Live Online Luigi Course for Data Engineering

Live Course Module: Luigi Course for Data Engineering

Total Duration: 40 Hours (4 Weeks)

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Week 1: Introduction to Luigi & Core Concepts

Duration: 8 hours (4 sessions × 2 hrs)

Topics:

1. Introduction to Workflow Orchestration (2 hrs)

   • What is workflow orchestration?

   • Why Luigi? Comparison with Airflow and Prefect

   • Overview of Luigi architecture: Scheduler, Worker, Task, Target

2. Luigi Installation & Environment Setup (2 hrs)

   • Installing Luigi using Python environment

   • Setting up Luigi central scheduler (luigid)

   • Exploring Luigi web UI

3. Building Your First Luigi Task (2 hrs)

   • Creating a simple Luigi pipeline

   • Understanding requires(), output(), and run() methods

   • Task dependencies and data flow

4. Mini Project + Q&A (2 hrs)

   • Build a two-stage Luigi pipeline (data extraction + transformation)

   • Run and monitor through the Luigi dashboard

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Week 2: Intermediate Luigi – Task Dependencies & Data Pipelines

Duration: 10 hours (5 sessions × 2 hrs)

Topics:

1. Task Parameters and Dynamic Pipelines (2 hrs)

   • Using luigi.Parameter for configurable workflows

   • Dynamic dependencies and parameterized tasks

2. Input/Output Targets (2 hrs)

   • FileSystemTarget, LocalTarget, S3Target, and HdfsTarget

   • Managing inputs and outputs in pipelines

3. Error Handling & Task Re-Runs (2 hrs)

   • Handling task failures

   • Task retry policies

   • Incremental pipeline execution

4. Integrating Luigi with Databases (2 hrs)

   • Reading/Writing data from PostgreSQL, MySQL, and SQLite

   • Example: ETL task using SQL queries in Luigi

5. Mini Project + Q&A (2 hrs)

   • Build a 3-step ETL pipeline using Luigi and SQL databases

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Week 3: Advanced Luigi – Integration with Big Data Tools

Duration: 10 hours (5 sessions × 2 hrs)

Topics:

1. Luigi with Apache Spark (2 hrs)

   • Submitting Spark jobs through Luigi

   • Managing distributed data transformations

2. Luigi with Hadoop / HDFS (2 hrs)

   • Using HdfsTarget for file I/O

   • Integrating Luigi with existing Hadoop workflows

3. Luigi with Kafka for Streaming Data (2 hrs)

   • Real-time ingestion pipeline design

   • Triggering Luigi tasks for batch micro-batching from Kafka topics

4. Monitoring & Logging Pipelines (2 hrs)

   • Luigi logging configuration

   • Job status monitoring and troubleshooting

5. Mini Project + Q&A (2 hrs)

   • Build a data pipeline integrating Spark + HDFS + Luigi

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Week 4: Deployment, Scaling & Capstone Project

Duration: 12 hours (6 sessions × 2 hrs)

Topics:

1. Scheduling Luigi Workflows (2 hrs)

   • Running Luigi pipelines on schedule

   • Using CRON and Luigi daemon mode

2. Scaling Luigi in Production (2 hrs)

   • Multi-worker setup

   • Parallel task execution

   • Optimizing performance and resource usage

3. Luigi in Cloud Environments (2 hrs)

   • Running Luigi on AWS/GCP/Azure

   • Luigi with S3/GCS for input-output data management

4. CI/CD for Luigi Pipelines (2 hrs)

   • Version control with Git

   • Automating Luigi deployments with Docker

5. Capstone Project Development (2 hrs)

   • Build an end-to-end data pipeline using Luigi, Spark, and Cloud storage

6. Capstone Presentation & Review (2 hrs)

   • Pipeline presentation and feedback

   • Best practices and career use-cases

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🧩 Capstone Project Example

Project Title: Automated Data Pipeline for Daily Sales Analytics
Goal: Ingest sales data from APIs → store in S3 → transform via Spark → load into a data warehouse → orchestrate with Luigi
Tech Stack: Luigi, Python, Spark, AWS S3, PostgreSQL