https://github.com/mxagar/datacamp_notes
These are my personal notes of several data science and engineering courses from Datacamp.
https://github.com/mxagar/datacamp_notes
data-engineering data-science guide machine-learning
Last synced: over 1 year ago
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These are my personal notes of several data science and engineering courses from Datacamp.
- Host: GitHub
- URL: https://github.com/mxagar/datacamp_notes
- Owner: mxagar
- Created: 2023-03-19T07:02:45.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-05-03T08:43:18.000Z (about 3 years ago)
- Last Synced: 2025-02-15T12:50:47.727Z (over 1 year ago)
- Topics: data-engineering, data-science, guide, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 2.2 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Datacamp Notes
These are my personal notes of several data science and engineering courses from [Datacamp](https://www.datacamp.com).
Datacamp is organized in single *courses* and *tracks*, which contain several single courses arranged in a learning order. Each one of the tracks/courses I did and considered interesting has a dedicated folder with its guide (markdown), code and additional material.
List of courses / tracks:
- [Analyzing IoT Data in Python](https://app.datacamp.com/learn/courses/analyzing-iot-data-in-python): [`Course_IoT`](Course_IoT).
- [Extreme Gradient Boosting with XGBoost](https://app.datacamp.com/learn/courses/extreme-gradient-boosting-with-xgboost): [`Course_XGBoost`](Course_XGBoost).
I have done some other courses from [Datacamp](https://www.datacamp.com), but the notes are located in domain-specific repositories I had before; for instance:
- [spark_big_data_guide](https://github.com/mxagar/spark_big_data_guide)
- [space_exploration](https://github.com/mxagar/space_exploration)
- [sql_guide](https://github.com/mxagar/sql_guide)
- [data_science_udacity](https://github.com/mxagar/data_science_udacity)
- etc.
Mikel Sagardia, 2023.
No guarantees.