├── .gitattributes ├── .gitignore ├── LICENSE ├── Learn ├── Python │ ├── Applied Data Science │ │ ├── Basic Feature Discovering for Machine Learning │ │ │ ├── Basic Feature Discovering for Machine Learning.ipynb │ │ │ └── Basic Feature Discovering for Machine Learning.py │ │ ├── Customer Churn Prediction using Machine Learning │ │ │ ├── Customer Churn Prediction using Machine Learning.ipynb │ │ │ └── Customer Churn Prediction using Machine Learning.py │ │ ├── Data Analyst Project Business Decision Research │ │ │ ├── Data Analyst Project Business Decision Research.ipynb │ │ │ └── Data Analyst Project Business Decision Research.py │ │ ├── Data Science Project Analisis Data COVID19 di Dunia & ASEAN │ │ │ ├── Data Science Project Analisis Data COVID19 di Dunia & ASEAN.ipynb │ │ │ └── Data Science Project Analisis Data COVID19 di Dunia & ASEAN.py │ │ ├── Data Science in Marketing Customer Segmentation with Python part 2 │ │ │ ├── Data Science in Marketing Customer Segmentation with Python part 2.ipynb │ │ │ ├── Data Science in Marketing Customer Segmentation with Python part 2.py │ │ │ └── cluster.pkl │ │ ├── Data Science in Marketing Customer Segmentation with Python │ │ │ ├── Data Science in Marketing Customer Segmentation with Python.ipynb │ │ │ └── Data Science in Marketing Customer Segmentation with Python.py │ │ ├── Data Science in Telco Data Cleansing │ │ │ ├── Data Science in Telco Data Cleansing.ipynb │ │ │ └── Data Science in Telco Data Cleansing.py │ │ └── Eksplorasi dan Analisis Data COVID-19 Indonesia using Python │ │ │ ├── Eksplorasi dan Analisis Data COVID-19 Indonesia using Python.ipynb │ │ │ └── Eksplorasi dan Analisis Data COVID-19 Indonesia using Python.py │ ├── Fundamental │ │ ├── Data Manipulation with Pandas - Part 1 │ │ │ ├── Data Manipulation with Pandas - Part 1.ipynb │ │ │ └── Data Manipulation with Pandas - Part 1.py │ │ ├── Data Manipulation with Pandas - Part 2 │ │ │ ├── Data Manipulation with Pandas - Part 2.ipynb │ │ │ └── Data Manipulation with Pandas - Part 2.py │ │ ├── Data Quality with Python for Beginner │ │ │ ├── Data Quality with Python for Beginner.ipynb │ │ │ └── Data Quality with Python for Beginner.py │ │ ├── Data Visualization using Plotnine │ │ │ ├── Data Visualization using Plotnine.ipynb │ │ │ └── Data Visualization using Plotnine.py │ │ ├── Data Visualization with Python Matplotlib for Beginner - Part 1 │ │ │ ├── Data Visualization with Python Matplotlib for Beginner - Part 1.ipynb │ │ │ ├── Data Visualization with Python Matplotlib for Beginner - Part 1.py │ │ │ └── monthly_gmv.png │ │ ├── Data Visualization with Python Matplotlib for Beginner - Part 2 │ │ │ ├── Data Visualization with Python Matplotlib for Beginner - Part 2.ipynb │ │ │ └── Data Visualization with Python Matplotlib for Beginner - Part 2.py │ │ ├── Data Wrangling Python │ │ │ ├── Data Wrangling Python.ipynb │ │ │ ├── Data Wrangling Python.py │ │ │ ├── shopping_data.csv │ │ │ └── shopping_data_missingvalue.csv │ │ ├── Exploratory Data Analysis with Python for Beginner │ │ │ ├── Exploratory Data Analysis with Python for Beginner.ipynb │ │ │ ├── Exploratory Data Analysis with Python for Beginner.py │ │ │ └── order.csv │ │ ├── Fundamental Data Visualization with Python │ │ │ ├── Fundamental Data Visualization with Python.ipynb │ │ │ └── Fundamental Data Visualization with Python.py │ │ ├── Machine Learning With Python for Beginner │ │ │ ├── Machine Learning With Python for Beginner.ipynb │ │ │ └── Machine Learning With Python for Beginner.py │ │ ├── Python for Data Professional Beginner - Part 1 │ │ │ ├── Python for Data Professional Beginner - Part 1.ipynb │ │ │ └── Python for Data Professional Beginner - Part 1.py │ │ ├── Python for Data Professional Beginner - Part 2 │ │ │ ├── Python for Data Professional Beginner - Part 2.ipynb │ │ │ └── Python for Data Professional Beginner - Part 2.py │ │ ├── Python for Data Professional Beginner - Part 3 │ │ │ ├── Python for Data Professional Beginner - Part 