The Cloud-Based AI and Data Engineering training course in Madrid provides professionals with the skills to design, build, and deploy AI solutions and data pipelines in cloud environments.
From:
06-04-2026
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.
The Cloud-Based AI and Data Engineering Training Courses in Madrid provide professionals with an advanced, holistic understanding of how artificial intelligence and modern data engineering practices intersect within cloud environments to power scalable, intelligent, and high-performance data solutions. Designed for data engineers, AI practitioners, cloud architects, and digital transformation leaders, these programs explore the essential tools, frameworks, and methodologies required to build and optimize AI-driven systems in the cloud.
Participants gain in-depth knowledge of cloud-native AI architectures, learning how to design data pipelines, manage distributed data processing workloads, and deploy machine learning models across hybrid or multi-cloud platforms. The courses emphasize end-to-end data engineering workflows—from ingestion and transformation to storage, orchestration, and model deployment—ensuring participants can build robust foundations for AI innovation. Hands-on exercises and real-world case studies allow attendees to work directly with cloud services supporting automation, streaming analytics, real-time processing, and AI model lifecycle management.
These cloud AI and data engineering training programs in Madrid highlight the strategic value of integrating advanced analytics with cloud infrastructure. Participants explore critical topics such as feature engineering at scale, automated MLOps pipelines, serverless computing, and performance optimization for large data workloads. The curriculum also addresses data governance, security, and operational excellence in cloud environments, ensuring that AI solutions remain reliable, compliant, and aligned with organizational objectives.
Attending these training courses in Madrid offers a dynamic and globally connected learning experience enriched by the city’s growing tech ecosystem. Participants benefit from expert instruction, peer collaboration, and exposure to practical use cases across industries. By completing this specialization, professionals will be equipped to architect and manage cloud-based AI systems, streamline data engineering processes, and lead initiatives that drive innovation, efficiency, and competitive advantage in an increasingly data-driven digital landscape.