Euroasia Training Euroasia Training
AR

Data Analytics, Artificial Intelligence and Decision Sciences

Cloud-Based AI and Data Engineering Solutions

5 units

Please select a city/session before registration.

About this program

With the increasing adoption of digital-first strategies, cloud computing has become essential to AI and data engineering. This Cloud-Based AI and Data Engineering Training Course equips participants with hands-on expertise in constructing big data pipelines, deploying AI models, and enhancing data workflows on prominent cloud platforms. Attendees will investigate cloud services related to AI, storage, and analytics, gaining the skills to design scalable architectures that foster innovation. Through case studies and practical labs, learners will understand how organizations leverage the cloud for real-time data processing, AI-driven insights, and cost-effective scalability. Upon completing the course, participants will be proficient in utilizing cloud platforms to integrate data pipelines, implement machine learning models, and support comprehensive AI initiatives across enterprises.

Course benefits

  • Acquire practical expertise in cloud-based data engineering
  • Implement AI and machine learning models within cloud environments
  • Design scalable data pipelines tailored for big data analytics
  • Enhance performance and manage costs through cloud-based solutions
  • Promote enterprise-wide AI adoption utilizing cloud strategies

Key outcomes

  • Examine cloud services applicable to AI and data engineering
  • Develop and oversee big data pipelines using cloud technologies
  • Utilize tools for real-time data streaming and analytics
  • Deploy and supervise machine learning models on cloud infrastructures
  • Maintain governance, security, and compliance in cloud AI implementations
  • Incorporate cloud-based AI into organizational strategies
  • Encourage innovation through scalable and adaptable architectures

Who should attend

  • Data engineers and cloud professionals
  • AI and machine learning specialists
  • IT managers and solution architects
  • Business executives leading digital transformation efforts

Course outline

1

Unit 1: Introduction to Cloud Concepts for AI and Data Engineering

  • Fundamentals of cloud computing
  • Survey of major cloud service providers (AWS, Azure, GCP)
  • Advantages and obstacles in adopting cloud technology
  • Illustrative case studies of AI implementations in cloud settings
2

Unit 2: Cloud-Centric Data Engineering

  • Developing data pipelines for large-scale datasets
  • Processes for data ingestion, transformation, and storage
  • Utilizing cloud-based ETL (Extract, Transform, Load) tools
  • Practical assignments on building data pipelines
3

Unit 3: Deploying AI Solutions on Cloud Platforms

  • Hosting machine learning models within cloud infrastructures
  • Use of containerization and serverless architectures for deployment
  • Techniques for monitoring and scaling AI applications
  • Laboratory session: deploying a predictive analytics model
4

Unit 4: Streaming Data and Real-Time Analytics

  • Technologies for processing data in real time
  • Application of AI in live streaming data environments
  • Business case studies demonstrating streaming analytics
  • Hands-on practice with real-time streaming datasets
5

Unit 5: Cloud AI Governance, Security, and Emerging Trends

  • Managing data governance within cloud platforms
  • Ensuring compliance and mitigating risks
  • Strategies for cost efficiency and performance optimization in cloud AI
  • Exploration of future developments in cloud-based data engineering