Online Course – Certified Professional Internship in Machine Learning on Google Cloud

Learn machine learning on Google Cloud. Real-world experiences with end-to-end ML.

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קורס אונליין - התמחות מקצועית מוסמכת בלמידת מכונה ב-Google Cloud

Professional Certificate

Intermediate level

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Telenorflow
  • Machine learning
  • Feature engineering
  • Cloud Computing
  • Vertex AI

What you will learn in the course

Courses for which the course is suitable

  • Machine learning model developer
  • Data Analyst
  • Data Engineer
  • AutoML expert
  • BigQuery ML Developer
  • Features Engineer
  • Machine Learning Project Manager
  • Google Cloud Solutions Developer
  • TensorFlow expert
  • Model performance analyzer

Internship – Series of 5 courses

What is machine learning, and what problems can it solve?

  • How can you build, train, and launch machine learning models at scale without writing a single line of code?
  • When should you use automated machine learning or personalized training?

What will you learn in the course?

  • Build Vertex AI AutoML models without writing a single line of code.
  • Build BigQuery ML models with basic SQL knowledge.
  • Create custom training jobs in Vertex AI that you can run using containers (with basic Docker knowledge).
  • Use the Feature Store for data management and environmental management.
  • Apply feature engineering to improve models.
  • Determine the appropriate data processing options for your use case.
  • Use VERTEX VIZIER for hyperparameter tuning to incorporate the right mix of parameters that yields accurate and generalized models.
  • Understand the theory for solving specific types of machine learning problems.
  • Write distributed models that scale in TensorFlow.
  • Take advantage of best practices for implementing machine learning on Google Cloud Platform.

Terms of Use

By registering for this internship, you agree to the Qwiklabs Terms of Service as set forth in the FAQ located at: https://qwiklabs.com/terms_of_service .

Hands-on Learning Project

This specialization incorporates hands-on labs using our Qwiklabs platform. These hands-on components will allow you to apply the skills you learned in the video lectures. Projects will include topics such as Google Cloud Platform products, which are used as defined in Qwiklabs. You can expect to gain hands-on experience with the concepts explained throughout the modules.

Details of the courses that make up the specialization

How Google does machine learning

Course 1 • 11 hours • 4.6 (7,260 reviews)

Course Details
  • Explain what the Vertex AI platform is and how it is used to quickly build, train, and launch automated machine learning models, without the need to write code.
  • Describe best practices for implementing machine learning in Google’s cloud.
  • Take advantage of Google Cloud’s tools and environment to perform machine learning.
  • To formulate best practices for responsible AI.

Preparing for machine learning

Course 2 • 14 hours • 4.6 (4,294 reviews)

Course Details
  • Explain how to improve data quality and perform exploratory data analysis.
  • Build and train automated machine learning models using Vertex AI and BigQuery ML.
  • Optimize and evaluate models using loss functions and performance metrics.
  • Create repeatable and scalable training, evaluation, and testing data systems.
Skills you will acquire:
  • Category: Inclusive Learning
  • Category: BigQuery
  • Category: Application Programming Interfaces (API)
  • Category: Machine Learning
  • Category: Google Cloud Platform

TensorFlow on Google Cloud

Course 3 • 13 hours • 4.4 (2,769 reviews)

Course Details
  • Design and build an input data pipeline for TensorFlow.
  • Use the tf.data library to manipulate data in large datasets.
  • Use Keras Sequential and Functional interfaces to create simple and advanced models.
  • Train, launch, and turn machine learning models into action at scale with Vertex AI.
Skills you will acquire:
  • Category: TensorFlow
  • Category: Machine Learning
  • Category: Cloud Computing

Feature engineering

Course 4 • 8 hours • 4.5 (1,763 reviews)

Course Details
  • Explain what a Vertex AI feature pool is and compare the key aspects required for a good feature.
  • Perform feature engineering using BigQuery ML, Keras, and TensorFlow.
  • Discuss how to preprocess and explore features with Dataflow and Dataprep.
  • Use tf.Transform.
Skills you will acquire:
  • Category: TensorFlow
  • Category: Python Programming
  • Category: Machine Learning
  • Category: Keras
  • Category: Building an input data pipeline

Machine learning in the enterprise

Course 5 • 19 hours • 4.6 (1,465 reviews)

Course Details
  • Explain data management, governance and preprocessing options.
  • Identify when to use Vertex AutoML, BigQuery ML, and custom training.
  • Apply Vertex Vizier to hyperparameter orientation.
  • Explain how to create forecasts in groups and online, set up model management, and create pipelines using Vertex AI.
Skills you will acquire:
  • Category: TensorFlow
  • Category: BigQuery
  • Category: Machine Learning
  • Category: Data Cleanup

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