Transforming Aspiring Tech Apprentices into Industry-Ready Professionals
Transforming Aspiring Tech Apprentices into Industry-Ready Professionals
A Cloud Security Engineer allows organizations to design and implement secure workloads and infrastructure on Google Cloud. Through an understanding of security best practices and industry requirements, this individual designs, develops, and manages a secure solution by using Google security technologies. A Cloud Security Engineer is proficient in identity and access management, defining the resource hierarchy and policies, using Google Cloud technologies to provide data protection, configuring network security defenses, monitoring environments for threats, configuring security automation, securing AI workloads, securing the software supply chain, and enforcing regulatory controls.
A Cloud Digital Leader can articulate the capabilities of Google Cloud core products and services and how they benefit organizations. They can also describe common business use cases and how cloud solutions support an enterprise. This certification is for anyone who wishes to demonstrate their knowledge of cloud computing basics and how Google Cloud products and services can be used to achieve an organization’s goals.
A GCP Cloud Engineer is an IT professional specializing in Google Cloud Platform (GCP), focusing on designing, implementing, and managing cloud solutions. They use GCP services and tools to deploy applications, monitor operations, and maintain enterprise solutions. They are responsible for tasks like planning, configuring, and deploying solutions, as well as managing and examining billing of GCP resources
Learn to efficiently manage and optimize Google Workspace for your organization. This course covers user management, security settings, and best practices to ensure smooth operations and collaboration. Perfect for aspiring or current IT administrators.
Explore the essentials of Google Cloud with our Data Practitioner course! Designed for beginners, this course will guide you through the fundamentals of data management and analysis using Google Cloud tools. Gain practical skills and confidence to harness the power of cloud technology for your data needs.
A Google Cloud Architect designs, develops, and manages robust, secure, scalable, and dynamic cloud solutions using Google Cloud technologies. They are skilled in enterprise cloud strategy, solution design, and architectural best practices. This role requires proficiency in various aspects of cloud computing, including multi-tiered distributed applications and hybrid environments
Master the skills to design, manage, and optimize databases on Google Cloud. This course equips you with the knowledge to handle cloud-based data solutions, ensuring efficiency and scalability for your projects. Perfect for aspiring database engineers looking to enhance their expertise in Google Cloud technologies.
Unlock the power of Google Cloud with our Google Cloud Developer course! Dive into cloud computing, learn to build and deploy applications, and master tools like Kubernetes and Firebase. Perfect for developers eager to enhance their skills and innovate in the cloud.
A Professional Data Engineer makes data usable and valuable for others by collecting, transforming, and publishing data. This individual evaluates and selects products and services to meet business and regulatory requirements. A Professional Data Engineer creates and manages robust data processing systems. This includes the ability to design, build, deploy, monitor, maintain, and secure data processing workloads
A Professional Cloud DevOps Engineer implements processes and capabilities throughout the systems development lifecycle using Google-recommended methodologies and tools. They enable efficient software and infrastructure delivery while balancing reliability with delivery speed. They optimize and maintain production systems and services.
A Professional Cloud Network Engineer is responsible for the design, implementation, and management of Google Cloud network infrastructure. This includes designing network architectures for high availability, scalability, resiliency, and security. This individual is skilled in configuring and managing Virtual Private Clouds (VPCs), routing, network security services, load balancing, and Cloud DNS. Additionally, they are proficient in setting up hybrid connectivity through Cloud Interconnect and Cloud VPN. Their expertise extends to diagnosing, monitoring, and troubleshooting network operations by using Google Cloud Observability and the Network Intelligence Center.
A Professional Machine Learning Engineer builds, evaluates, productionizes, and optimizes AI solutions by using Google Cloud capabilities and knowledge of conventional ML approaches. The ML Engineer handles large, complex datasets and creates repeatable, reusable code. The ML Engineer designs and operationalizes generative AI solutions based on foundational models. The ML Engineer considers responsible AI practices, and collaborates closely with other job roles to ensure the long-term success of AI-based applications. The ML Engineer has strong programming skills and experience with data platforms and distributed data processing tools. The ML Engineer is proficient in the areas of model architecture, data and ML pipeline creation, generative AI, and metrics interpretation. The ML Engineer is familiar with foundational concepts of MLOps, application development, infrastructure management, data engineering, and data governance. The ML Engineer enables teams across the organization to use AI solutions. By training, retraining, deploying, scheduling, monitoring, and improving models, the ML Engineer designs and creates scalable, performant solutions.