AI in the Cloud: Azure, Google, and Beyond
Introduction
Artificial Intelligence (AI) has moved beyond experimentation and is now the foundation of business transformation. Cloud platforms such as **Microsoft Azure**, **Google Cloud Platform (GCP)**, and others have democratized access to AI by providing scalable infrastructure, ready-to-use AI services, and powerful machine learning tools. Organizations no longer need massive on-premise systems—cloud-based AI enables them to **innovate faster, reduce costs, and scale solutions globally**.
This program equips professionals with the knowledge and practical insights needed to leverage cloud AI platforms for strategic advantage, from **data preparation and model deployment to governance and innovation**.
Objectives
By the end of this program, participants will be able to:
* Understand the fundamentals of AI in cloud environments.
* Compare AI capabilities across Azure, Google Cloud, and other platforms.
* Design cloud-based AI architectures for enterprise needs.
* Apply pre-built AI services for automation, analytics, and customer experience.
* Manage AI workloads securely and ethically.
* Build a roadmap for scaling AI initiatives in the cloud.
Who Should Attend
* Business Leaders & Strategists exploring AI adoption.
* IT Managers & Cloud Architects.
* Data Scientists & AI Engineers.
* Compliance, Governance, and Risk Professionals.
* Entrepreneurs and Innovators leveraging AI for scale.
Methodology
* Interactive Lectures & Expert Case Studies.
* Hands-on Demonstrations with Azure AI and Google AI Services.
* Group Workshops on Cloud AI Strategy.
* Real-World Case Simulations for Deployment.
* Action Planning for Organizational AI Readiness.
Course Outline
Day 1: AI in the Cloud Landscape
* Cloud AI: Evolution and Opportunities.
* Microsoft Azure AI vs. Google Cloud AI vs. AWS AI.
* Core services: Vision, Language, Speech, and Decision AI APIs.
* Introduction to Machine Learning in the Cloud.
Day 2: Microsoft Azure AI in Action
* Azure Cognitive Services.
* Azure Machine Learning Studio and MLOps.
* Integrating AI with Azure Data Services.
* Case Study: Enterprise AI on Azure.
Day 3: Google Cloud AI and Vertex AI
* GCP AI Services Overview.
* Vertex AI: Unified ML Platform.
* AutoML and Pre-trained Models.
* Case Study: Scalable AI Deployment on Google Cloud.
Day 4: Advanced AI in the Cloud
* Hybrid and Multi-Cloud AI Architectures.
* Ethical AI and Governance in Cloud Environments.
* Security, Compliance, and Responsible AI Practices.
* Building Cloud AI Centers of Excellence.
Day 5: The Future of AI in the Cloud
* AI + Cloud: Emerging Trends.
* Generative AI in Cloud Platforms.
* Cloud AI for Sustainability and ESG.
* Personal Action Planning: AI Strategy for Your Organization.
Key Takeaways
* Deep understanding of leading cloud AI platforms.
* Practical tools for deploying scalable AI solutions.
* Insights on governance, risk, and compliance in AI adoption.
* A roadmap to align cloud AI with business objectives.
Enquiries and Registration
Enquiry at : admin@keleaders.com
Whatsapp: 0044 790 125 9494
For more details visit our website : www.keleaders.com
