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DS-302

Big Data Engineering

When you finish, you can

Build a data pipeline that moves, cleans and serves data at scale, and choose between the cloud tools without buying the wrong one.

Start hereYou need DS-201 and comfort with Python and SQL. Free tiers (BigQuery sandbox, local Spark) cover every exercise.

9 hours total5 Chapters20 Lessons1 Exams3 CreditsFREE
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Debate a counselor

Take a position on Big Data Engineering. The AI counselor argues the other side, asks you questions back, and cites a source for every fact it states. Sources listed under a reply are the pages it actually found; if none are listed, it is arguing from reasoning only. It is an AI and it can be wrong: check the sources.

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    A room for people taking this course, in any language, translated for every reader. Open breakout rooms for one question at a time.

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    Prerequisites::DS-201 Statistical Methods

    Course Syllabus

    9h total

    Practice

    1. Write a word count as a map step and a reduce step on paper, then in Python on a text file.
    2. Draw the difference between a data lake and a warehouse for your own organisation's data.
    3. List three signs your data has outgrown a single machine.

    Check

    Lake or warehouse for raw clickstream logs you might analyse next year? Say why in three sentences.

    Topics Covered

    big-datasparkpipelines

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