GCP Data Engineer Pro: Google Machine Learning and AI

Google Cloud 2024    |    Intermediate
  • 13 videos | 1h 30m 13s
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Over time, humanity has learned from patterns, beginning with recognizing what characteristics indicate poisonous plants versus edible botanicals. In the same way, machine learning (ML) is all about recognizing the patterns in data so useful predictions can be made. In this course, explore ML systems tailored for diverse objectives, integrate ML into a data warehouse environment, different GCP ML products, and prebuilt models. Next, learn how to develop a project with a prebuilt ML model, the rationale for creating new models, and the ML data preparation process. Finally, discover how to create a custom-trained model using the Vertex AI SDK for Python and compare Vertex AI and BigQuery. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline what machine learning (ml) is and is not
    Differentiate machine learning systems that can be used with different goals
    Identify the standard steps associated with incorporating machine learning into a data warehouse process
    List the different products available for leveraging machine learning
    Recognize in which scenarios prebuilt models would meet a business use case
    Create a project that utilizes a prebuilt model for machine learning
  • Outline the use case and purpose of developing new models and the difference between automl and custom model training
    Identify the process and key steps involved in preparing data to be incorporated into machine learning
    Create a custom-trained model using the vertex ai sdk for python
    Differentiate vertex ai from bigquery and describe how vertex ai can be integrated with bigquery workflows
    Recognize common issues that can arise with machine learning and how to troubleshoot them
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 16s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 11m 9s
    Upon completion of this video, you will be able to outline what machine learning (ML) is and is not. FREE ACCESS
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    3.  Machine Learning Algorithms
    10m 5s
    After completing this video, you will be able to differentiate machine learning systems that can be used with different goals. FREE ACCESS
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    4.  The Machine Learning Workflow
    6m 6s
    In this video, we will identify the standard steps associated with incorporating machine learning into a data warehouse process. FREE ACCESS
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    5.  Google Machine Learning Products
    9m 3s
    Upon completion of this video, you will be able to list the different products available for leveraging machine learning. FREE ACCESS
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    6.  Prebuilt Models
    4m 50s
    Through this video, you will be able to recognize in which scenarios prebuilt models would meet a business use case. FREE ACCESS
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    7.  Implementing a Prebuilt Model
    5m 5s
    Discover how to create a project that utilizes a prebuilt model for machine learning. FREE ACCESS
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    8.  Custom Model Training
    9m 11s
    In this video, we will outline the use case and purpose of developing new models and the difference between AutoML and custom model training. FREE ACCESS
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    9.  Data Preparation for Machine Learning
    8m 39s
    After completing this video, you will be able to identify the process and key steps involved in preparing data to be incorporated into machine learning. FREE ACCESS
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    10.  Training a Model Using Vertex AI
    7m 24s
    During this video, discover how to create a custom-trained model using the Vertex AI SDK for Python. FREE ACCESS
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    11.  Machine Learning Options for BigQuery
    6m 58s
    Upon completion of this video, you will be able to differentiate Vertex AI from BigQuery and describe how Vertex AI can be integrated with BigQuery workflows. FREE ACCESS
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    12.  Troubleshooting Issues in Machine Learning
    9m 31s
    Through this video, you will be able to recognize common issues that can arise with machine learning and how to troubleshoot them. FREE ACCESS
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    13.  Course Summary
    58s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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