Data Analytics and Visualization

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This 5-course specialization focuses on advanced machine learning topics using Google Cloud Platform where you will get hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs. This specialization picks up where “Machine Learning on GCP” left off and teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text. It ends with a course on building recommendation systems. Topics introduced in earlier courses are referenced in later courses, so it is recommended that you take the courses in exactly this order.

This learning path is for application developers who want to enhance their projects with the power of generative AI and accelerate their development workflow. From understanding the core concepts of Gemini, Google's advanced language model, to building end-to-end applications on Google Cloud, this path will guide you through essential techniques and tools. You'll learn how to leverage Gemini Code Assist to streamline your development process, whether you're working with the command-line interface, configuring it for your organization, or kicking off a new project. Finally, dive into hands-on labs to practice what you've learned and earn several skill badges.

This series of courses introduces data in the cloud and Looker to someone who would like to become a Looker Developer. It includes the background on how data is managed in the cloud and how it can be used to create value for an organization. You will then learn the skills you need as a Looker Developer to use the Looker Modeling Language (LookML) to empower your organization to conduct self-serve data exploration, analysis and visualization.

In this specialization, you learn the fundamentals of application development on Google Cloud. Through a combination of presentations and hands-on labs, participants learn best practices for designing cloud applications, the use of service orchestration and choreography to coordinate microservices, and how to use Cloud Functions to develop single-purpose functions that process events within your cloud infrastructure. This class is intended for application developers, architects, and cloud engineers who want to build new cloud applications or redesign existing applications to run on Google Cloud. This course teaches participants the following skills: Understand how to choose the appropriate data storage option for application use cases. Use authentication and authorization to secure an application. Describe use cases for the different Google Cloud compute options for running applications. Describe the benefits and challenges of microservice-based architectures. Describe the advantages of event-driven applications. Identify the strengths of orchestration and choreography. Use Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler to coordinate a microservices application on Google Cloud. Recognize the benefits of and use cases for Cloud Functions in modern application development. Understand how to build, test, and deploy Cloud Functions. Secure and connect Cloud Functions to resources and cloud databases. Use best practices with Cloud Functions.