Why take this course
If you’re an architect, a designer, or simply someone who wants to build modern and reliable Big Data systems, this course is for you. You’ll learn a practical approach to designing solutions based on the AWS platform. You’ll gain the knowledge to leverage key services to create scalable and cost-optimized systems. This will enable you to build advanced Data Lake architectures and monitor and audit their performance.
What you'll learn
- The core concepts of cloud computing and the AWS platform.
- The “Well-Architected Framework” and its pillars (operational excellence, security, reliability, performance efficiency, cost optimization).
- How to configure an Amazon EMR cluster and process data in real time.
- You’ll master creating ETL processes using AWS Glue and analyzing data with Amazon Redshift.
- How to design, build, and manage modern Big Data systems.
Certification & Exam
Upon completion of the training, you will receive a certificate of participation, confirming your skills in Big Data systems design on the AWS platform. There is no final exam—all you need is active participation in the classes.
Who is this course for
This course is designed for anyone involved in the process of designing and building system architectures. It’s ideal for designers and architects who already have experience building complex systems and want to migrate them to a cloud environment.
Topics covered
- Introduction to cloud computing
- AWS basics:
- Basic concepts
- AWS products
- Introduction to environment design
- Creating systems with high availability
- Scaling of environments
- Automation
- “Well-Architected Framework” – a tool for designing environments on AWS, according to the main pillars:
- Interoperability
- Security
- Reliability
- Efficiency
- Cost optimization
- Designing Big Data systems on the AWS platform
- Amazon EMR cluster configuration
- Data storage on the AWS platform
- Real-time data processing with Apache Spark and Amazon Kinesis
- Application of Apache Pig, Hive in Amazon EMR
- Creating ETL using AWS Glue
- Analysis of Amazon Redshift data
- Monitoring and Audit