
Machine learning and artificial intelligence
Did you know that the adoption of machine learning results in 2x more data-driven decisions, 5x faster decision-making, and 3x faster execution?1
Learn how to implement the latest machine learning and artificial intelligence technology by exploring training on BigQuery, TensorFlow, Cloud Vision, Natural Language API, and more.
Data Scientist / Machine Learning Engineer learning path
A Data Scientist models and analyzes key data to continually improve how businesses utilize data. Data Scientists aim to make accurate predictions about the future using in-depth data modeling and deep learning.
Course
Big Data & Machine Learning Fundamentals
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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Perform Foundational Data, ML, and AI Tasks in Google Cloud
Get started with big data, machine learning, and artificial intelligence. Take your first steps with Google Cloud tools like BigQuery, Cloud Speech API, and AI Platform. You'll have the opportunity to earn a Google Cloud skill badge upon completion.
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Machine Learning on Google Cloud
In this course you will experiment with end-to-end machine learning on Google Cloud, starting from building a machine learning-focused strategy and progressing into model training, optimization, and productionalization.
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Advanced Machine Learning with TensorFlow on Google Cloud Platform
This advanced course teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text, and ends with building recommendation systems. This content can also be taken as part of the Advanced Solutions Lab.
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MLOps (Machine Learning Operations) Fundamentals
In this course you will learn MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. This content can also be taken as part of the Advanced Solutions Lab.
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ML Pipelines on Google Cloud
In this course you will learn how to implement ML pipelines with continuous training and CI/CD practices to increase your ML workflow development and deployment velocity, automation, and ability to scale with your data on Google Cloud. This content can also be taken as part of the Advanced Solutions Lab.
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Build and Deploy Machine Learning Solutions on Vertex AI
Get practice with Vertex AI platform, AutoML, and custom training services. You'll learn how to use Vertex AI for new and existing ML workloads, as well as how to leverage AutoML, custom training, and new MLOps services to significantly enhance development productivity and accelerate time to value.
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Create Conversational AI Agents with Dialogflow CX
Learn how to create a conversational virtual agent, including how to: define intents and entities, use versions and environments, create conversational branching, and use IVR features.
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What you'll learn
TensorFlow, AI Platform Notebooks, Cloud Dataflow, Cloud DataFusion, AI Platform, BigQuery, BigQuery ML, Cloud ML APIs, Kubeflow Pipelines
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Courses
5
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Labs
27
Take the next step
Contact Center Engineer
Learn how to design, develop, and deploy customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You'll also learn some best practices for integrating conversational solutions with your existing contact center software, establishing a framework for human agent assistance, and implementing solutions securely and at scale.
Course
Customer Experiences with Contact Center AI
Learn how to design, develop, and deploy customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You'll also learn some best practices for integrating conversational solutions with your existing contact center software, establishing a framework for human agent assistance, and implementing solutions securely and at scale.
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Automate Interactions with Contact Center AI
Interactions with Contact Center AI should be conversational and human-like. Learn how to build a virtual agent, design conversational flows for your virtual agent, and add a phone gateway to a virtual agent.
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Create Conversational AI Agents with Dialogflow CX
Learn how to create a conversational virtual agent, including how to: define intents and entities, use versions and environments, create conversational branching, and use IVR features.
Learn moreRelated information
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What you'll learn
Contact Center Artificial Intelligence, Dialogflow, Natural Language Understanding (NLU)
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Courses
1
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Labs
12
Take the next step
Additional courses and practice
Advanced Solutions Lab

The Advanced Solutions Lab is a 4-week, full-time immersive training program in applied machine learning. It provides a unique opportunity for your technical teams to dive into a particular machine learning use case for your business. Attendees learn alongside Google's machine learning experts in a dedicated, collaborative space on Google Campus.
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