Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Training Apache Spark - Process Your Big Data Quickly training are: Basics in Python or Java programming, knowledge of SQL and Linux. A preliminary interview validates your eligibility.

What are the objectives of the Training Apache Spark - Process Your Big Data Quickly training?

The objectives of the Training Apache Spark - Process Your Big Data Quickly training are: Understand the fundamental concepts of Apache Spark. Install and configure a Spark environment. Manipulate RDDs to process distributed data. Use Spark SQL and DataFrames for fast analyses. Develop Spark applications in batch mode. Explore streaming with Spark Streaming. Deploy Spark jobs on a local cluster. Upon completion, you will be able to put these skills into practice.

Is the training available in person?

Yes, the Training Apache Spark - Process Your Big Data Quickly training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Training Apache Spark - Process Your Big Data… | Learni

The story of Learni

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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Methods, approaches, and teaching resources

The Training Apache Spark - Process Your Big Data Quickly 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.

Teaching resources provided

To ensure the quality of the Training Apache Spark - Process Your Big Data Quickly training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and 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.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Training Apache Spark - Process Your Big Data Quickly training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training access terms and deadlines

Training program

Module 1Introduction to Apache Spark: concepts and installation (Spark tools, Scala, Python)

Discover the basics of Apache Spark, its distributed architecture and advantages over Hadoop, install Spark on your machine through guided exercises, configure PySpark for initial tests, manipulate simple datasets with the Spark console, create your first job that reads and transforms a CSV file, experience the power of in-memory processing that accelerates your analyses from day one.

Module 2RDDs and transformations: basic methods (RDD, map, filter, reduce)

Dive into Resilient Distributed Datasets, apply map, filter and reduce on real cases like web log analysis, chain transformations with practical exercises on millions of lines, manage actions like count and collect, optimize your code to avoid common pitfalls, produce deliverables like an aggregated report, gain speed and confidence to scale your processing.

Module 3Spark SQL and DataFrames: advanced queries (DataFrames, SQL, joins)

Master DataFrames for structured analyses, write SQL queries on massive data, perform joins and aggregations on real datasets like e-commerce sales, convert RDDs to DataFrames for greater efficiency, explore UDFs for custom functions, generate basic visualizations, transform your skills into immediate business tools with interactive live exercises.

Module 4Projects and deployment: streaming and cluster (Spark Streaming, YARN)

Build a complete real-time stream analysis project with Spark Streaming on simulated Twitter data, deploy on a local cluster via Docker, test fault tolerance, integrate Spark with Kafka for professional cases, finalize a portfolio with an exportable Spark job, receive personalized feedback, leave ready to implement Spark in the enterprise and boost your Big Data career.