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Syllabus

Modern agents
Explain the collaborative functionality of the components of generative AI agents.
Building agents
Explain how you can combine the components of generative AI agents to build powerful solutions.
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Activities

Coming soon We're preparing activities for Gen AI Agents: Transform Your Organization. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Gen AI Agents: Transform Your Organization will develop knowledge and skills that may be useful to these careers:
Artificial Intelligence Engineer
An Artificial Intelligence Engineer builds and deploys AI systems, including generative AI agents, to solve complex business problems. This course is highly relevant for aspiring or current Artificial Intelligence Engineers as it provides hands-on practice building a basic generative AI agent and deep dives into components like models, reasoning loops, and tools. Understanding how to combine these components to create powerful solutions, as outlined in the "Building agents" module, directly translates into practical engineering tasks. Furthermore, the course's exploration of Google Cloud's generative AI products offers valuable insight into real-world platform capabilities for creating agents and solutions. This curriculum directly addresses the technical foundations required for this advanced engineering role.
Generative Artificial Intelligence Product Manager
A Generative Artificial Intelligence Product Manager guides the development and strategy of AI products, particularly those involving generative AI agents. This course provides a robust foundation for Generative Artificial Intelligence Product Managers by exploring how organizations can leverage custom generative AI agents to tackle specific business challenges. The "Strategy: Planning ahead" module, covering strategic planning for AI integration, organizational impact, and fostering innovation, is crucial for defining product roadmaps and vision. Understanding the components of generative AI agents and their application to enhancing customer experience provides the necessary technical literacy to collaborate effectively with engineering teams and envision impactful AI solutions.
Artificial Intelligence Solutions Architect
An Artificial Intelligence Solutions Architect designs and oversees the implementation of AI-driven systems and solutions within an organization. For an Artificial Intelligence Solutions Architect, this course is invaluable as it delves into how custom generative AI agents can transform an organization by addressing specific business challenges. The practical exploration of agent components, such as models and reasoning loops, combined with understanding how to build powerful solutions from these parts, directly informs architectural design choices. The module on "Enhancing the customer experience with agents" using Google Cloud's generative AI products provides concrete examples and knowledge crucial for designing scalable and effective AI agent solutions.
Artificial Intelligence Consultant
An Artificial Intelligence Consultant advises businesses on AI strategy, implementation, and leveraging AI technologies for organizational growth and efficiency. For an Artificial Intelligence Consultant, this course is exceptionally relevant, providing a comprehensive understanding of how generative AI agents can transform organizations by addressing specific business challenges. The "Strategy: Planning ahead" module, which covers strategic planning for AI integration, assessing impact, and managing change, equips consultants with the framework to guide clients through complex digital transformations. Furthermore, understanding the components of generative AI agents and their practical application, including enhancing customer experience with Google Cloud products, enables consultants to recommend concrete, high-impact solutions.
Machine Learning Engineer
A Machine Learning Engineer develops and implements machine learning algorithms and systems, often specializing in areas like generative AI. This course is highly beneficial for Machine Learning Engineers seeking to specialize in or deepen their understanding of generative AI agents. It offers hands-on practice building a basic generative AI agent and explores its fundamental components, including models, reasoning loops, and tools. The curriculum's focus on combining these components to build powerful solutions, as detailed in the "Building agents" module, directly enhances the practical skills required for developing advanced machine learning applications. Understanding agent functionality and strategic integration prepares engineers to contribute meaningfully to cutting-edge AI projects.
Technical Program Manager Artificial Intelligence
A Technical Program Manager Artificial Intelligence oversees complex AI initiatives, ensuring projects are delivered on time and align with strategic objectives. This course is directly applicable to Technical Program Managers Artificial Intelligence as it explores how custom generative AI agents can transform an organization, addressing critical business challenges. The "Strategy: Planning ahead" module, focusing on strategic planning for AI integration, impact within the organization, and planning for change, provides essential leadership insights for managing AI projects. Understanding the components of generative AI agents and how to combine them to build powerful solutions enables effective communication with engineering teams and informed decision-making throughout the program lifecycle.
Data Scientist
A Data Scientist analyzes complex datasets to extract insights and build predictive models, increasingly including generative AI applications. This course can be highly valuable for Data Scientists looking to expand their expertise into the rapidly evolving field of generative AI agents. By exploring the components of generative AI agents, such as models and reasoning loops, and understanding how they tackle specific business challenges, Data Scientists gain critical insight into advanced model architectures and their deployment. The strategic planning for AI integration and impact also helps Data Scientists understand the broader organizational context for their work, enabling them to design more impactful and relevant data-driven solutions.
Cloud Architect
A Cloud Architect designs and implements cloud-based infrastructure and solutions, often supporting advanced technologies like AI and machine learning. This course is particularly relevant for Cloud Architects as it describes how Google Cloud’s generative AI products can be used to create generative AI agents and solutions. Understanding the specific components of generative AI agents, such as models and reasoning loops, helps architects design optimal cloud environments for their deployment and scaling. The strategic planning for AI integration within an organization provides crucial context for building robust, secure, and future-proof cloud infrastructures that effectively support generative AI initiatives.
Prompt Engineer
A Prompt Engineer designs and refines inputs for generative AI models to achieve specific, desired outputs and behaviors. For a Prompt Engineer, this course is highly relevant as it delves into the components of generative AI agents, specifically mentioning models and reasoning loops. While agents involve more than just prompting, understanding how models are orchestrated within these larger systems, and how they combine with tools to build powerful solutions, provides a broader context for prompt design. The hands-on practice building a basic generative AI agent enhances understanding of model interaction, which is foundational for optimizing prompt effectiveness within complex AI applications.
Customer Experience Strategist
A Customer Experience Strategist conceptualizes and implements strategies to optimize customer interactions and satisfaction across an organization. This course may be highly useful for a Customer Experience Strategist as it explicitly includes a module on "Enhancing the customer experience with agents," describing how Google Cloud’s generative AI products can create such solutions. Understanding how custom generative AI agents tackle specific business challenges provides insight into automating and improving customer journeys. The course's exploration of strategic planning for AI integration further helps in envisioning how these agents fit into broader customer service architectures and contribute to overall organizational transformation.
Innovation Manager
An Innovation Manager drives new ideas and technologies within an organization to foster growth and competitive advantage. This course may be particularly useful for an Innovation Manager because it directly addresses fostering a culture of innovation as a leader, particularly through the strategic integration of AI solutions. By exploring how custom generative AI agents can transform organizations and tackle specific business challenges, Innovation Managers gain insight into practical applications of cutting-edge technology. Understanding the components of these agents and strategic planning for AI impact can help them identify new opportunities and champion initiatives that leverage generative AI for significant organizational improvement.
Business Analyst Artificial Intelligence
A Business Analyst Artificial Intelligence bridges the gap between business needs and technical AI solutions, identifying opportunities and requirements. This course may be particularly useful for a Business Analyst Artificial Intelligence as it explores how custom generative AI agents can tackle specific business challenges and transform organizations. Understanding the components of these agents and how they combine to build powerful solutions provides insight into AI capabilities. The "Strategy: Planning ahead" module, covering strategic planning for AI integration and impact, directly supports the analyst's role in aligning AI initiatives with business goals and envisioning change with AI solutions.
Chief Technology Officer
A Chief Technology Officer provides strategic leadership for an organization's technological direction, including the adoption and integration of emerging technologies like generative AI. This course may be highly useful for a Chief Technology Officer as it focuses on how generative AI agents can transform an organization and includes a key module on "Strategy: Planning ahead." This module directly addresses strategic planning for AI integration, assessing its impact within the organization, and planning for change with AI solutions to foster a culture of innovation as a leader. Understanding the foundational concepts of generative AI agents and their potential enables CTOs to make informed decisions about technology roadmaps and drive organizational advancement.
User Experience Designer Artificial Intelligence
A User Experience Designer Artificial Intelligence focuses on creating intuitive and effective interactions for AI-powered products and services, including generative AI agents. This course may be useful for a User Experience Designer Artificial Intelligence because it provides insight into how generative AI agents enhance the customer experience and transform organizations. Understanding the collaborative functionality of agent components and how they are built into powerful solutions helps designers anticipate user needs and interaction patterns. The module on strategic planning for AI integration further allows designers to understand the broader impact and context of AI agents, facilitating the creation of user-centric and innovative AI solutions.
Enterprise Architect
An Enterprise Architect designs and oversees the overall structure of an organization's IT systems and processes, ensuring alignment with business strategy. This course may be helpful for an Enterprise Architect, as it focuses on how generative AI agents can transform an organization and addresses strategic planning for AI integration and impact within the enterprise. Understanding the collaborative functionality of generative AI agent components and how they can be combined to build powerful solutions provides architectural insights. This perspective enables architects to incorporate generative AI effectively into the broader enterprise technology landscape, fostering a culture of innovation and managing change with new AI solutions.

