Course Modules
Módulo I: Bienvenido a AWS Academy Data Engineering
- Requisitos previos y objetivos del curso
- Resumen del curso
Módulo II: Organizaciones basadas en datos
- Decisiones basadas en datos
- El canal de datos: infraestructura para decisiones basadas en datos
- El papel del ingeniero de datos en las organizaciones basadas en datos
- Estrategias de datos modernas
- Laboratorio: Acceso y análisis de datos mediante Amazon S3
- Verificación de conocimientos
Módulo III: Los elementos de los datos
- Las cinco V de los datos: volumen, velocidad, variedad, veracidad y valor
- Volumen y velocidad
- Variedad tipos de datos
- Variedad fuentes de datos
- Veracidad y valor
- Actividades para mejorar la veracidad y el valor
- Actividad: Planificación de su canalización
- Verificación de conocimientos
Módulo IV: Principios y patrones de diseño para canalizaciones de datos
- Marco y lentes de buena arquitectura de AWS
- Actividad: Uso del marco de buena arquitectura
- La evolución de las arquitecturas de datos
- Arquitectura de datos moderna en AWS
- Canalización de arquitectura de datos moderna: ingesta y almacenamiento
- Canalización de arquitectura de datos moderna: procesamiento y consumo
- Canalización de análisis de streaming
- Laboratorio: Consulta de datos mediante Athena - Verificación de conocimientos
Módulo V: Asegurar y escalar la canalización de datos
- Revisión de seguridad en la nube
- Seguridad de las cargas de trabajo de análisis
- Seguridad del aprendizaje automático
- Escalado: descripción general
- Crear una infraestructura escalable
- Creación de componentes escalables
- Verificación de conocimientos
Módulo VI: Ingesta y preparación de datos
- Comparación de ETL y ELT
- Introducción a la manipulación de datos
- Descubrimiento de datos
- Estructuración de datos
- Limpieza de datos
- Enriquecimiento de datos
- Validación de datos
- Publicación de datos
- Verificación de conocimientos
Módulo VII: Ingesta por lote o por flujo
- Comparación de la ingesta de lotes y flujos
- Procesamiento de ingesta por lotes
- Herramientas de ingesta diseñadas específicamente
- AWS Glue para procesamiento de ingesta por lotes
- Consideraciones de escala para el procesamiento por lotes
- Laboratorio: realización de ETL en un conjunto de datos mediante AWS Glue
- Kinesis para procesamiento de flujos
- Consideraciones de escala para el procesamiento de flujos
- Ingesta de datos de IoT por flujo
- Verificación de conocimientos
Módulo VIII: Almacenamiento y organización de datos
- Almacenamiento en la arquitectura de datos moderna
- Almacenamiento en lago de datos
- Almacenamiento de datos
- Bases de datos diseñadas específicamente
- Almacenamiento en apoyo pipeline
- Almacenamiento seguro
- Laboratorio: Almacenamiento y análisis de datos mediante Amazon Redshift
- Verificación de conocimientos
Módulo IX: Procesamiento de Big Data
- Conceptos de procesamiento de big data
- Apache Hadoop
- Apache chispa
- Amazon EMR
- Administrar sus clústeres de Amazon EMR
- Laboratorio: procesamiento de registros mediante Amazon EMR
- Apache Hudi - Laboratorio: Actualización de datos dinámicos in sitio
- Verificación de conocimientos
Módulo X: Procesamiento de datos para ML
- Conceptos de ML
- El ciclo de vida del ML
- Enmarcar el problema del ML para alcanzar el objetivo empresarial
- Recolectando datos
- Aplicar etiquetas a datos de entrenamiento con objetivos conocidos
- Actividad: Etiquetado con SageMaker Ground Truth
- Preprocesamiento de datos
- Ingeniería de características
- Desarrollar un modelo
- Implementación de un modelo
- Infraestructura de aprendizaje automático en AWS
- Creador de sabios
- Demostración: preparación de datos y entrenamiento de un modelo con SageMaker
- Demostración: preparación de datos y entrenamiento de un modelo con SageMaker Canvas
- Servicios de IA/ML en AWS
Módulo XI: Análisis y visualización de datos
- Considerar los factores que influyen en la selección de herramientas
- Comparación de herramientas y servicios de AWS
- Demostración: análisis y visualización de datos con AWS IoT Analytics y QuickSight
- Selección de herramientas para un caso de uso de análisis de juegos
- Laboratorio: Análisis y visualización de datos en streaming con Kinesis Data Firehose, OpenSearch Service y paneles de OpenSearch
- Verificación de conocimientos
Módulo XII: Automatización del proceso
- Automatización de la implementación de infraestructura
- CI/CD
- Automatización con funciones escalonadas
- Laboratorio: Creación y orquestación de canalizaciones ETL mediante el uso de Athena y funciones de paso
- Verificación de conocimientos
Módulo XIII: Un puente hacia la certificación
- Descripción general de la certificación AWS
Current process description
The AWS Certified Data Engineering - Associate (DEA-C01) course is designed to provide practical skills in the design, implementation and optimization of data pipes on AWS.
