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 Databricks Training - Master Delta Lake and Data Scalability training are: Basics in Python or SQL, knowledge of Spark, experience in data manipulation.. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Databricks Training - Master Delta Lake and Data Scalability training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Databricks Training - Master Delta Lake and 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 Databricks Training - Master Delta Lake and Data Scalability 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 Databricks Training - Master Delta Lake and Data Scalability 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 Databricks Training - Master Delta Lake and Data Scalability 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 objectives

Configure optimized Databricks clusters for your workloads

Implement Delta Lake for reliable and scalable tables

Develop advanced ETL pipelines with Spark Structured Streaming

Manage the ML lifecycle with integrated MLflow

Automate workflows via Databricks Jobs

Optimize performance and costs on Unity Catalog

Training program

Module 1Databricks Fundamentals: Notebooks and Clusters (Spark SQL, Python)

Dive into the Databricks environment by configuring your first scalable clusters, creating collaborative notebooks to explore massive datasets, executing optimized Spark SQL queries on real cases like log analysis, and producing your first interactive reports with Delta Live Tables, while measuring immediate performance gains to boost your data productivity.

Module 2Delta Lake: Advanced ACID Data Management (Reliability, Versioning)

Master Delta Lake by implementing transactional tables on your large-scale data, managing time travel to restore previous versions in case of errors, optimizing merges and Z-order to accelerate queries by 10x, through practical exercises on e-commerce datasets, and generating production-ready deliverables that secure your ETL pipelines.

Module 3MLflow and Machine Learning: Tracking and Model Deployment

Integrate MLflow to track ML experiments, log metrics and artifacts on Databricks, train models on GPU clusters with Hyperopt, deploy via MLflow Models for scalable inference, through concrete cases like churn prediction, and create unified registries that accelerate your ML iterations by 50%.

Module 4Workflows and Optimization: Jobs, Unity Catalog, Monitoring

Automate your workflows with Databricks Jobs and Schedules on end-to-end pipelines, configure Unity Catalog for multi-team data governance, optimize cloud costs via autoscaling and spot instances, test on real projects with integrated monitoring, and deliver a portfolio of production-ready jobs that reduce your processing times by 40%.