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 Airflow - Orchestrate Your Data Pipelines Effectively training are: Python basics, command line knowledge, simple ETL concepts.. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Airflow - Orchestrate Your Data Pipelines Effectively training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training Airflow - Orchestrate Your Data Pipelin... | 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 Airflow - Orchestrate Your Data Pipelines Effectively 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 Airflow - Orchestrate Your Data Pipelines Effectively 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 Airflow - Orchestrate Your Data Pipelines Effectively 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 program

Module 1Airflow Introduction: Installation and Architecture (CLI Tools, Docker, Web UI)

Discover Airflow through a guided Docker installation, set up your local environment in 30 minutes, explore the scheduler and workers architecture, run your first tests with simple DAGs, handle the Metadata database to store states and logs, and visualize everything in the intuitive interface to launch your data workflows without delay.

Module 2DAG Creation: Basic Tasks and Dependencies (PythonOperator, BashOperator)

Dive into writing DAGs with Python, define sequential and parallel tasks, test dependencies through practical exercises on mock ETLs, integrate variables and Jinja templates to dynamize your scripts, generate detailed logs, and validate successful executions for smooth and reliable data flows from today.

Module 3Advanced Operators: Data Integrations (PostgresOperator, S3Hook, Sensors)

Master operators for SQL, cloud files, and APIs, connect Airflow to PostgreSQL and S3 via practical hooks, implement sensors for smart waits, code a complete ETL pipeline on a real client case, manage errors with automated retries, and produce exportable deliverables to scale your data processing without manual effort.

Module 4Monitoring and Deployment: Production Optimization (Airflow UI, Alerting)

Monitor workflows live via the Airflow dashboard, analyze metrics and graphs for quick debugging, set up Slack and email alerts for failures, deploy in Celery Executor mode on the cloud, optimize with pools and quotas, and finish with a personal capstone project deliverable for autonomous and performant production.