Databricks for Beginners: Data Analytics

Practical Databricks+Delta Lake hands‑on course: ETL with PySpark,medallion pipelines,visualization,streaming & basic ML

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Build end-to-end Delta Lake pipelines (Bronze → Silver → Gold) on Databricks and persist managed Delta tables in Unity Catalog.
Implement robust PySpark ETL: safe type casting, duplicate handling, schema enforcement, and scalable transformations.
Optimize Spark jobs using partitioning, caching, join strategies and Spark UI diagnostics to reduce runtime and cost.
Create production‑ready analytics: advanced SQL (CTEs, window functions, MERGE) and reusable business views.
Produce clear visualizations and reports from Spark data using Databricks built‑in tools and Python libraries (Matplotlib/Seaborn).
Build basic Structured Streaming pipelines with Delta Lake sinks and handle late/duplicate events with watermarking and deduplication.
Apply an introductory ML workflow: feature preparation, model training/evaluation, MLflow tracking, and model persistence.

Basic programming familiarity (comfort with reading and editing Python code).
Fundamental SQL knowledge (SELECT, JOIN, GROUP BY).
A laptop/desktop with internet access.
A Databricks account (Community Edition or trial) — instructions provided in Section 2
Recommended but not required: basic pandas or Jupyter notebook experience for faster onboarding.
No prior Spark or Databricks experience required — this course starts with workspace setup and guides you step‑by‑step.

Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!

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