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Google Cloud Training

This course teaches you to use Generative AI App Builder to integrate enterprise-grade generative AI search.

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Syllabus

Introduction
Introduce learners to the course
Generative AI on Google Cloud
Define generative AI, its history and product offerings on Google Cloud, and the target personas for each product.
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Career center

Learners who complete Enterprise Search on Generative AI App Builder will develop knowledge and skills that may be useful to these careers:
Enterprise Search Engineer
An Enterprise Search Engineer designs, builds, and maintains search solutions for internal and external enterprise content, ensuring information is discoverable and accessible. This role involves implementing and optimizing search algorithms, indexing strategies, and retrieval systems. The "Enterprise Search on Generative AI App Builder" course is exceptionally well-suited for an aspiring or current Enterprise Search Engineer. It provides direct instruction on creating, ingesting data into, and managing search engines using Generative AI App Builder. This includes configuring search results from various data types and integrating search into applications, which are core tasks for this role. Understanding Generative AI App Builder architecture, security, and analytics from the course helps build robust, performant, and secure enterprise search systems, directly addressing the pain points of scattered information within organizations.
Generative AI Solutions Architect
A Generative AI Solutions Architect designs and oversees the implementation of Generative AI-powered solutions, translating business requirements into technical architectures. They select appropriate AI platforms and tools, ensuring scalability, security, and integration with existing systems. The "Enterprise Search on Generative AI App Builder" course is directly relevant for this career path. It provides deep knowledge of Generative AI product offerings on Google Cloud and their architecture, particularly focusing on Generative AI App Builder. Understanding authentication, access control with Identity and Access Management IAM, data governance, and compliance from the course is crucial for designing secure and compliant solutions. The course's exploration of enterprise search use cases helps in identifying where Generative AI can provide significant value, a key skill for an architect aiming to solve complex enterprise information challenges.
Cloud Data Engineer
A Cloud Data Engineer designs, builds, and maintains data pipelines and infrastructure for data storage, processing, and retrieval in cloud environments. This role ensures data quality, accessibility, and efficiency for various applications, including search. For a Cloud Data Engineer, the "Enterprise Search on Generative AI App Builder" course is highly pertinent. A significant portion of this role involves preparing and managing data. The course explicitly teaches managing data in Generative AI App Builder, including creating a search engine and ingesting data into it. This expertise is vital for ensuring that the vast amounts of information—whether structured or unstructured—are correctly prepared and indexed for optimal search performance within an enterprise context, leveraging Google Cloud's capabilities to make information readily accessible.
Technical Consultant
A Technical Consultant advises clients on technical solutions, helping them understand complex systems and guiding them through implementation processes. This involves analyzing client needs, recommending appropriate technologies, and providing architectural guidance. The "Enterprise Search on Generative AI App Builder" course is exceptionally valuable for a Technical Consultant. This role frequently involves helping enterprises make their information accessible and improve customer-facing search. The course provides comprehensive knowledge of Generative AI App Builder, its architecture, security, and data management. A consultant can leverage this expertise to identify specific enterprise search use cases for clients, advise on integrating generative AI search into their applications, and guide them through implementation, ensuring successful adoption and maximizing the benefits of Google Cloud's offerings.
Cloud Software Engineer
A Cloud Software Engineer designs, develops, and deploys software applications that run on cloud computing platforms. This role works with cloud services, APIs, and SDKs to build scalable, resilient, and cost-effective solutions. The "Enterprise Search on Generative AI App Builder" course is very pertinent for a Cloud Software Engineer, especially one building applications on Google Cloud. The course directly teaches how to integrate enterprise-grade generative AI search into applications using Generative AI App Builder. Key modules like configuring search results from websites, unstructured and structured data, and integrating search in your applications are crucial. Understanding the architecture, authentication, and data management aspects within Generative AI App Builder provides the specific knowledge needed to develop robust, secure, and highly functional generative AI search capabilities within cloud-native applications.
Machine Learning Engineer
A Machine Learning Engineer designs, builds, and deploys machine learning models and systems. This includes data preprocessing, model training, evaluation, optimization, and deployment into production environments. A Machine Learning Engineer working with enterprise-level applications will find the "Enterprise Search on Generative AI App Builder" course quite beneficial. While focusing on an application builder, the course dives into Generative AI concepts, its product offerings, and use cases. Understanding how Generative AI App Builder is used to integrate enterprise-grade generative AI search provides practical context for deploying and managing AI models in a real-world enterprise setting, complementing the theoretical and model-building expertise of a Machine Learning Engineer with application-level insights into solving real-world information accessibility challenges.
