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.
1 seat held for the next session
30:00Held for another
Request a call back and an advisor reaches you within 24 business hours, Monday to Saturday.
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning objectives
- Understand Apache Spark's distributed architecture
- Install and configure a Spark environment
- Manipulate RDDs for fast transformations
- Use DataFrames and Spark SQL for structured analyses
- Execute distributed jobs on local clusters
- Optimize basic performance with caching
- Apply Spark to a concrete Big Data case
Our social commitment
A school kit donated to a child for every training
To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.
- Backpack, notebooks and essential supplies
- Distributed through our partner charities
- Included, at no extra cost to you
The Learni story
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
Don't let this gap widen
Why this program matters
Without Apache Spark, waste 40 hours per week on slow sequential scripts, while your competitors process petabytes in minutes.
65% of untrained data analysts fail on Big Data projects, suffering costly bugs at 10k€/month and exploded deadlines x3.
Stay stuck on obsolete tools like Pandas, lose market opportunities estimated at 50% annual data growth.
Avoid frustration, server overload, and competitive lag: train to boost productivity x5, scale without limits, and dominate Big Data tomorrow.
Program
Module 1Introduction to Apache Spark: architecture and installation (PySpark, SparkSession)
Dive into the basics of Apache Spark, install the environment via Docker and PySpark, create your first SparkSession, explore the master-worker architecture with interactive exercises, launch Spark shells on real datasets, and generate your first execution logs to visualize distributed processing, while gaining immediate confidence.
Module 2RDDs: transformations and actions (map, filter, reduce)
Master RDDs, Spark's resilient core, apply map, filter, and reduce on massive CSV files, chain lazy transformations and trigger actions, test on real cases like web log analysis, debug with Spark UI, and generate ready-to-use statistical deliverables to process millions of lines effortlessly.
Module 3DataFrames and Spark SQL: optimized queries (joins, aggregations)
Move to performant DataFrames, load JSON or Parquet data, write native SQL queries, perform joins and groupBy on real e-commerce datasets, optimize with Catalyst, visualize results via Pandas, and export to CSV or NoSQL databases, turning your analyses into actionable insights in just a few clicks.
Module 4Advanced jobs and final project: caching, optimization, practical case
Execute complete jobs on a mini-cluster, apply caching and partitioning to accelerate, integrate Spark with Jupyter, solve an end-to-end project on IoT data, measure performance gains, share deliverables via Git, and leave with a concrete portfolio ready to scale in production.
Evaluation method
- Daily practical exercises
- Interactive quizzes at the end of each day
- Final graded project with personalized feedback
Learning method
- Hands-on method: 80% practical
- Real datasets and open-source tools
- Live interactive remote sessions
Methods, materials and delivery
The Training Apache Spark - Process Your Big Data in 4 Days program is delivered onsite or remote (blended-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 - Process Your Big Data in 4 Days 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 - Process Your Big Data in 4 Days 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
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
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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FAQ
Frequently asked questions
How much does the Training Apache Spark - Process Your Big Data in 4 Days training cost?+
The individual price is $4,620 (USD). The team / on-site group package is shown on the course page. A detailed quote is sent within one business day.
How long is the Training Apache Spark - Process Your Big Data in 4 Days training?+
The training lasts 4 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Basics in Python programming, knowledge of SQL and big data concepts.
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
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