Under the practical Learning Method approach, participants will receive a cloud entrance pack to apply the concepts through workshops, laboratories and projects in real environments, and will use tools such as AWS GUE, Amazon Redshift, Kinesis, Dynamodb, SageMaker and AWS EMR. They will learn to design storage, processing and data analysis solutions for Big Data environments, Business Intelligence and Machine Learning.
This course is aimed at data engineers, data analysts, data scientists and ETL professionals who wish to be certified as AWS Certified Data Engineer Associate and develop key competitions in the cloud.
Objectives
At the end of the course, participants will be able to:
- Understand the infrastructure and AWS services for data, such as Amazon S3, RDS, Dynamodb, Redshift and Gue
- Design and implement data pipes, optimizing intake, processing and storage
- Apply principles of data safety and governance, ensuring compliance with regulations
- Scale data solutions on AWS, implementing high -performance and low -cost architectures
- Automatize ETL processes in AWS, using AWS GUE, Step Functions and Lambda
- Optimize the performance in Big Data environments, with AWS EMR and Apache Spark
- Implement data analysis solutions, integrating Amazon Athena, Quicksight and Kinesis
- Prepare for AWS Certified Data Engineering - Associate certification, validating the mastery of the best data engineering practices in AWS
Prerequisites
Preferred schedule
To participate in this training, attendees must meet the following requirements:
- Holding the AWS Certified Cloud Practitioner certification or demonstrating equivalent experience in AWS
- Basic knowledge in databases and SQL language
- Familiarity with concepts of storage, processing, and data analysis
- These requirements ensure that participants can focus on applying knowledge acquired in real data environments
What Does This Course Include?
| Our Value Proposition | Benefit for Participant or Company |
|---|---|
| International Certification AWS Certified Data Engineer - Associate | 40 hours |
| • E-learning reinforcement topics and exclusive materials and simulators | • Complementary platform with digital resources, study guides, support recordings and exam simulators. |
| • Flexible educational model (in-person or live remote) | • Possibility to choose modality without losing human interaction and teaching support. |
| • Focus on employability and professional performance and exam preparation. | • Preparation oriented to certification, job performance and professional scaling based on practice, enhanced with AI support. |
| • Integration of Artificial Intelligence in learning | • Students use AI tools to reinforce understanding, practice exams and enhance their productivity. |
| • International Certification included | • Official endorsement with global recognition. Includes certification exams and access to the partner platform. |
| • Laboratories in real learning environments. | • Unlimited practical experience with real lab accounts and access to professional cloud infrastructure. |
| • Live classes with certified expert instructors. | • Guided and personalized training with direct real-time support, not offline. Recorded classes only for review. |
| • Personalized attention, small groups. | • Individual tracking, progress evaluations and technical support during training. AI-proctored performance examiner. |
| • Post-certification support and extended access to resources | • Post-assistance, access to materials for and continuous updates. |
| • Practical methodology and real and/or simulated projects. | • Applied learning from day one: simulations, business cases, projects and real cloud environments. |
| • Certificates of Approval and/or participation. | • International Certification by AWS ACADEMY MEMBER INSTITUTION
• Infinity Training Institute USA: International Certification Diploma in English • Aula Matriz IETDH Colombia - Certificate of participation |
Why choose Infinity Training Institute?
