Módulos

This certification program combines two levels of training at Amazon Web Services (AWS):

• AWS CERTIFIED Cloud Practitioner (CLF-C02): Introduction to the fundamental concepts of cloud computing, AWS global infrastructure and billing models
• AWS Certified Data Engineering - Associate (DEA -C01): Design, implementation and optimization of Data pipes on AWS for Big Data, Machine Learning and advanced analysis environments
• 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, applying concepts from the introduction to the cloud to the advanced data management in AWS
• At the end, they will be prepared to perform as Cloud Engineer, Data Engineer or Big Data Specialist, in addition to approving both certification exams

At the end of the course, participants will be able to:

• Understand AWS infrastructure, its main services and its price philosophy
• Implement safety and compliance measures on AWS, including IAM and data encryption
• Design and implement scalable data pipes on AWS, optimizing intake, processing and storage
• Configure and manage Databases on AWS, including Amazon RDS, Dynamodb and Redshift
• Automatize ETL processes in AWS, using AWS GUE, Step Functions and Lambda
• Optimize cloud architectures, ensuring high availability and cost efficiency
• Monitor and analyze data in real time, using kinesis, athena and quicksight
• Prepare for AWS CERTIFIED CLOUD CERTIFICATIONS Practitioner and AWS Certified Data Engineering - Associate, ensuring the mastery of the issues evaluated

To participate in this training, attendees must meet the following requirements:

• Basic technical knowledge in information technologies.
• Familiarity with databases and SQL language.
• Prior experience in AWS is not required, but it is recommended to have knowledge in IT infrastructure.

These requirements ensure that participants can focus on the practical application of the concepts, from the foundations to the analysis of cloud data.

Learning Methodology

The learning methodology, regardless of the modality (in-person or remote), is based on the development of workshops or labs that lead to the construction of a project, emulating real activities in a company.

The instructor (live), a professional with extensive experience in work environments related to the topics covered, acts as a workshop leader, guiding students' practice through knowledge transfer processes, applying the concepts of the proposed syllabus to the project.

The methodology seeks that the student does not memorize, but rather understands the concepts and how they are applied in a work environment.

As a result of this work, at the end of the training the student will have gained real experience, will be prepared for work and to pass an interview, a technical test, and/or achieve higher scores on international certification exams.

Conditions to guarantee successful results:

• a. An institution that requires the application of the model through organization, logistics, and strict control over the activities to be carried out by the participants in each training session.
• b. An instructor located anywhere in the world, who has the required in-depth knowledge, expertise, experience, and outstanding values, ensuring a very high-level knowledge transfer.
• c. A committed student, with the space, time, and attention required by the training process, and the willingness to focus on understanding how concepts are applied in a work environment, and not memorizing concepts just to take an exam.

Pre-enrollment

You do not need to pay to pre-enroll. By pre-enrolling, you reserve a spot in the group for this course or program. Our team will contact you to complete your enrollment.

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