Online Course – Certified Professional Internship in Machine Learning with TensorFlow in the Google Cloud by Google Cloud Institute

Learn how to use machine learning with Google Cloud. Discover use machine learning from start to finish in real-world conditions.

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קורס אונליין - התמחות מקצועית מוסמכת בלמידת מכונה עם TensorFlow בענן Google של Google Cloud Institute

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

  • Project management capabilities
  • Communication skills
  • Critical thinking
  • Analytical tools
  • Digital Marketing
  • Creativity in problem solving
  • Experience working with new technologies
  • Teamwork skills
  • Strategic planning
  • Understanding the market and consumer behavior

What you will learn in the course

Courses for which the course is suitable

  • Machine Learning Engineer
  • Artificial Intelligence Developer
  • Data Analyst
  • Data Scientist
  • Data Modeling Expert
  • Software developer with a specialization in machine learning
  • Artificial Intelligence Project Manager
  • Machine Learning Researcher
  • TensorFlow expert
  • Data Systems Analyst

Internship – a five-part course series

What is machine learning?

  • What kind of problems can it solve?
  • The five steps required to address a machine learning use case:
    • Why is each step essential?
  • Why have neural networks become so popular?
  • How do you define a supervised learning problem?
  • How do you reach a suitable solution using gradient descent?
  • A suitable method for building data systems.

Learn how to:

  • Create distributed machine learning models that can evolve within TensorFlow.
  • Adjust the training of the models to benefit from horizontal scalability.
  • Achieve high-performance forecasts.
  • Convert raw data into features so that machine learning processes can identify the important characteristics in the data.
  • Create insights that are meaningful in the context of the problem.
  • Integrate the combination of parameters that allow obtaining accurate and qualitative models.
  • Understanding the theory is necessary for solving specific types of machine learning problems.

Experience end-to-end machine learning:

  • Start by creating a strategy focused on machine learning.
  • Progress in the training, optimization, and production of models.
  • Hands-on workshops using the Google Cloud Platform.

Registration for the internship series

Registration for this internship series constitutes agreement to the Qwiklabs Terms of Service detailed in the FAQ and available at: https://qwiklabs.com/terms_of_service

Applied Learning Project

The specialization series includes:

  • Practical workshops to perform on our Qwiklabs platform.
  • Applying what you learn in the recorded courses.
  • Projects are focused around a topic such as Google Cloud Platform products.
  • Practical experience in the principles explained in the modules.

Details of the courses that make up the specialization

How Google is doing machine learning in French language courses

Course 1 • 14 hours • 4.3 (16 ratings)

  • Course Details
  • What you’ll learn
    • Describe the Vertex AI platform and how to use it to create, train, and launch AutoML machine learning models without writing code.
    • Describe best practices for implementing machine learning on Google Cloud.
    • Take advantage of Google Cloud Platform tools and environment to implement ML.
    • To formulate good practices of responsible IA.

Course 2 • 15 hours • 4.5 (11 ratings)

  • Course Details
  • What you’ll learn
    • Explain how to improve data quality and perform exploratory analyses.
    • Create and train AutoML models with Vertex AI and BigQuery ML.
    • Optimize and evaluate models using loss functions and performance metrics.
    • Create training, evaluation, and testing datasets that can be replicated and expanded.

Course 3 • 13 hours

  • Course Details
  • What you’ll learn
    • Create TensorFlow and Keras machine learning models and describe their key components.
    • Use the tf.data library to manipulate data and large datasets.
    • Use Keras Sequential and Functional APIs for simple and advanced model creation.
    • Train, launch, and transform ML models for large-scale challenges with Vertex AI.

Course 4 • 10 hours

  • Course Details
  • What you’ll learn
    • Describe the Vertex AI Feature Store and compare the main aspects that characterize a relevant feature.
    • Perform feature engineering using BigQuery ML, Keras, and TensorFlow.
    • Discover how to preprocess and explore features using Dataflow and Dataprep.
    • Use tf.Transform.

Course 5 • 17 hours

  • Course Details
  • What you’ll learn
    • Welcome to “The Art and Science of Machine Learning.” This course consists of 6 modules.
    • During the course, we will examine the fundamental skills – intuition, logic, and experimentation – required to tune your ML models and improve their performance.
    • We will learn how to generalize your model using regularization techniques and discuss the impact of hyperparameters such as batch size and learning rate on model performance.
    • We will also introduce some of the most common optimization algorithms and explain how to set an optimization method in your TensorFlow code.

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