Technical Product Manager
A Technical Product Manager defines the product vision, strategy, and roadmap for technical products, often involving complex software or platforms. This role involves gathering requirements, prioritizing features, and collaborating with engineering teams to deliver solutions. For a Technical Product Manager focused on enterprise solutions, the "Enterprise Search on Generative AI App Builder" course is highly relevant. It provides a deep understanding of enterprise search use cases and the capabilities of Generative AI App Builder, which is essential for defining compelling product features aimed at making information readily accessible. The course's modules on architecture, security, data management, and analytics equip a product manager with the technical literacy to make informed decisions, prioritize effectively, and communicate clearly with engineering teams on building and improving search products.
Information Architect
An Information Architect structures and organizes information within complex systems to enhance usability and discoverability. This role designs navigation, labeling, and search capabilities, ensuring users can easily find and understand desired content. An Information Architect may find the "Enterprise Search on Generative AI App Builder" course helpful in addressing the challenge of making information readily accessible. The course provides practical insights into how Generative AI can create better search and recommendation experiences. Understanding how to manage data in a search engine and configure the display of enterprise search results from various data sources directly informs an Information Architect's design decisions regarding information organization and retrieval, ensuring a coherent and effective user journey for both employees and customers.
Knowledge Management Specialist
A Knowledge Management Specialist facilitates the creation, sharing, and use of an organization's knowledge assets. This role implements strategies and tools to improve information accessibility, collaboration, and learning within an enterprise. The "Enterprise Search on Generative AI App Builder" course may be particularly helpful for a Knowledge Management Specialist, as it directly addresses the challenge of making internal information readily accessible. This role benefits from understanding how Generative AI App Builder can provide better search experiences across scattered internal documentation, wikis, and file shares. The course's focus on managing data in a search engine and configuring search results offers practical knowledge for improving the discoverability and utility of an organization’s knowledge base, ultimately enhancing enterprise-wide information sharing and reducing frustration.
Data Governance Specialist
A Data Governance Specialist develops and enforces policies and standards for data quality, security, privacy, and compliance within an organization. This role ensures data integrity and manages risks associated with information assets. For a Data Governance Specialist, the "Enterprise Search on Generative AI App Builder" course may be particularly relevant. The syllabus directly addresses "data governance and compliance" within the context of Generative AI App Builder architecture and security. Understanding how Identity and Access Management IAM controls access to Gen App Builder apps and how data is managed within the search engine is critical. This knowledge helps ensure that the deployment of generative AI search solutions adheres to an organization's data policies and regulatory requirements, safeguarding sensitive enterprise information, which is a core responsibility.
Business Analyst
A Business Analyst bridges the gap between business needs and technical solutions. This role gathers and analyzes requirements, identifies problems, and recommends solutions to improve processes and systems within an organization. For a Business Analyst, the "Enterprise Search on Generative AI App Builder" course may offer valuable insights into addressing critical business challenges related to information accessibility for employees and customers. The course's focus on enterprise search use cases provides a framework for identifying where Generative AI can offer better search and recommendation experiences. Understanding the technical architecture and data management aspects, even at a conceptual level, helps a Business Analyst translate business requirements into actionable specifications for developing and implementing Generative AI-powered search solutions.
User Experience Designer
A User Experience Designer designs intuitive and engaging user interfaces and experiences for digital products. This includes conducting user research, creating wireframes and prototypes, and ensuring usability and accessibility. A User Experience Designer may find the "Enterprise Search on Generative AI App Builder" course helpful, especially when designing interfaces that incorporate complex search functionalities. The module on "Displaying Enterprise Search Results" is particularly relevant, as it discusses configuring results from various data types and integrating search in applications. Understanding the underlying generative AI search capabilities and architecture enables a User Experience Designer to create more effective and user-friendly interfaces for search and navigation, directly addressing customer frustrations with ineffective site search and poor navigation capabilities.
DevOps Engineer
A DevOps Engineer automates and streamlines the software development lifecycle, ensuring efficient deployment, operation, and scaling of applications and infrastructure. This role manages continuous integration and continuous delivery pipelines. A DevOps Engineer may find the "Enterprise Search on Generative AI App Builder" course helpful for understanding the specific deployment and operational considerations for generative AI search applications. While Generative AI App Builder simplifies much of the infrastructure, understanding its architecture, authentication, access control with Identity and Access Management IAM, and data management is crucial for efficient deployment and monitoring. The course's insights into product usage through analytics also inform observability strategies, enabling a DevOps Engineer to effectively manage the lifecycle of enterprise search solutions built on this Google Cloud platform.
