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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
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The Training Apache Flink - Mastering Real-Time Streaming Pipelines training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Training Apache Flink - Mastering Real-Time Streaming Pipelines training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Training Apache Flink - Mastering Real-Time Streaming Pipelines training is carried out through:
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Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Quick installation of a local Flink cluster and hands-on with advanced DataStream APIs, development of stateful jobs with keyed state and timers for complex windowing on simulated streams, native integration with Kafka for real-time data ingestion and output, performance optimization via parallelism configuration, backpressure, and checkpointing, practical exercises on concrete cases such as bank fraud analysis or IoT metrics, production of architecture diagrams, optimized source code, and monitoring plan with Prometheus, everything ready for enterprise deployment tomorrow.
Target audience
Data engineers, big data architects, streaming developers for professional skill enhancement
Prerequisites
Mastery of Java or Scala, experience with Kafka or Spark, knowledge of distributed systems
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