Course Catalog  > Data Science, AI, and ML

Google Cloud Data Science, AI, and ML Training

Our official Google Cloud training for Data Science, AI, and ML teaches attendees to master machine learning fundamentals, craft data models for insights (LookML),  design engaging customer experiences using Contact Center AI (Dialogflow) , generate text on Gen AI Studio, practice responsible AI, and more - all on Google Cloud's powerful platform.

Request Information
Request On-Site or Customized Course Info
Machine Learning on Google Cloud
Course ID: GCP-ML
Delivery: On-Site or Instructor-led Virtual
This course introduces the artificial intelligence (AI) and machine learning (ML) offerings on Google Cloud that support the data-to-AI lifecycle through AI foundations, AI development, and AI solutions. It explores the technologies, products, and tools available to build an ML model, an ML pipeline, and a generative AI project. You learn how to build AutoML models without writing a single line of code; build BigQuery ML models using SQL, and build Vertex AI custom training jobs by using Keras and TensorFlow. You also explore data preprocessing techniques and feature engineering.
Google Cloud Big Data and Machine Learning Fundamentals
Course ID: GCP-BD-ML
Delivery: On-Site or Instructor-led Virtual
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.
Customer Experiences with Contact Center AI - Dialogflow CX
Course ID: GCP-CUST-EXP-AI-CX
Delivery: On-Site or Instructor-led Virtual

In this Dialogflow course, master designing customer conversations using Contact Center Artificial Intelligence (CCAI). You’ll use Dialogflow CX to create virtual agents and test them using the simulator. Learn to add functionality to access data from external systems, making virtual agents conversationally dynamic. You'll be introduced to testing methods, connectivity protocols, APIs, environment management, and compliance measures. Learn best practices for integrating conversational solutions with your existing contact center software and implementing solutions securely and at scale.
Customer Experiences with Contact Center AI - Dialogflow ES
Course ID: GCP-CUST-EXP-AI-ES
Delivery: On-Site or Instructor-led Virtual

In this Contact Center AI course, master designing customer conversations using Contact Center Artificial Intelligence (CCAI). Attendees use Dialogflow ES to create virtual agents, test them using the simulator, and add functionality to access data from external systems, making virtual agents conversationally dynamic. This course covers testing methods, connectivity protocols, APIs, environment management, and compliance measures. Students also learn best practices for integrating conversational solutions with your existing contact center software and implementing solutions securely and at scale.
Developing Data Models with LookML
Course ID: GCP-DDM-LOOK
Delivery: On-Site or Instructor-led Virtual
This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.
Interactive Chat for Applications using Gen AI Studio
Course ID: GCP-ICA-GAIS
Delivery: On-Site or Instructor-led Virtual

In this course, you will explore the use of interactive multi-turn chat models using Gen AI Studio on Vertex AI and learn how to incorporate those models into your application using the PaLM API and client libraries. You will learn how to design and test chat prompts to ensure the best outputs for your applications and discuss how to choose parameters for the PaLM API to improve response quality for your use case.
Introduction to Responsible AI in Practice
Course ID: GCP-IRAIP
Delivery: On-Site or Instructor-led Virtual

In this course, you will do a high-level exploration of Google's recommended best practices for responsible AI usage across different areas of focus: Fairness, Interpretability, Privacy and Safety. Along the way, you will learn how you can leverage different open-source tools and tools on Vertex AI to explore these concepts and spend time considering the different challenges that arise with generative AI.
Text Generation for Applications using Gen AI Studio
Course ID: GCP-TGA-GAIS
Delivery: On-Site or Instructor-led Virtual

In this course, you will explore the use of text generation models using Gen AI Studio on Vertex AI and learn how to incorporate those models into your application using the PaLM API and client libraries. You will learn how to design and tune prompts to ensure the best outputs for your applications and discuss how to fine-tune foundational models to improve model output quality.