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DM Haritha Kawshan Piyumantha

Member since 2022

Silver League

18710 points
Responsible AI: Applying AI Principles with Google Cloud Earned Jan 4, 2024 EST
Introduction to Vertex AI Studio Earned Jun 16, 2023 EDT
Create Image Captioning Models Earned Jun 16, 2023 EDT
Transformer Models and BERT Model Earned Jun 16, 2023 EDT
Attention Mechanism Earned Jun 16, 2023 EDT
Encoder-Decoder Architecture Earned Jun 16, 2023 EDT
Introduction to Image Generation Earned Jun 16, 2023 EDT
Generative AI Fundamentals Earned Jun 16, 2023 EDT
Introduction to Responsible AI Earned Jun 16, 2023 EDT
Introduction to Large Language Models Earned Jun 16, 2023 EDT
Introduction to Generative AI Earned Jun 16, 2023 EDT
Build a Secure Google Cloud Network Earned May 24, 2023 EDT
Mitigating Security Vulnerabilities on Google Cloud Earned Apr 18, 2023 EDT
Google Kubernetes Engine Best Practices: Security Earned Apr 18, 2023 EDT
Implement Cloud Security Fundamentals on Google Cloud Earned Apr 17, 2023 EDT
Security Best Practices in Google Cloud Earned Apr 17, 2023 EDT
Managing Security in Google Cloud Earned Apr 11, 2023 EDT
Analytics for SAP on Google Cloud Earned Mar 7, 2023 EST
Modernizing Mainframe Applications with Google Cloud Earned Mar 3, 2023 EST
Deploying SAP on Google Cloud Earned Sep 8, 2022 EDT
SAP on Google Cloud Earned Sep 8, 2022 EDT
Scaling with Google Cloud Operations Earned Sep 2, 2022 EDT
Modernize Infrastructure and Applications with Google Cloud Earned Sep 2, 2022 EDT
Developing a Google SRE Culture Earned Aug 30, 2022 EDT
Exploring Data Transformation with Google Cloud Earned Aug 17, 2022 EDT
Digital Transformation with Google Cloud Earned Aug 17, 2022 EDT
Build Infrastructure with Terraform on Google Cloud Earned Aug 16, 2022 EDT
Set Up an App Dev Environment on Google Cloud Earned Aug 15, 2022 EDT
Implementing Cloud Load Balancing for Compute Engine Earned Aug 10, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned Aug 10, 2022 EDT
Cloud Engineering Earned Aug 8, 2022 EDT
Kubernetes in Google Cloud Earned Aug 8, 2022 EDT
DEPRECATED Cloud Architecture Earned Aug 8, 2022 EDT
Google Cloud Essentials Earned Aug 2, 2022 EDT
Reliable Google Cloud Infrastructure: Design and Process Earned Jul 25, 2022 EDT
Essential Google Cloud Infrastructure: Foundation Earned Jul 25, 2022 EDT
DEPRECATED Planning for a Google Workspace Deployment Earned Jul 7, 2022 EDT
Google Workspace Security Earned Jul 6, 2022 EDT
Google Workspace Core Services Earned Jul 5, 2022 EDT
Google Workspace User and Resource Management Earned Jul 5, 2022 EDT

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.

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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.

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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

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Earn a skill badge by completing the Build and Secure Networks in Google Cloud course, where you will learn about multiple networking-related resources to build, scale, and secure your applications 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 the skill badge, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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In this self-paced training course, participants learn mitigations for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. They also learn about the Security Command Center, cloud logging and audit logging, and using Forseti to view overall compliance with your organization's security policies.

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Get Anthos Ready. This Google Kubernetes Engine-centric quest of best practice hands-on labs focuses on security at scale when deploying and managing production GKE environments -- specifically role-based access control, hardening, VPC networking, and binary authorization.

