The Cloud-Based AI and Data Engineering course in Budapest provides professionals with the skills to design and implement AI solutions and data engineering processes in cloud environments.
From:
20-07-2026
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 Budapest provide professionals with the technical and strategic competencies needed to design, deploy, and manage scalable data pipelines and artificial intelligence solutions in cloud environments. Designed for data engineers, cloud architects, machine learning developers, and digital transformation leaders, these programs focus on how modern organizations can leverage cloud platforms to support advanced analytics, automated workflows, and intelligent decision-making at scale.
Participants explore the core principles of cloud-based AI architecture, including distributed data processing, data lakes and warehouses, containerization, orchestration, and machine learning model deployment. The courses emphasize how leading cloud platforms—such as AWS, Azure, and Google Cloud—enable dynamic data integration, real-time analytics, and seamless delivery of AI services across organizational operations. Through hands-on labs and real-world case studies, attendees learn how to configure data pipelines, optimize storage solutions, implement ETL/ELT processes, and operationalize AI models within cloud infrastructure.
These cloud and data engineering training programs in Budapest also address key governance and operational considerations, including cost optimization, scalability planning, data security, compliance frameworks, and performance monitoring. The curriculum highlights the importance of collaboration between data engineering, analytics, and business teams to ensure that cloud-based AI solutions deliver measurable value and align with strategic objectives.
Participants practice using automation tools, API integrations, workflow schedulers, and MLOps platforms to streamline development, deployment, and lifecycle management of machine learning applications.
Attending these training courses in Budapest offers a collaborative learning environment enriched by the city’s growing technology and innovation ecosystem. Professionals engage with instructors and peers from diverse sectors, fostering shared insights and best practices.
By completing this specialization, participants will be equipped to build and manage cloud-centered AI and data engineering systems that enhance organizational efficiency, analytical capability, and digital agility. They will be prepared to lead initiatives that support scalable, resilient, and intelligence-driven operations in a rapidly evolving data-centric landscape.