Join Sign in

Apply your skills in Google Cloud console

Dhruv Saija

Member since 2025

Gold League

9390 points
Introduction to Responsible AI Earned May 9, 2025 EDT
Introduction to Large Language Models Earned May 9, 2025 EDT
Introduction to Generative AI Earned May 9, 2025 EDT
Create ML Models with BigQuery ML Earned May 9, 2025 EDT
Working with Notebooks in Vertex AI Earned May 8, 2025 EDT
Professional Machine Learning Engineer Study Guide Earned May 7, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud Earned May 6, 2025 EDT
Build Real World AI Applications with Gemini and Imagen Earned Apr 30, 2025 EDT

This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.

Learn more

This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.

Learn more

This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

Learn more

Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.

Learn more

This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.

Learn more

This course helps learners create a study plan for the PMLE (Professional Machine Learning Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

Learn more

This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.

Learn more

Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Vertex AI platform.

Learn more