Certifications

Business-level preparation focused on Google Cloud's official Generative AI Leader blueprint.

Associate-level preparation for Google Cloud Associate Cloud Engineer. Covers: Setting up a cloud solution environment; Planning and configuring cloud solutions; Deploying and implementing a cloud solution; Ensuring successful operation of a cloud solution.

Professional-level preparation for designing, developing, and managing robust, secure, scalable, and dynamic solutions on Google Cloud.

Professional-level preparation for Google Cloud Professional Data Engineer. Covers: Designing data processing systems; Ingesting and processing the data; Storing the data; Preparing and using data for analysis; Maintaining and automating data workloads.

Google's Professional Machine Learning Engineer certification validates the ability to design, build, productionize, and optimize ML solutions on Google Cloud, including generative AI on foundation models. Six domains span low-code AI, data and model collaboration, scaling prototypes, serving, automating pipelines, and monitoring.

Practitioner-level preparation for AI/ML on AWS, including foundation models, generative AI on Bedrock and SageMaker, prompt engineering, responsible AI, and AI security/governance. Targets candidates with up to ~6 months of AI/ML exposure.

Foundational-level preparation for understanding AWS Cloud value, security, core services, and billing. Validates broad AWS knowledge for non-technical and early-career candidates.

Associate-level preparation for AWS Certified Developer - Associate. Covers: Development with AWS Services; Security; Deployment; Troubleshooting and Optimization.

Specialty-level preparation for AWS Certified Machine Learning - Specialty. Covers: Data Engineering; Exploratory Data Analysis; Modeling; Machine Learning Implementation and Operations.

Associate-level preparation for designing secure, resilient, high-performing, and cost-optimized AWS architectures. Validates 1+ year of hands-on AWS solution-design experience.

Foundational-level preparation for Microsoft Azure AI Fundamentals. Covers: Artificial Intelligence workloads and considerations; fundamental principles of machine learning on Azure; features of computer vision workloads on Azure; features of Natural Language Processing (NLP) workloads on Azure; features of generative AI workloads on Azure.

Foundational-level preparation for understanding cloud concepts, core Azure architecture and services, and Azure management and governance. Validates broad Azure knowledge for non-technical and early-career candidates.

Foundational-level preparation for Microsoft security, compliance, and identity (SCI) concepts and the Microsoft Entra, Microsoft security, and Microsoft Purview compliance solution families.

Associate-level preparation for Salesforce platform administration in Lightning Experience: configuration and setup, Object Manager and Lightning App Builder, sales and service applications, productivity, data and analytics, and Flow-based process automation.