data (Cloud Storage, BigQuery, Spanner, Cloud SQL, Apache Spark, Apache Hadoop), organizing data types (tabular/text/speech/image/video), managing datasets in Vertex AI, preprocessing (Dataflow, TensorFlow Extended [TFX], BigQuery), creating/consolidating features in Vertex AI Feature Store, privacy of data usage (PII/PHI), and ingesting data into Vertex AI for inference.

  • 2.2Notebooks and experiment tracking

    Understand choosing the Jupyter backend on Google Cloud (Vertex AI Workbench, Colab Enterprise, notebooks on Dataproc), security best practices in Vertex AI Workbench, Spark kernels, code-repository integration, developing with frameworks (TensorFlow/PyTorch/sklearn/Spark/JAX), leveraging foundation/open-source models in Model Garden, tracking ML experiments (Vertex AI Experiments, Kubeflow Pipelines, Vertex AI TensorBoard), and evaluating generative AI solutions.