1. Internationally guaranteed certifications
All our courses are Internationally certified:
- Infinity Training Institute USA: International Certification Diploma in English.
- International Certification from our partners Microsoft, Oracle, Certitalents, AWS, PMI, Cisco, etc.
2. We are not an automatic platform, nor self-study through videos
We are a unique model, in-person or Remote modality (with live instructor). Technology + pedagogy + AI + expert instructors + real practice — not self-study or outdated content.
3. Training designed for today's job market
Experience applicable immediately in interviews, technical tests and real work environments.
4. Real or simulated projects with international standards
Students access real environments such as Azure, AWS, Google Cloud, Oracle Cloud, develop real or simulated projects, building a demonstrable technical portfolio depending on the type of course or certification they have chosen.
5. A unique combination in Latin America and the USA
Certification + real practice + AI + continuous support + dual diploma.
6. Proven results
More than 95% of our graduates obtain official certification and improve professionally in less than six months.
7. Competency level guarantee
If the student during the practical training process does not reach a minimum performance level of 75%, they must repeat the course if the instructor determines so, and the student has shown the commitment and minimum class attendance required by the model.
Your professional future starts here
At Infinity Training Institute we boost your growth with an innovative, flexible model focused on real learning and performance evaluation. Certified instructors, intensive practice, integrated AI and constant support: world-class training.
All our courses are Internationally certified:
- Infinity Training Institute USA: International Certification Diploma in English.
- International Certification from our partners Microsoft, Oracle, Certitalents, AWS, PMI, Cisco, etc.
2. We are not an automatic platform, nor self-study through videos
We are a unique model, in-person or Remote modality (with live instructor). Technology + pedagogy + AI + expert instructors + real practice — not self-study or outdated content.
3. Training designed for today's job market
Experience applicable immediately in interviews, technical tests and real work environments.
4. Real or simulated projects with international standards
Students access real environments such as Azure, AWS, Google Cloud, Oracle Cloud, develop real or simulated projects, building a demonstrable technical portfolio depending on the type of course or certification they have chosen.
5. A unique combination in Latin America and the USA
Certification + real practice + AI + continuous support + dual diploma.
6. Proven results
More than 95% of our graduates obtain official certification and improve professionally in less than six months.
7. Competency level guarantee
If the student during the practical training process does not reach a minimum performance level of 75%, they must repeat the course if the instructor determines so, and the student has shown the commitment and minimum class attendance required by the model.
Your professional future starts here
At Infinity Training Institute we boost your growth with an innovative, flexible model focused on real learning and performance evaluation. Certified instructors, intensive practice, integrated AI and constant support: world-class training.
Learning Methodology
At Infinity Training Institute, we apply a comprehensive, ever-evolving methodology centered on practical learning, powered by Artificial Intelligence, enabling personalized instruction, performance assessment, and optimized preparation for international certifications with certified instructors, real labs, simulators, and e-learning platforms. Participants learn by doing, developing technical and professional skills in small groups, with personalized follow-up and pre and post-certification support. Infinity Training Institute: Learn. Apply. Get Certified. Transcend.
Current process description
The AWS Certified Data Engineering - Associate (DEA-C01) course is designed to provide practical skills in the design, implementation and optimization of data pipes on AWS.
Under the practical Learning Method approach, participants will receive a cloud entrance pack to apply the concepts through workshops, laboratories and projects in real environments, and will use tools such as AWS GUE, Amazon Redshift, Kinesis, Dynamodb, SageMaker and AWS EMR. They will learn to design storage, processing and data analysis solutions for Big Data environments, Business Intelligence and Machine Learning.
This course is aimed at data engineers, data analysts, data scientists and ETL professionals who wish to be certified as AWS Certified Data Engineer Associate and develop key competitions in the cloud.