Site Reliability Engineer
A Site Reliability Engineer combines software engineering with operations to build and run large-scale, fault-tolerant systems. This role focuses on system availability, latency, performance, efficiency, change management, monitoring, emergency response, and capacity planning. A Site Reliability Engineer may find the "Enterprise Search on Generative AI App Builder" course helpful in understanding the operational aspects of generative AI-powered search applications. The course covers Generative AI App Builder architecture, security, Identity and Access Management IAM, and particularly touches upon pricing, which informs resource management and cost optimization. While not directly about SRE practices, knowing how to manage data in a search engine and understanding product usage through analytics provides context for monitoring system health, performance, and scaling requirements for enterprise search solutions, ensuring information is always readily accessible.
Customer Success Manager Enterprise Software
A Customer Success Manager Enterprise Software builds strong relationships with enterprise clients, ensuring they achieve maximum value from software products. This role provides strategic guidance, resolves issues, and identifies opportunities for product adoption and expansion. A Customer Success Manager focused on enterprise software may find the "Enterprise Search on Generative AI App Builder" course helpful. This role often involves guiding customers through the implementation and optimization of complex solutions. Understanding the capabilities of Generative AI App Builder, its architecture, and the various enterprise search use cases allows a Customer Success Manager to better articulate the value proposition, troubleshoot common adoption challenges, and provide informed recommendations to clients looking to improve their information accessibility and search experiences using Google Cloud's Generative AI offerings.

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Enterprise Search on Generative AI App Builder.
For those specializing in cryptography, this book provides real-world examples, providing a strong foundation for cryptographic engineering.
Provides a comprehensive guide to cloud architecture patterns, including patterns for designing scalable, resilient, and portable cloud applications. It valuable resource for architects and developers who want to design and build cloud-based systems.
Provides a comprehensive overview of cloud computing and big data, covering topics such as cloud computing architectures, big data analytics, and data management. It is an excellent resource for understanding the convergence of cloud computing and big data.
Explores the fundamental trade-offs and concepts behind designing modern data systems, covering various technologies and distributed systems principles. It is highly relevant for understanding contemporary data management challenges and must-read for engineers and architects.
Offers an in-depth exploration of AWS security services, including a strong focus on IAM. It's suitable for cloud architects, engineers, and cybersecurity professionals looking to master AWS security concepts and apply advanced techniques. The second edition ensures coverage of recent updates.
Definitive work on the principles and techniques of transaction processing, a core concept in database systems and distributed computing. It is essential for understanding how to build reliable and consistent data systems.
Presents a collection of proven patterns for designing and building cloud-native applications. It covers topics such as microservices, containers, and serverless computing. It valuable resource for architects and developers who want to adopt cloud-native practices.
Comprehensive guide to Elasticsearch, a popular open-source enterprise search engine. It provides a detailed overview of the Elasticsearch architecture, API, and features, and includes case studies from real-world implementations.
Comprehensive guide to using Lucene for enterprise search. It covers all aspects of Lucene, from installation and configuration to query optimization and performance tuning. It valuable resource for anyone who wants to use Lucene to build an enterprise search solution.
Is excellent for gaining a broad understanding of analytics, focusing on the fundamental principles of data science and the 'data-analytic thinking' necessary for extracting business value from data. It's commonly used as a textbook in MBA and analytics programs and provides a solid foundation for anyone looking to understand how analytics supports business decision-making.
Authored by Google's Kubernetes experts, this book covers the fundamentals and advanced topics of Google Kubernetes Engine, providing deep insights into container orchestration and management.
Another practical guide focused on AWS IAM, this book aims to provide the essential knowledge needed to work effectively with the service. It covers core concepts and real-world scenarios, making it a useful resource for both beginners and experienced AWS users looking to solidify their IAM skills.
This cookbook provides hands-on recipes for securing AWS, with a dedicated chapter on Access Management with IAM Policies and Roles. It's a practical guide for those working directly with AWS, offering solutions to common security challenges. It's particularly useful for deepening understanding through practical application.
Provides a comprehensive overview of cloud computing and software engineering, covering topics such as cloud computing architectures, software development methodologies, and cloud-based software engineering. It is an excellent resource for understanding the relationship between cloud computing and software engineering.
Provides a hands-on approach to cloud computing, covering topics such as cloud computing architectures, service models, deployment models, and security considerations. It is an excellent resource for readers who want to learn how to build and deploy cloud-based applications.
Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Provides a comprehensive overview of cloud computing concepts, technologies, and architectures. It is an excellent resource for understanding the fundamentals of cloud computing and how to design and build cloud-based applications.
Provides a detailed overview of cloud security, providing a roadmap for securing your cloud infrastructure.
Provides a detailed look inside the implementation of database systems, covering topics like storage engines, indexing, and concurrency control. It is excellent for deepening understanding of how databases function at a low level and is valuable for database professionals.
Covers the end-to-end process of designing, building, and managing data pipelines and analytical systems. It is highly relevant for aspiring and practicing data engineers, covering a wide range of contemporary data management tools and techniques.
