Rigorous trainer selection
Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.
- Triple validation: technical, pedagogical, sectoral.
- Minimum rating 4.8/5 over the last 12 sessions.
Learning objectives
- Master the distributed architecture of Apache Spark for professional processing
- Develop scalable data pipelines in enterprise settings
- Implement Spark SQL to analyze massive datasets
- Design certifiable real-time streaming applications
- Optimize Spark performance with advanced tuning
- Deploy secure Spark clusters in production
- Acquire certifiable skills to boost your Big Data career
The Learni story
Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.
Don't let this gap widen
Why this program matters
Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.
Organizations that don't train their talents on key topics see their competitiveness drop.
Every quarter without training is a gap widening with competitors who invest.
The cost of inaction quickly exceeds that of well-targeted training.
Program
Module 1Apache Spark Architecture: Cluster Configuration and Spark Core (YARN, Mesos, RDDs)
Dive into the installation of a multi-node Apache Spark cluster with YARN or Kubernetes, configure standalone and client modes for professional environments, manipulate RDDs for distributed transformations on terabyte datasets, perform practical exercises on partitioning and caching, produce a first fault-tolerant Spark job with monitoring via Spark UI, apply real enterprise cases to validate your scalable batch processing skills.
Module 2Apache Spark SQL: DataFrames, Datasets, and Query Optimizations (Catalyst)
Leverage Spark SQL to load and transform structured data from HDFS, S3, or Kafka, master DataFrames for complex joins on billions of rows, use the Catalyst optimizer to accelerate queries up to 10x, integrate custom UDFs in Python or Scala, analyze real enterprise logs with window functions and advanced aggregations, generate optimized production-ready reports.
Module 3Apache Spark Streaming: Structured Streaming and Real-Time Processing (Kafka)
Develop fault-tolerant streaming applications with Structured Streaming on continuous Kafka streams, implement micro-batches to process IoT events in milliseconds, manage exactly-once semantics with checkpoints, integrate watermarks for late data, test on simulated industrial sensor datasets, produce real-time dashboards connected to Elasticsearch, apply enterprise cases for immediate data reactivity.
Module 4Apache Spark MLlib: Distributed Machine Learning and Pipelines (Advanced Models)
Build end-to-end ML pipelines with MLlib for classification and regression on clusters, train distributed XGBoost or deep learning models on terabytes of data, tune hyperparameters via CrossValidator, integrate Feature Store for reusability, evaluate on real adapted Kaggle enterprise datasets, deploy scalable predictive models with PMML export, obtain production-ready scoring deliverables.
Module 5Apache Spark Optimization and Deployment: Tuning, Security, Monitoring (Databricks)
Optimize Spark performance with AQE, predicate pushdown, and spill tuning to reduce cloud costs by 50%, secure clusters with Kerberos and SSL in enterprise settings, deploy on Databricks or EMR with CI/CD GitHub Actions, monitor via Ganglia and Prometheus, resolve memory leaks on critical cases, finalize a complete red thread project with code review and skill certification, prepare for immediate production deployment.
Evaluation method
- Multiple-choice quiz to validate learning outcomes at the end of the training
- Continuous assessment through practical Spark exercises
- Defense of the Big Data red thread project in front of the trainer
Learning method
- Courses led by an active expert Data Engineer trainer
- Practical exercises on real enterprise Spark clusters
- Progressive red thread project on massive datasets
- Complete course materials and source codes provided
Methods, materials and delivery
The Training Apache Spark - Processing Big Data in Real Time program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.
The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.
Equipment required
For the smooth delivery of the Training Apache Spark - Processing Big Data in Real Time program, the following equipment is required:
- Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
- Training environments installed on workstations or accessible online
- Course materials, hands-on exercises and complementary resources
- Post-training access to materials and educational resources
For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.
* contact us for remote delivery feasibility** ratio varies depending on the program
Skills assessment methods
Assessment of skills acquired during the Training Apache Spark - Processing Big Data in Real Time program is performed through:
- During training: case studies, hands-on labs and professional scenarios
- End of training: self-assessment questionnaire and skills evaluation by the trainer
- After training: completion certificate detailing acquired skills
Program accessibility
Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.
Enrollment terms and lead times
Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.
Verified reviews
What our learners
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
Our method
Training quality, guaranteed at every step
Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.
You meet the trainer beforehand
30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.
- Live briefing on goals and team context.
- Veto right — we swap the trainer for free if needed.
Content tailored to your context
No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.
- Hands-on cases drawn from your stack and projects.
- Program co-written then validated by your team.
Continuous quality follow-up
Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.
- NPS, knowledge quizzes and skills self-assessment.
- Satisfaction guarantee: fully satisfied or free rework.
A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.
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