Data Engineering & Api Development Training Course: Data As Apis

Introduction

Transform your data into accessible services with our Data Engineering and API Development Training Course. This program is designed to equip you with the essential skills to make data available via APIs, enabling you to build scalable and interoperable data-driven applications. In today's interconnected world, mastering API development for data engineering is crucial for organizations seeking to democratize data access and drive innovation. Our data API training course offers hands-on experience and expert guidance, empowering you to create robust and efficient data APIs.

This data as APIs training delves into the core concepts of API development for data engineering, covering topics such as RESTful APIs, data serialization, and API security. You'll gain expertise in using industry-standard tools and techniques to make data available via APIs, meeting the demands of modern data-intensive environments. Whether you're a data engineer, backend developer, or systems architect, this Data Engineering and API Development course will empower you to build and maintain efficient and secure data APIs.

Target Audience:

• Data Engineers
• Backend Developers
• Systems Architects
• API Developers
• Data Scientists
• Cloud Engineers
• Anyone needing data API development skills

Course Objectives:

• Understand the fundamentals of data engineering and API development.
• Master RESTful API design and implementation for data services.
• Utilize data serialization formats (JSON, Avro, Protobuf) for API responses.
• Implement API authentication and authorization mechanisms.
• Design and build scalable and performant data APIs.
• Optimize API performance for data retrieval and delivery.
• Troubleshoot and address common issues in data API development.
• Implement API documentation and versioning strategies.
• Integrate data APIs with various data sources and applications.
• Understand how to handle large-scale data API deployments.
• Explore advanced API patterns for data engineering (e.g., GraphQL, event-driven APIs).
• Apply real world use cases for data APIs in data engineering.
• Leverage API development tools and frameworks for efficient implementation.

Duration

10 Days

Course content

Module 1: Introduction to Data APIs

• Fundamentals of data engineering and API development.
• Overview of RESTful APIs, data serialization, and API security.
• Setting up an API development environment.
• Introduction to API development tools and frameworks.
• Best practices for data API development.

Module 2: RESTful API Design and Implementation

• Mastering RESTful API design and implementation for data services.
• Utilizing HTTP methods and status codes.
• Implementing API endpoints for data retrieval and manipulation.
• Designing and building RESTful data APIs.
• Best practices for RESTful API design.

Module 3: Data Serialization Formats

• Utilizing data serialization formats (JSON, Avro, Protobuf) for API responses.
• Implementing JSON serialization for web APIs.
• Utilizing Avro and Protobuf for high-performance data APIs.
• Designing data serialization strategies.
• Best practices for data serialization.

Module 4: API Authentication and Authorization

• Implementing API authentication and authorization mechanisms.
• Utilizing OAuth 2.0 and API keys.
• Designing and building secure API authentication systems.
• Optimizing authorization for data access control.
• Best practices for API security.

Module 5: Scalable Data API Development

• Designing and building scalable and performant data APIs.
• Utilizing API caching and load balancing.
• Implementing asynchronous API processing.
• Designing scalable API architectures.
• Best practices for API scalability.

Module 6: API Performance Optimization

• Optimizing API performance for data retrieval and delivery.
• Utilizing API performance monitoring tools.
• Implementing data compression and pagination.
• Designing efficient data retrieval strategies.
• Best practices for API performance.

Module 7: Troubleshooting API Development

• Troubleshooting and addressing common issues in data API development.
• Analyzing API logs and error messages.
• Utilizing debugging techniques for problem resolution.
• Resolving common API errors.
• Best practices for troubleshooting.

Module 8: API Documentation and Versioning

• Implementing API documentation and versioning strategies.
• Utilizing OpenAPI and Swagger for API documentation.
• Designing and building API versioning systems.
• Optimizing API documentation for developer usability.
• Best practices for API documentation.

Module 9: Integration with Data Systems

• Integrating data APIs with various data sources and applications.
• Utilizing API gateways and service meshes.
• Implementing data API integration with other systems.
• Designing efficient data integration strategies.
• Best practices for integration.

Module 10: Large-Scale API Deployments

• Understanding how to handle large-scale data API deployments.
• Utilizing containerization and orchestration (Docker, Kubernetes).
• Implementing API deployment strategies.
• Designing scalable API deployment architectures.
• Best practices for large scale deployments.

Module 11: Advanced API Patterns

• Exploring advanced API patterns for data engineering (GraphQL, event-driven APIs).
• Utilizing GraphQL for flexible data retrieval.
• Implementing event-driven APIs for real-time data streaming.
• Designing and building advanced API solutions.
• Optimizing advanced patterns for specific applications.
• Best practices for advanced APIs.

Module 12: Real-World Use Cases

• Implementing data APIs for e-commerce data platforms.
• Utilizing data APIs for financial transaction systems.
• Implementing data APIs for IoT data streams.
• Utilizing data APIs for social media data access.
• Best practices for real-world applications.

Module 13: API Tools Implementation

• Utilizing API development tools and frameworks (Flask, FastAPI, Spring Boot).
• Implementing data APIs with specific tools.
• Designing and building automated API workflows.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: API Monitoring and Metrics

• Implementing API monitoring and metrics.
• Utilizing API performance monitoring tools.
• Designing and building API dashboards.
• Optimizing monitoring for real-time insights.
• Best practices for monitoring.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.