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https://github.com/jesussantana/data-science-with-python-it-academy

Learn how to extract value from data by ingesting, transforming, storing, analyzing, and visualizing data
https://github.com/jesussantana/data-science-with-python-it-academy

classification-model clustering-methods dash data-analysis data-mining data-science database machine-learning matplotlib mongodb numpy pandas plotly python3 regression-models seaborn sklearn sql web-scraping

Last synced: 3 days ago
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Learn how to extract value from data by ingesting, transforming, storing, analyzing, and visualizing data

Host: GitHub
URL: https://github.com/jesussantana/data-science-with-python-it-academy
Owner: jesussantana
License: mit
Created: 2021-07-12T07:44:09.000Z (over 3 years ago)
Default Branch: main
Last Pushed: 2024-08-08T17:11:31.000Z (3 months ago)
Last Synced: 2024-08-08T20:07:38.157Z (3 months ago)
Topics: classification-model, clustering-methods, dash, data-analysis, data-mining, data-science, database, machine-learning, matplotlib, mongodb, numpy, pandas, plotly, python3, regression-models, seaborn, sklearn, sql, web-scraping
Homepage:
Size: 18.6 KB
Stars: 2
Watchers: 2
Forks: 1
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # [Data Science with Python - IT Academy](https://www.barcelonactiva.cat/es/itacademy)

![IT-Academy](https://esmarketingdigital.com/images/IT-Academy1.png)

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)  

 

[![Made withJupyter](https://img.shields.io/badge/Made%20with-Jupyter-orange?style=for-the-badge&logo=Jupyter)](https://jupyter.org/try)  

[![Linkedin: JesusSantana](https://img.shields.io/badge/-JesusSantana-blue?style=flat-square&logo=Linkedin&logoColor=white&link=https://www.linkedin.com/in/chus-santana/)](https://www.linkedin.com/in/chus-santana/)  

[![GitHub JesusSantana](https://img.shields.io/github/followers/jesussantana?label=follow&style=social)](https://github.com/jesussantana)  

---

# Objectives

## In the Data Science itinerary with Python we will learn how to extract value from data by ingesting, transforming, storing, analyzing and visualizing data.

---

# Final Project

## - [Project Crypto Punks](https://drive.google.com/file/d/1PpVMcJtAnLuVKMa4fPB6SqX1Fb2bbI-G/view?usp=drive_link)

# Technical Test

## - [Barcelona Rainfall Analysis](https://drive.google.com/file/d/1NVu3lp8N7PPKJEqoKxQ469SYdIPACB3b/view?usp=sharing)

---

# COURSE SYLLABUS

## S01 Installation of the work environment

## S02 Introduction to Python

## S03 Data Structure and Control Structures

- [S03 T01: Data structure](https://github.com/jesussantana/estructures_dades)

- [S03 T02: Structure of a Matrix](https://github.com/jesussantana/imatges_numpy)

- [S03 T03: Control structure](https://github.com/jesussantana/estructures_control)

- [S03 T04: Practice with numerical programming](https://github.com/jesussantana/programacio_Numerica)

- [S03 T05: Data exploration](https://github.com/jesussantana/estructures_Dataframe)

## S04 Data visualization

- [S04 T01: Graphic display of a dataset](https://github.com/jesussantana/visualitzacio_exploratoria)

- [S04 T02: Graphic display of Multiple variables](https://github.com/jesussantana/Visualitzacio_grafica_Multiples_variables)

##  S05 Other basic Python modules

- [S05 T01: Log Transformation with Regular Expressions](https://github.com/jesussantana/Registre_de_logs)

## S06 Sampling methods

- [ S06 T01: Sampling Models](https://github.com/jesussantana/Sampling)

## S07 Data, Probabilities and Statistics

- [S07 T01: Data, probabilities and statistics](https://github.com/jesussantana/Statistics)

## S08 Hypothesis Testing

- [S08 T01: Hypothesis test](https://github.com/jesussantana/Hypothesis-testing)

## S09 Correlation, Feature Scaling & Feature Engineering

- [ S09 T01: Feature Engineering](https://github.com/jesussantana/Feature-Engineering)

## S10 Introduction Machine Learning

## S11 Train and Test

- [S11 T01: Practicing with training and test sets](https://github.com/jesussantana/SkLearn-Train-Test)

## S12 Supervised Learning - Regressions

- [S12 T01: Supervised Learning - Regressions](https://github.com/jesussantana/Supervised-Regression)

## S13 Supervised Learning - Classification

- [S13 T01: Supervised Learning - Classification](https://github.com/jesussantana/Supervised-Classification)

## S14 Imbalance Classification Dataset

## S15 Unsupervised Learning - Clustering

- [S15 T01: Unsupervised Learning - Clustering](https://github.com/jesussantana/Unsupervised-Classification)

## S16 Advanced Machine Learning

- [S16 T01: Pipelines, grid search i text mining](https://github.com/jesussantana/Advanced-Machine-Learning)

- [S16 T02: Web Scraping](https://github.com/jesussantana/Web-Scraping)

## S17 Relational databases

- [S17 T01: Relational databases](https://github.com/jesussantana/Database)

- [S17 T02: MySQL database](https://github.com/jesussantana/SQL-Database)

## S18 NoSQL databases

- [S18 T01: NoSQL database](https://github.com/jesussantana/NoSQL-Database)

## S19 Data science Toolbox

- [S19 T01: Interactive display with ElasticSearch Stack Kibana](https://github.com/jesussantana/Kibana/blob/main/notebooks/S19_T01_Kibana.ipynb)