UdemyIT CertificationsPaid courseIntermediate levelCertificate

Apache Spark with PySpark 2026: Zero to Expert + Delta Lake (Udemy.com)

The Complete Hands-On Course | PySpark 4 + Delta Lake 3 + Structured Streaming + Real-Time Projects | Databricks

4.2

82 reviews

Created by: Aymeric Daniel Neuvy

Last updated April 2026

What you will learn

Master Apache Spark with Python (PySpark 4.x) from beginner to production-ready level
Build and deploy end-to-end data pipelines using Delta Lake – the #1 most in-demand Spark technology in 2025-2026 (ACID transactions, time travel, schema evolut
Implement real-time streaming applications with Structured Streaming + Kafka, including exactly-once processing, watermarking, and Delta Lake sinks
Design and optimize large-scale Spark jobs ( Catalyst optimizer, AQE, skew handling, broadcasting, partitioning, bucketing) to process terabytes efficiently
Build 4 complete real-world projects you can immediately add to your portfolio and GitHub: NYC Taxi analysis (10 GB+), log processing pipeline, movie recommenda
Work like a professional Data Engineer using Databricks Community Edition (free) – the exact same platform used by Netflix, Uber, and 90 % of Fortune 500 compan

How it compares

Against the other 848 rated Udemy courses in IT Certifications on CourseDuck:

Rating4.2 out of 5higher than 10% of them
Reviews82#729 of 849 by number of reviews
Length14.3 hourslonger than 71% of them
Last updatedApril 2026more recently than 60% of them

Course Description

Become a Spark Expert in 2026 with the Most Complete & Up-to-Date PySpark Course on Udemy

Master Apache Spark with Python (PySpark) from zero to production-ready, including the technologies that 95% of Spark jobs use in 2025-2026:

• Delta Lake (the #1 most requested skill in 2025-2026)

• Structured Streaming + Kafka

• Databricks Lakehouse workflow (Community Edition – 100% free)

• Real-time dashboards, recommendation systems, sentiment analysis

• 4 complete real-world projects you can put directly on your resume

What you’ll learn (everything hands-on):

✓ Spark Core, RDDs, DataFrames, Datasets & Spark SQL (the 80% you’ll use every day)

✓ Spark Architecture Deep Dive (Driver, Executors, Shuffle, Partitions, Skew)

✓ Performance Tuning Mastery (Catalyst, AQE, Tungsten, Z-Ordering, Broadcasting)

✓ Delta Lake Full Stack: ACID, Time Travel, Schema Evolution, MERGE, OPTIMIZE

✓ Structured Streaming with Kafka + Exactly-once + Watermarking + Delta Sink

✓ Machine Learning with Spark: MLlib + Pandas UDF + XGBoost + HuggingFace

✓ Deploy on AWS EMR, GCP Dataproc, Azure + full Databricks workflow

✓ 4 Production-Ready Projects: NYC Taxi (10 GB+), Log Pipeline, Netflix like Movie Recommendation, Real-Time Twitter Sentiment Dashboard

No boring theory – every concept is taught with live coding + downloadable notebooks.

Two ways to code (you choose):

• 100% local environment (Mac/Windows setup)

• Databricks Community Edition (free forever – the exact same tool used by Fortune 500)

Perfect for:

• Data Engineers & Big Data Engineers wanting 100K–200K€ jobs

• Data Scientists who want to work with datasets > 100 GB

• Analysts who want to 10x their SQL speed

• Anyone preparing Databricks or Spark certifications

Includes:

• All notebooks + datasets + Docker files

• PDF cheat sheets (PySpark, Delta Lake, Streaming)

• 100+ interview questions with answers

• Private Discord community + direct help from me

• Lifetime updates (Spark 4.x, Delta Lake 3.x, 4.x already included)

Enroll now – 30-day money-back guarantee

Click “Buy Now” and become job-ready in the most in-demand big data technology of 2026!

Intermediate Level

Time: 14.3h

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Instructor Details

Aymeric Daniel Neuvy

4.2 Rating
82 Reviews

I'm Aymeric, a IT Engineer who shipped Spark systems in production. And I teach maths and computing since 2020.

I've built real-time analytics platforms processing millions of events daily, architected GCP data pipelines for automotive marketing (Nissan), and scaled AdTech integrations handling 99.9% uptime across major publishers (CNN, WikiHow, Condé Nast).