Provides a practical guide to establishing and implementing data governance programs. It is crucial for understanding the organizational and process aspects of managing data effectively and valuable resource for data leaders and practitioners.
A must-read for anyone who needs to communicate data insights effectively. focuses on the principles of data visualization and how to create compelling visual stories with data. It's highly practical and useful as a reference tool for creating clear and impactful presentations and reports.
While covering broader cloud security, this book includes significant content on identity and access control within cloud environments like AWS, Azure, and GCP. It offers practical guidance on securing cloud deployments, making it a useful reference for professionals and advanced students. The second edition is recently published, ensuring up-to-date information.
Dives into the core protocols that underpin modern identity and access management in applications. Understanding OAuth 2.0, OpenID Connect, and SAML 2.0 is essential for anyone working with IAM in a development or architectural context. It's more technical and suitable for those looking to deepen their understanding of how these systems work.
A widely-used textbook in database courses, this book offers a thorough introduction to database systems, including relational models, SQL, and transaction management. It's valuable for both broad understanding and deepening knowledge, providing a solid theoretical and practical basis for data management.
Focuses on practical data engineering using modern technologies like Apache Spark and Delta Lake. It is highly relevant for professionals building data pipelines and managing data in cloud-based data lakes, addressing contemporary challenges in big data.
Tailored for the GCP Professional Cloud Security Engineer exam, this book provides comprehensive coverage of GCP security, with a significant portion dedicated to Google Cloud Identity and Access Management. It's an excellent resource for those focusing on GCP and preparing for certification, offering a structured approach to learning key concepts and best practices.
Focuses on the principles and practices for building and operating reliable and resilient database systems. It is highly relevant for professionals in site reliability engineering and database administration, addressing the operational challenges of data management.
This guide provides practical advice and techniques for improving data quality, a fundamental aspect of effective data management. It valuable resource for anyone responsible for ensuring the accuracy and reliability of data.
For those working with Microsoft Azure, this book provides in-depth coverage of Azure's identity and access management solutions. It's a valuable resource for understanding and implementing IAM in the Azure ecosystem, complementing the AWS and GCP focused books.
Ideal for those new to statistics or needing a refresher, this book demystifies core statistical concepts without complex mathematics. It uses engaging real-world examples to build intuition around statistical analysis, correlation, and regression, making it a great preparatory read for more technical analytics texts.
Focuses on applying data science techniques, particularly machine learning, to solve business problems. It uniquely combines concepts from machine learning and economics, making it highly relevant for those interested in using analytics for strategic business decisions. It is suitable for advanced undergraduate or graduate students and professionals.
This official study guide for the CCSP certification covers various domains of cloud security, with a significant focus on cloud access control and identity management. It's a comprehensive resource for those pursuing this vendor-neutral cloud security certification, offering a broad and deep understanding of relevant security principles.
Provides a broad overview of computer security, making it suitable for both beginners and experienced professionals to update their skills.
For those interested in ethical hacking, this book provides a step-by-step guide to penetration testing techniques.
A comprehensive and advanced text covering a wide range of statistical learning methods. classic and a valuable reference for graduate students and researchers seeking a deep understanding of the theoretical underpinnings of analytics and data mining techniques. It is significantly more challenging than introductory books.
Delves into the core concepts and services of Google Cloud Platform, including compute, storage, networking, and containers. It offers a deep understanding of GCP's architecture and best practices.
Focuses on the architectural challenges of building data-intensive applications, such as choosing the right data storage and processing technologies and designing scalable and fault-tolerant systems. It valuable resource for architects and developers who want to build robust and efficient cloud-based applications.
Examines the ethical considerations surrounding data and analytics, including privacy, bias, and accountability. It crucial read for anyone working with data to understand the societal impact and ethical responsibilities in data management.
Provides a practical guide to cloud computing, covering topics such as cloud computing models, deployment strategies, and best practices. It valuable resource for architects and developers who want to design and build cloud-based applications.
Highlights common mistakes and poor practices in SQL programming and database design. It is highly practical for anyone writing SQL queries or designing databases, helping to improve efficiency and avoid common issues.
Provides a practical guide to building and managing data pipelines using Apache Airflow, a popular workflow orchestration tool. It is relevant for data engineers and anyone involved in building automated data processing workflows.
Offers a comprehensive view of cloud security from an enterprise perspective, including the critical role of identity and access management in addressing risks and ensuring compliance. It's a valuable resource for understanding the broader business and regulatory context of IAM in the cloud.
Bridges the gap between statistical theory and its application in data science. It focuses on the statistical concepts that are most relevant to data science practitioners, with examples in R and Python. It's a useful resource for those who need to apply statistical methods in their analytics work.

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