Join Sign in

Komalkumar Kurapati

Member since 2024

Introduction to Vertex AI Studio Earned Aug 1, 2025 EDT
Create Image Captioning Models Earned Aug 1, 2025 EDT
Transformer Models and BERT Model Earned Jul 27, 2025 EDT
Encoder-Decoder Architecture Earned Jul 27, 2025 EDT
Attention Mechanism Earned Jul 27, 2025 EDT
Introduction to Image Generation Earned Jul 27, 2025 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned Jul 17, 2025 EDT
[DEPRECATED]Introduction to Responsible AI Earned Jul 14, 2025 EDT
Introduction to Large Language Models Earned Jun 16, 2025 EDT
Introduction to Generative AI Earned Jun 13, 2025 EDT
[Deprecated] Get Started with Looker Earned Nov 17, 2024 EST
Implement Event-Driven Messaging and Automation Workflows Earned Nov 16, 2024 EST
The Basics of Google Cloud Compute Earned Nov 12, 2024 EST
Deploy and Manage Applications on Google App Engine Earned Nov 10, 2024 EST
Analyze Images with the Cloud Vision API Earned Nov 7, 2024 EST
DEPRECATED Networking Fundamentals on Google Cloud Earned Nov 7, 2024 EST
Monitoring in Google Cloud Earned Nov 7, 2024 EST

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 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 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 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 Gemini Enterprise Agent Platform.

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 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. Explore other content in the Gemini Agent Ready (GEAR) program.

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

Earn a skill badge by completing the Get Started with Looker skill badge course, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker.

Learn more

Earn a skill badge by completing the Implement Event-Driven Messaging and Automation Workflows skill badge course, where you learn how to use Pub/Sub through the Cloud console, how Cloud Scheduler jobs can save you effort, and when Pub/Sub Lite can save you money on high-volume event ingestion.

Learn more

Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.

Learn more

Earn a Skill Badge by completing the Deploy and Manage Applications on Google App Engine course, where you learn how to use App Engine with Python, Go, and PHP.

Learn more

Earn a skill badge by completing the Analyze Images with the Cloud Vision API quest, where you discover how to leverage the Cloud Vision API for various tasks, including extracting text from images.

Learn more

Earn a skill badge by completing the Networking Fundamentals on Google Cloud quest, where you learn how to work with VPC networks and load balancers on Google Cloud. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.

Learn more

Complete the introductory Monitoring in Google Cloud skill badge course to demonstrate skills in the following: using Cloud Monitoring tools to monitor resources on Google Cloud.

Learn more