Providing Technology Training and Mentoring For Modern Technology Adoption
Data engineering is a software engineering practice with focus on design, development, and the productionizing of data processing systems. It includes all the practical aspects of data acquisition, transfer, transformation, and storage on-prem or in the cloud.This intensive hands-on training course teaches the students how to apply Python to the practical aspects of data engineering and introduces the students to the popular Python libraries used in the field, including NumPy, pandas, Matplotlib, scikit-learn, and Apache Spark.
Developers, Software Engineers, Data Scientists, and IT Architects
Participants are expected to have practical experience coding in one or more modern programming languages. Knowledge of Python is desirable but not necessary. The students are expected to be able to quickly learn the new material, reinforce the knowledge of a learned topic by doing programming exercises (labs), and then apply their knowledge in data engineering mini projects.
Dealing with the StateHow Can I Maintain State?Micro Front-ends (a.k.a. MicroUI)How can MicroUI Help Me?Your Clients Are DiverseThe "Rich Client" - "Thin Server" ParadigmThe "Rich Client" - "Thin Server" Architecture RIA as a Driving Force to Turn the "Thin Server" into a Set of MicroservicesDesign for FailureResilience-Related Design PatternsThe Immutable Infrastructure PrincipleImplementing MicroservicesMicroservice-Oriented Application Frameworks and PlatformsEmbedding Databases Embedded Java Databases Summary
Understanding Google's Geocoding API (Research Project) Getting Started with Apigee UI Qwiklabs Comparing API Management Platforms (Research Project) Monolith vs Microservices Design Data Availability and Consistency