Join Sign in

Apply your skills in Google Cloud console

Sumeet Patil

Member since 2022

Silver League

3639 points
Build Agents with Agent Development Kit (ADK) Earned Feb 20, 2026 EST
Create Your First Gemini Enterprise Application Earned Feb 20, 2026 EST
Enterprise Agents and Use Cases Earned Feb 20, 2026 EST
Agent Fundamentals Earned Feb 20, 2026 EST
Introduction to AI Agents Earned Feb 20, 2026 EST
Responsible AI: Applying AI Principles with Google Cloud Earned Feb 21, 2024 EST
Introduction to Vertex AI Studio Earned Aug 6, 2023 EDT
Create Image Captioning Models Earned Aug 3, 2023 EDT
Transformer Models and BERT Model Earned Aug 3, 2023 EDT
Attention Mechanism Earned Aug 3, 2023 EDT
Encoder-Decoder Architecture Earned Aug 3, 2023 EDT
Introduction to Image Generation Earned Aug 2, 2023 EDT
Generative AI Fundamentals Earned Aug 2, 2023 EDT
Introduction to Responsible AI Earned Aug 2, 2023 EDT
Introduction to Large Language Models Earned Aug 2, 2023 EDT
Introduction to Generative AI Earned Aug 2, 2023 EDT

Learn about how you can use Agent Development Kit (ADK) to build complex, production-ready AI agents. This course covers ADK’s open-source framework, moving from simple prompt engineering to a code-first, structured software development approach suitable for enterprise-grade, multi-agent systems.

Learn more

Create your first Gemini Enterprise application to earn a skill badge! Connect diverse data sources to your application to build a powerful, unified search and analysis engine. Master advanced capabilities like deep research agents, multi-agent ideation, and NotebookLM for focused analysis.

Learn more

Discover how AI agents drive business impact. You’ll map agent types to your KPIs and explore use cases that solve real bottlenecks. Then, learn how Gemini Enterprise empowers you to build and orchestrate the right agents—from no-code to high-code solutions.

Learn more

AI Agents represent a major shift beyond traditional large language models (LLMs): instead of simply generating text-based solutions, they can also act autonomously to execute them. This course introduces the fundamentals of AI Agents, how they differ from LLM APIs, and where they add value in the real world. Based on Google’s agents whitepaper, it provides the theoretical foundation needed before writing your first lines of agent code—ideal for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior (and not just text generation). Join the community forum for questions and discussions.

Learn more

Gain a conceptual overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems. You’ll explore the technical architecture—models, tools, and orchestration—that enables agents to learn, plan, and achieve goals on your behalf.

Learn more

As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you. In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.

Learn more

This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.

Learn more

This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images

Learn more

This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.

Learn more

This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.

Learn more

This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.

Learn more

This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.

Learn more

Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. By passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

Learn more

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