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 Spark Core for massive distributed processing in the enterprise
- Optimize Spark SQL and DataFrames for high-performance, certified queries
- Implement Spark Structured Streaming for real-time analysis
- Develop ML models with MLlib and professional data science skills
- Configure scalable Spark clusters for production
- Analyze graphs with GraphX and optimize overall performance
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 1Spark Core: Optimizing RDDs and Advanced Transformations (Scala/Python, Tuning, Persistence)
Explore the advanced mechanisms of Spark Core by creating resilient RDDs on massive datasets, apply broadcast variables and accumulators to accelerate jobs, configure memory and disk persistence with hands-on exercises using real enterprise logs, perform manual partition tuning to reduce shuffles, and develop an optimized batch pipeline with code review by the trainer.
Module 2Spark SQL: Leveraging DataFrames and Catalyst (Complex Queries, UDFs, Catalogs)
Master DataFrames for ultra-high-performance SQL analyses on terabytes of data, implement User Defined Functions in Scala and Python, optimize with the Catalyst Optimizer using detailed execution plans, integrate Hive and Delta Lake for ACID tables, work on real-world business reporting cases, generate materialized views, and export to data warehouses.
Module 3Spark Streaming: Real-Time Processing with Structured Streaming (Kafka, Sources, Exactly-Once)
Develop fault-tolerant streaming applications by connecting Spark to Kafka and Kinesis, process continuous streams with windowing and stateful aggregations, ensure exactly-once semantics via checkpoints, simulate real-time IoT scenarios on local clusters, debug using the Spark UI and metrics, and deploy an interactive dashboard for live business event monitoring.
Module 4MLlib and GraphX: Distributed Machine Learning (ML Pipelines, Graph Algorithms)
Build end-to-end ML pipelines with distributed feature engineering, train XGBoost and deep learning models on Spark, evaluate with large-scale cross-validation, analyze social graphs using PageRank and Connected Components on GraphX, apply to real e-commerce datasets, tune hyperparameters with integrated MLflow, and produce batch and streaming predictions for the enterprise.
Module 5Spark Optimization and Deployment: YARN/K8s Clusters, Monitoring, Security
Configure Spark clusters on YARN, Kubernetes, and EMR with high availability, implement Kerberos and Ranger security, optimize executor memory and garbage collection for critical jobs, monitor with Ganglia and Prometheus, deploy via CI/CD with Jenkins, benchmark your ongoing project, and prepare for production certification with a full audit and scaling plan.
Evaluation method
- MCQ to validate learning outcomes at the end of the training
- Continuous assessment through practical Spark exercises
- Defense of the ongoing big data project before the trainer
Learning method
- Courses led by an active expert Spark data engineer
- Practical exercises on real big data clusters
- Progressive ongoing project for distributed processing
- Complete course materials and source codes provided
Methods, materials and delivery
The Training Apache Spark - Processing Distributed Big Data in the Enterprise 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 Distributed Big Data in the Enterprise 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 Distributed Big Data in the Enterprise 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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