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Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge to demonstrate skills in the following: creating and assigning roles with Identity and Access Management (IAM); creating and managing service accounts; enabling private connectivity across virtual private cloud (VPC) networks; restricting application access using Identity-Aware Proxy; managing keys and encrypted data using Cloud Key Management Service (KMS); and creating a private Kubernetes cluster. 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 the skill badge course, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Storage access control technologies, Security Keys, Customer-Supplied Encryption Keys, API access controls, scoping, shielded VMs, encryption, and signed URLs. It also covers securing Kubernetes environments.

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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Identity, Resource Manager, IAM, Virtual Private Cloud firewalls, Cloud Load Balancing, Cloud Peering, Cloud Interconnect, and VPC Service Controls. This is the first course of the Security in Google Cloud series. After completing this course, enroll in the Security Best Practices in Google Cloud course.

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This course focuses on how you can leverage the Google Cloud Analytics and AI/ML offerings to integrate and innovate with SAP

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This course enables system integrators and partners to understand the principles of automated migrations, plan legacy system migrations to Google Cloud leveraging G4 Platform, and execute a trial code conversion.

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This course provides a holistic experience of optimally configuring SAP on Google Cloud. Participants will learn to configure SAP on Google Cloud, and what best practices are, leaving the course with actionable experience to configure SAP on Google Cloud and run SAP workloads on Google Cloud.

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This course is the third part of the SAP on Google Cloud Platform learning path. Following the SAP on Google Cloud Foundations eLearning and the SAP on Google Cloud Self-paced labs. Participants should have completed these two components before. This course consists of hands-on labs that provide a holistic experience of optimally configuring SAP on Google Cloud. Participants will learn to configure SAP on Google Cloud, and what best practices are, leaving the course with actionable experience to configure SAP on Google Cloud and run SAP workloads on Google Cloud for their customers.

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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. "Modernize Infrastructure and Applications with Google Cloud" explores these challenges and offers solutions to overcome them by using cloud technology. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.

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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences. “Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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There's much excitement about cloud technology and digital transformation, but often many unanswered questions. For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin? If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.

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Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization.

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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub. 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 skill badge that you can share with your network.

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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.

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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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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this course, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications.

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.

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This course equips students to build highly reliable and efficient solutions on Google Cloud using proven design patterns. It is a continuation of the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine courses and assumes hands-on experience with the technologies covered in either of those courses. Through a combination of presentations, design activities, and hands-on labs, participants learn to define and balance business and technical requirements to design Google Cloud deployments that are highly reliable, highly available, secure, and cost-effective.

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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, virtual machines and applications services. You will learn how to use the Google Cloud through the console and Cloud Shell. You'll also learn about the role of a cloud architect, approaches to infrastructure design, and virtual networking configuration with Virtual Private Cloud (VPC), Projects, Networks, Subnetworks, IP addresses, Routes, and Firewall rules.

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Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series. In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area. You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training. This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.

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This course empowers learners to secure their Google Workspace environment. Learners will implement strong password policies and two-step verification to govern user access. They will then utilize the security investigation tool to proactively identify and respond to security risks. Next, they will manage third-party app access and mobile devices to ensure security. Finally, learners will enforce email security and compliance measures to protect organizational data.

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This course was designed to give learners a comprehensive understanding of Google Workspace core services. Learners will explore enabling, disabling, and configuring settings for these services, including Gmail, Calendar, Drive, Meet, Chat, and Docs. Next, they'll learn how to deploy and manage Gemini to empower their users. Finally, learners will examine use cases for AppSheet and Apps Script to automate tasks and extend the functionality of Google Workspace applications.

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This course was designed to provide an understanding of user and resource management in Google Workspace. Learners will explore the configuration of organizational units to align with their organization's needs. Additionally, learners will discover how to manage various types of Google Groups. They will also develop expertise in managing domain settings within Google Workspace. Finally, learners will master the optimization and structuring of resources within their Google Workspace environment.

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