README.md~

## WBS Data Science Bootcamp Repository

The repository documents the individual projects of the [WBS Data Science Bootcamp](https://www.wbscodingschool.com/data-science-bootcamp/).

<table><tbody><tr><td>Prep</td><td>Setting up <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Tableau_in_Linux.md">Tableau for use in Linux</a> (Manjaro/Arch)</td></tr><tr><td>Project 1: <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_1/Project%201%20-%20Magist%20-SQL.sql">Basic and advanced SQL queries</a></td><td>Answering business questions with MySQL and Tableau. The project assesses the viability of using the services of a logistics company as part of a tech company's market entry (e.g. <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/project1_product_space.png">assessing product spaces</a>, <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/project1_geospatial_deliverytime.png">delivery quality</a>). &nbsp;</td></tr><tr><td>Project 2: <a href="https://colab.research.google.com/drive/1K0nn3ABxKaPJ0jBRpSPbDoqC4XFU25W3?usp=share_link">Python, Pandas, and Seaborn</a></td><td>Answering business questions using Python libraries Pandas and Seaborn. Cleaning and categorizing data by <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_2/price_categories.png">price</a>, product, and <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_2/discount_effectiveness.png">discount categories</a> to perform <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_2/weekly_revenues_by_discount.png">discount analysis</a> on sales events.&nbsp;</td></tr><tr><td>Project 3: <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_3/Project_3_data_engineering.ipynb">Data Engineering</a></td><td>Read my <a href="https://medium.com/@jarisdata/how-to-set-up-a-simple-data-pipeline-etl-with-python-and-sql-586af0e75ad1">Medium article</a> on how to set up a data pipeline (ETL) using web scraping, API requests, SQL storage, AWS cloud storage, and automation.</td></tr><tr><td>Project 4: <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_4/clustering_songs.ipynb">Unsupervised Machine Learning</a></td><td>Clustering Spotify songs according to their audio features using KMeans (<a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_4/images/Screenshot%20from%202023-01-26%2015-12-52.png">2D-</a>,<a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_4/images/Screenshot%20from%202023-01-26%2015-12-13.png">3D-</a>, <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_4/images/Screenshot%20from%202023-01-26%2015-22-07.png">radar</a> plots). Paste your own Spotify playlist and after pre-processing data (i.e. calculating <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_4/images/Screenshot%20from%202023-01-26%2011-58-14.png">inertia</a> and <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_4/images/Screenshot%20from%202023-01-26%2015-23-36.png">silhouette</a> scores) choose the number of clusters.</td></tr><tr><td>Project 5: Supervised Machine Learning</td><td>Joining students' (<a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_5/images/house_price_classification.png">1</a>,<a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_5/images/mushroom_competition.png">2</a>) and <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_5/images/KAGGLE_house_price_regression.png">Kaggle</a> competitions to estimate house prices using &nbsp;<a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_5/supervised_ML_classification_competition_final.ipynb">classification</a> and <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_5/kaggle_AMES_supervised_ML_regression_upload.ipynb">regression</a> techniques with various machine learning models in Scikit Learn. Also, <a href="https://github.com/jarisdata/Data_Science_Bootcamp/blob/main/Project_5/Mushroom_competition_upload.ipynb">classifying poisonous mushrooms</a> adjusting thresholds to avoid false negative predictions.</td></tr><tr><td>Project 6: Recommender system</td><td>Developing a movie recommender system (to be uploaded)</td></tr><tr><td>Project 7: Deep Learning</td><td>Using TensorFlow for Natural Language Processing (to be uploaded)</td></tr><tr><td>Final Project</td><td>Developing a dashboard for political and economic data of developing countries (to be uploaded)</td></tr></tbody></table>