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Course Overview

As organizations shift to digital-first strategies, cloud computing has become the backbone of AI and data engineering. This Cloud-Based AI and Data Engineering Training Course provides participants with practical knowledge of building big data pipelines, deploying AI models, and optimizing data workflows on leading cloud platforms.

Participants will explore cloud services for AI, storage, and analytics, learning to design scalable architectures that support innovation. Case studies and labs will illustrate how enterprises use the cloud for real-time data processing, AI-driven insights, and cost-efficient scalability.

By the end of the course, attendees will be able to leverage cloud platforms to integrate data pipelines, deploy machine learning models, and support enterprise-wide AI initiatives.

Course Benefits

• Gain practical skills in cloud-based data engineering

• Deploy AI and machine learning models in the cloud

• Design scalable data pipelines for big data analytics

• Optimize performance and costs with cloud solutions

• Strengthen enterprise AI adoption with cloud strategies

Course Objectives

• Explore cloud services for AI and data engineering

• Build and manage big data pipelines in the cloud

• Apply tools for real-time data streaming and analytics

• Deploy and monitor machine learning models on cloud platforms

• Ensure governance, security, and compliance in cloud AI solutions

• Integrate cloud-based AI into enterprise strategies

• Foster innovation with scalable and flexible architectures

Training Methodology

This course blends instructor-led sessions, case studies, group projects, and hands-on labs with cloud tools. Participants will design and test solutions using real-world datasets and cloud platforms.

Target Audience

• Data engineers and cloud specialists

• AI and machine learning professionals

• IT managers and solution architects

• Business leaders driving digital transformation

Target Competencies

• Cloud AI deployment and management

• Data pipeline engineering

• Big data analytics and streaming

• Secure and scalable cloud architecture

Course Outline

Unit 1: Cloud Fundamentals for AI and Data Engineering

• Cloud computing essentials

• Overview of leading cloud providers (AWS, Azure, GCP)

• Benefits and challenges of cloud adoption

• Case studies of AI in the cloud

Unit 2: Data Engineering in the Cloud

• Designing data pipelines for big data

• Data ingestion, transformation, and storage

• Cloud tools for ETL (Extract, Transform, Load)

• Real-world exercises in pipeline creation

Unit 3: Cloud-Based AI Deployment

• Hosting machine learning models on cloud platforms

• Containerization and serverless deployment

• Monitoring and scaling AI models

• Hands-on lab: deploying a predictive model

Unit 4: Real-Time Analytics and Streaming Data

• Tools for real-time data processing

• AI applications in live data streams

• Case studies of streaming analytics in business

• Practical exercise with streaming datasets

Unit 5: Governance, Security, and Future of Cloud AI

• Data governance in cloud environments

• Compliance and risk management

• Optimizing costs and performance in cloud AI

• Future trends in cloud-based data engineering

Ready to scale AI with the cloud?
Join the Cloud-Based AI and Data Engineering Training Course with EuroQuest International Training and build the skills to power enterprise innovation.