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# Learn Kedro with hands-on video | ||
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If you like to learn from video, you can follow our [hands-on course "Introduction to Kedro: Building Maintainable Data Pipelines" on YouTube](https://www.youtube.com/playlist?list=PL-JJgymPjK5LddZXbIzp9LWurkLGgB-nY). | ||
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The course is structured into sections and these are each broken into short videos that cover specific Kedro topics. You'll walk through the [spaceflights tutorial](../tutorial/spaceflights_tutorial.md) and get hands-on with the example. Along the way, you'll learn key Kedro concepts like datasets and the Kedro Data Catalog, nodes and pipelines, and configuration management. | ||
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## Who is this course for? | ||
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This course is for data scientists, data engineers and machine learning engineers. You can be junior, mid-level or senior in your field of work. You're likely to be hands-on with projects, or a decision-maker who regularly makes design and implementation choices about Python data products. | ||
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We assume you know these concepts: | ||
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* Python basics (coding on Jupyter and other notebook interfaces) | ||
* Manipulating data with pandas | ||
* Visualising insights | ||
* Command line basics | ||
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We don't assume knowledge of software engineering in Python, so the course contains information about reusability principles, how to create a Python package, and how to use version control. | ||
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## What you'll learn | ||
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In short, you'll learn answers to the following: | ||
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* Introduction to Kedro | ||
* What is Kedro? How does it help you create maintainable, reusable data science code? | ||
* How does Kedro fit into the data science ecosystem? | ||
* What do you need to do to create a Kedro project? | ||
* How can you refactor a Jupyter notebook to a Kedro project? | ||
* How do you package Python code as a library? | ||
* How do you work with Kedro projects in VSCode? | ||
* What are namespaces and dataset factories? | ||
* What is needed to deploy a Kedro project using container solutions like Docker and open source orchestrators like Airflow? | ||
* What are Kedro plugins? | ||
* How can you contribute to Kedro? | ||
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You don't need to register for the course and you can skip around the sections to find help on a particular area as you pick up the skills needed to build your own Kedro projects. | ||
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## Index of videos | ||
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[Introduction to Kedro: Building Maintainable Data Pipelines](https://www.youtube.com/playlist?list=PL-JJgymPjK5LddZXbIzp9LWurkLGgB-nY) is split into the following videos: | ||
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### Part 0: Introduction | ||
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1. [Data science in production: the good, the bad and the ugly](https://www.youtube.com/watch?v=DD7JuYKp6BA) | ||
1. [What is Kedro?](https://www.youtube.com/watch?v=PdNkECqvI58) | ||
1. [Kedro and data orchestrators](https://www.youtube.com/watch?v=_HH8SCmCP_Q) | ||
1. [How does Kedro fit into the data science ecosystem?](https://www.youtube.com/watch?v=nAyUqORd9R8) | ||
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### Part 1: Get started with Kedro | ||
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1. [Create a Kedro project from scratch?](https://www.youtube.com/watch?v=YBY2Lcz7Gw4) | ||
1. [The spaceflights starter](https://www.youtube.com/watch?v=K6PhgVyXhWE) | ||
1. [Use Kedro from Jupyter notebook](https://www.youtube.com/watch?v=3q2RNWLibyY) | ||
1. [Set up the Kedro Data Catalog](https://www.youtube.com/watch?v=rl2cncGxyts) | ||
1. [Explore the spaceflights data](https://www.youtube.com/watch?v=bZD8N0yv3Fs) | ||
1. [Refactor your data processing code into functions](https://www.youtube.com/watch?v=VFcrvnnNas4) | ||
1. [Create your first data pipeline with Kedro](https://www.youtube.com/watch?v=VFcrvnnNas4) | ||
1. [Assemble your nodes into a Kedro pipeline](https://www.youtube.com/watch?v=P__gFG1TmMo) | ||
1. [Run your Kedro pipeline](https://www.youtube.com/watch?v=sll_LhZE-p8) | ||
1. [Visualise your data pipeline with Kedro-Viz](https://www.youtube.com/watch?v=KWqSzbHgNW4) | ||
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### Part 2: Make complex Kedro pipelines | ||
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1. [Merge different dataframes in Kedro](https://www.youtube.com/watch?v=ctTFAeL4JgU) | ||
1. [Predict prices using machine learning](https://www.youtube.com/watch?v=Y4JvVO2DOJA) | ||
1. [Refactor your data science code into functions](https://www.youtube.com/watch?v=zvAnE05-agw) | ||
1. [How to work with parameters in Kedro](https://www.youtube.com/watch?v=eIA12RQMlFY) | ||
1. [Create a Kedro pipeline with parameters](https://www.youtube.com/watch?v=iRwy-IStfPo) | ||
1. [Reuse your Kedro pipeline using namespaces](https://www.youtube.com/watch?v=cYHHVAoWZ2E) | ||
1. [Kedro pipeline runners](https://www.youtube.com/watch?v=_B6R2uOj3-s) | ||
1. [Create Kedro datasets dynamically using factories](https://www.youtube.com/watch?v=tNE-tdvHNP8) | ||
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### Part 3: Ship your Kedro project to production | ||
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1. [Define your own Kedro environments](https://www.youtube.com/watch?v=9quRBGDOFq8) | ||
1. [Use S3 and MinIO cloud storage with Kedro](https://www.youtube.com/watch?v=TkoBEQIdHbA) | ||
1. [Package your Kedro project into a Python wheel](https://www.youtube.com/watch?v=yaoAQVX0iM8) | ||
1. [Turn your Kedro project into a Docker container](https://www.youtube.com/watch?v=lA-Ivuxmakw&list=PL-JJgymPjK5LddZXbIzp9LWurkLGgB-nY&index=26&t=1s&pp=gAQBiAQB) | ||
1. [Deploy your Kedro project to Apache Airflow](https://www.youtube.com/watch?v=AhCcnJ1Au70) | ||
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### Part 4: Where next? | ||
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[Continue your Kedro journey](https://www.youtube.com/watch?v=JvXhv8_0tlE) |
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