Cloud Fundamentals for Data Practitioners (CD-101)
A forgotten cluster runs all weekend and turns up on Monday as a $3,000 line item nobody can explain. A query that cost pennies at your desk scans a hundred times more data in production and quietly bills for every byte. A storage bucket left open to the internet becomes the headline in a breach report. None of these is a mystery once you understand how the cloud charges for data and who is responsible for locking it down. This course teaches you to see those mechanics before they surprise you.
CD-101 is the on-ramp to the School of Cloud Data Platforms, taught data-first. Every idea arrives through one question — "what does this mean for a dataset?" — instead of generic certification trivia. You will learn the building blocks that every managed data service is assembled from, the shared-responsibility line that decides what you must secure yourself, and the pay-per-use discipline that keeps a platform's monthly bill defensible. The whole course, including its lab, runs on your own machine at zero cost: no cloud account, no card on file, nothing to tear down but a folder.
- Describe the core cloud building blocks for data — compute, object storage, and networking — and explain why compute and storage are billed and scaled separately - Explain regions and availability zones as the boundaries a dataset lives in, and why placing compute next to storage avoids egress charges - Map the managed data-services landscape (object stores, warehouses, and lakehouses) at a conceptual level, naming AWS, Azure, and GCP examples - Read the shared-responsibility model and the free-tier posture to decide what the provider secures versus what you must secure yourself - Estimate a cloud data workload's monthly bill from its cost drivers and apply least-privilege as a day-one habit
Who this course is for
CD-101 gates every platform course in the school, so it is written for learners arriving from several directions:
- The continuity learner partway through the migrated AWS or Azure codelabs who wants the mental models underneath the services they are already clicking through.
- The on-prem data engineer with solid SQL and ETL whose employer is moving to the cloud and who needs service-selection judgment, not just syntax.
- The analyst broadening out who lives in one warehouse and wants the full picture around it: ingestion, storage, cost, and access control.
- The aspiring platform engineer building toward the infrastructure, cost, and governance courses that turn a builder into a platform owner.
Prerequisites
SQL fundamentals and basic Python — enough to read a short query and a short script without panic. Prior DA-1xx or DE-1xx coursework covers this comfortably, or you can place out with the school's placement quiz. You do not need a cloud account, a credit card, or any paid tool. The concepts are vendor-neutral, and the lab runs entirely on your machine using only the Python standard library.
Modules
CD-101 is roughly twelve hours of effort across six modules. This first slice delivers three foundational lessons and your first hands-on lab, covering the building blocks, the managed-services landscape, and the cost-and-security core.
| # | Module | What you leave with |
|---|---|---|
| 1 | Cloud building blocks for data | Compute, object storage, networking, regions/zones |
| 2 | Identity and access fundamentals | Accounts, roles, policies, least privilege as habit |
| 3 | Networking just-enough | The VPC/VNet mental model and private endpoints |
| 4 | Anatomy of a cloud data platform | Ingestion to serving, mapped across four clouds |
| 5 | Pricing literacy | On-demand vs. serverless, egress, cost-per-month |
| 6 | Working like a professional | Tagging, budget alarms, and teardown discipline |
The three lessons and the lab below cover the core of Modules 1, 4, 5, and 6, and give you the cost-estimation skill the rest of the school leans on whenever it asks "what does this cost per month?"
Outcomes
By the end of CD-101 you can:
- Explain how compute, object storage, and networking combine into a cloud data platform, and why storage is its center of gravity.
- Choose a region for a dataset and predict when moving that data will cost you in egress charges.
- Place any managed data service on the managed-versus-self-managed spectrum and say which security duties the shared-responsibility model leaves to you.
- Estimate a workload's monthly bill from storage, egress, and compute usage, and flag a configuration that would spill out of the free tier.
Where this leads
CD-101 gates all five Practitioner platform courses — AWS analytics, data engineering on AWS, the Azure data platform, Databricks, and Snowflake — and through them the Advanced courses on infrastructure-as-code, cost engineering, and security. The cost-calculator you build in this course's lab is the seed of a habit those courses assume: every design decision comes with a monthly-cost answer. Start here, and the pricing and security discussions later never catch you off guard.
Do the lessons in order. Each introduces vocabulary the next assumes — regions and object storage in Lesson 1, the service landscape in Lesson 2, and the cost drivers in Lesson 3 — and the lab pulls all three together into a calculator you will reach for whenever you size a workload.