Objectives
At the end of the course, participants will be able to:
- Understand the infrastructure and AWS services for data, such as Amazon S3, RDS, Dynamodb, Redshift and Gue
- Design and implement data pipes, optimizing intake, processing and storage
- Apply principles of data safety and governance, ensuring compliance with regulations
- Scale data solutions on AWS, implementing high -performance and low -cost architectures
- Automatize ETL processes in AWS, using AWS GUE, Step Functions and Lambda
- Optimize the performance in Big Data environments, with AWS EMR and Apache Spark
- Implement data analysis solutions, integrating Amazon Athena, Quicksight and Kinesis
- Prepare for AWS Certified Data Engineering - Associate certification, validating the mastery of the best data engineering practices in AWS
Prerequisites
Preferred schedule
To participate in this training, attendees must meet the following requirements:
- Holding the AWS Certified Cloud Practitioner certification or demonstrating equivalent experience in AWS
- Basic knowledge in databases and SQL language
- Familiarity with concepts of storage, processing, and data analysis
- These requirements ensure that participants can focus on applying knowledge acquired in real data environments
What Does This Course Include?
| Our Value Proposition | Benefit for Participant or Company |
|---|---|
| International Certification AWS Certified Data Engineer - Associate | 40 hours |
| • E-learning reinforcement topics and exclusive materials and simulators | • Complementary platform with digital resources, study guides, support recordings and exam simulators. |
| • Flexible educational model (in-person or live remote) | • Possibility to choose modality without losing human interaction and teaching support. |
| • Focus on employability and professional performance and exam preparation. | • Preparation oriented to certification, job performance and professional scaling based on practice, enhanced with AI support. |
| • Integration of Artificial Intelligence in learning | • Students use AI tools to reinforce understanding, practice exams and enhance their productivity. |
| • International Certification included | • Official endorsement with global recognition. Includes certification exams and access to the partner platform. |
| • Laboratories in real learning environments. | • Unlimited practical experience with real lab accounts and access to professional cloud infrastructure. |
| • Live classes with certified expert instructors. | • Guided and personalized training with direct real-time support, not offline. Recorded classes only for review. |
| • Personalized attention, small groups. | • Individual tracking, progress evaluations and technical support during training. AI-proctored performance examiner. |
| • Post-certification support and extended access to resources | • Post-assistance, access to materials for and continuous updates. |
| • Practical methodology and real and/or simulated projects. | • Applied learning from day one: simulations, business cases, projects and real cloud environments. |
| • Certificates of Approval and/or participation. | • International Certification by AWS ACADEMY MEMBER INSTITUTION
• Infinity Training Institute USA: International Certification Diploma in English • Aula Matriz IETDH Colombia - Certificate of participation |
Why choose Infinity Training Institute?
1. Internationally guaranteed certificationsAll our courses are Internationally certified:
- Infinity Training Institute USA: International Certification Diploma in English.
- International Certification from our partners Microsoft, Oracle, Certitalents, AWS, PMI, Cisco, etc.
2. We are not an automatic platform, nor self-study through videos
We are a unique model, in-person or Remote modality (with live instructor). Technology + pedagogy + AI + expert instructors + real practice — not self-study or outdated content.
3. Training designed for today's job market
Experience applicable immediately in interviews, technical tests and real work environments.
4. Real or simulated projects with international standards
Students access real environments such as Azure, AWS, Google Cloud, Oracle Cloud, develop real or simulated projects, building a demonstrable technical portfolio depending on the type of course or certification they have chosen.
5. A unique combination in Latin America and the USA
Certification + real practice + AI + continuous support + dual diploma.
6. Proven results
More than 95% of our graduates obtain official certification and improve professionally in less than six months.
7. Competency level guarantee
If the student during the practical training process does not reach a minimum performance level of 75%, they must repeat the course if the instructor determines so, and the student has shown the commitment and minimum class attendance required by the model.
Your professional future starts here
At Infinity Training Institute we boost your growth with an innovative, flexible model focused on real learning and performance evaluation. Certified instructors, intensive practice, integrated AI and constant support: world-class training.
Learning Methodology
At Infinity Training Institute, we apply a comprehensive, ever-evolving methodology centered on practical learning, powered by Artificial Intelligence, enabling personalized instruction, performance assessment, and optimized preparation for international certifications with certified instructors, real labs, simulators, and e-learning platforms. Participants learn by doing, developing technical and professional skills in small groups, with personalized follow-up and pre and post-certification support. Infinity Training Institute: Learn. Apply. Get Certified. Transcend.