Reading list

We haven't picked any books for this reading list yet.
A textbook that presents AI from a computational perspective, covering topics such as agents, knowledge representation, reasoning, and planning. Suitable for readers with a background in computer science or mathematics.
A classic textbook on reinforcement learning, a subfield of AI concerned with learning from interaction with the environment. Covers both theoretical concepts and practical algorithms, with a focus on real-world applications.
A comprehensive textbook that provides a broad overview of the field, covering topics such as problem-solving, learning, machine learning, and natural language processing. Suitable for both beginners and advanced learners.
A highly cited and influential book that focuses on deep learning, a subfield of AI concerned with constructing models for complex data. Covers theoretical concepts, popular algorithms, and practical applications.
A practical guide to natural language processing (NLP) using Python, covering topics such as text classification, sentiment analysis, and machine translation. Suitable for beginners with some programming experience.
A short but powerful book that explores the potential benefits and risks of AI, as well as the ethical dilemmas that need to be addressed as AI becomes more advanced.
A comprehensive German-language textbook that provides a broad overview of AI, covering topics such as search, knowledge representation, and machine learning. Suitable for both beginners and advanced learners.
A French-language textbook that focuses on machine learning, a subfield of AI. Covers topics such as supervised learning, unsupervised learning, and deep learning. Suitable for beginners with some programming experience.
A comprehensive textbook that covers probabilistic graphical models (PGMs), a powerful tool for representing and reasoning about complex systems. Suitable for advanced learners with a background in probability and statistics.
Draws on adult development theory to provide a framework for understanding and facilitating individual and organizational change.
Examines the impact of technological advancements on the future of work and the need for business transformation to adapt to these changes.
Explores the impact of cultural differences on business interactions, providing insights into how to navigate cultural challenges during transformation initiatives.
While presented as a novel, this book foundational text for understanding the importance of IT operations and DevOps principles in enabling business transformation. It illustrates how improving the flow of work in IT can significantly impact the entire organization's performance. It's particularly useful for gaining a practical understanding of how operational improvements contribute to broader transformation goals.

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