3.ipynb │ │ │ └── Python for Data Professional Beginner - Part 3.py │ │ ├── Statistic using Python for Data Science - Part 2 │ │ │ ├── Statistic using Python for Data Science - Part 2.ipynb │ │ │ └── Statistic using Python for Data Science - Part 2.py │ │ └── Statistic using Python for Data Science │ │ │ ├── Statistic using Python for Data Science.ipynb │ │ │ └── Statistic using Python for Data Science.py │ └── Preliminary │ │ ├── Introduction to Data Science with Python │ │ ├── Introduction to Data Science with Python.ipynb │ │ └── Introduction to Data Science with Python.py │ │ └── Python Fundamental for Data Science │ │ ├── Python Fundamental for Data Science.ipynb │ │ ├── Python Fundamental for Data Science.py │ │ └── penduduk_gender_head.csv ├── R │ ├── Applied Data Science │ │ ├── A Walk Into Sensory Science │ │ │ ├── A Walk Into Sensory Science.R │ │ │ ├── A Walk Into Sensory Science.Rmd │ │ │ ├── A-Walk-Into-Sensory-Science.html │ │ │ └── chocolates_adjmean.rds │ │ ├── Analisis Data COVID19 di Indonesia │ │ │ ├── Analisis Data COVID19 di Indonesia.R │ │ │ ├── Analisis Data COVID19 di Indonesia.Rmd │ │ │ └── Analisis-Data-COVID19-di-Indonesia.html │ │ ├── Data Science in Finance Credit Risk Analysis │ │ │ ├── Data Science in Finance Credit Risk Analysis.R │ │ │ ├── Data Science in Finance Credit Risk Analysis.Rmd │ │ │ └── Data-Science-in-Finance-Credit-Risk-Analysis.html │ │ ├── Data Science in Finance Dimension Reduction │ │ │ ├── Data Science in Finance Dimension Reduction.R │ │ │ ├── Data Science in Finance Dimension Reduction.Rmd │ │ │ └── Data-Science-in-Finance-Dimension-Reduction.html │ │ ├── Data Science in Marketing Customer Segmentation │ │ │ ├── Data Science in Marketing Customer Segmentation.R │ │ │ ├── Data Science in Marketing Customer Segmentation.Rmd │ │ │ ├── Data-Science-in-Marketing-Customer-Segmentation.html │ │ │ └── cluster.rds │ │ └── Data Science in Retail Market Basket Analysis │ │ │ ├── Data Science in Retail Market Basket Analysis.R │ │ │ ├── Data Science in Retail Market Basket Analysis.Rmd │ │ │ ├── Data-Science-in-Retail-Market-Basket-Analysis.html │ │ │ └── top3_item_retail.txt │ ├── Fundamental │ │ ├── Advanced Data Visualization for Everyone │ │ │ ├── Advanced Data Visualization for Everyone.R │ │ │ ├── Advanced Data Visualization for Everyone.Rmd │ │ │ └── Advanced-Data-Visualization-for-Everyone.html │ │ ├── Data Preparation in Data Science using R │ │ │ ├── Data Preparation in Data Science using R.R │ │ │ ├── Data Preparation in Data Science using R.Rmd │ │ │ └── Data-Preparation-in-Data-Science-using-R.html │ │ ├── Data Visualization in Data Science using R │ │ │ ├── Data Visualization in Data Science using R.R │ │ │ ├── Data Visualization in Data Science using R.Rmd │ │ │ └── Data-Visualization-in-Data-Science-using-R.html │ │ ├── Fundamental Data Visualization using R │ │ │ ├── Fundamental Data Visualization using R.R │ │ │ ├── Fundamental Data Visualization using R.Rmd │ │ │ └── Fundamental-Data-Visualization-using-R.html │ │ └── Statistics using R for Data Science │ │ │ ├── Statistics using R for Data Science.R │ │ │ ├── Statistics using R for Data Science.Rmd │ │ │ └── Statistics-using-R-for-Data-Science.html │ └── Preliminary │ │ ├── Introduction to Data Science with R │ │ ├── Introduction to Data Science with R.R │ │ ├── Introduction to Data Science with R.Rmd │ │ └── Introduction-to-Data-Science-with-R.html │ │ └── R Fundamental for Data Science │ │ ├── R Fundamental for Data Science.R │ │ ├── R Fundamental for Data Science.Rmd │ │ └── R-Fundamental-for-Data-Science.html └── SQL │ ├── Fundamental │ ├── Fundamental SQL Group By and Having │ │ ├── Data │ │ │ ├── customer.sql │ │ │ ├── invoice.sql │ │ │ ├── payment.sql │ │ │ ├── product.sql │ │ │ └── subscription.sql │ │ └── Fundamental SQL Group By and Having.sql │ ├── Fundamental SQL Using FUNCTION and GROUP BY │ │ ├── Data │ │ │ ├── sales_retail_2019.sql │ │ │ ├── students.sql │ │ │ └── tr_penjualan.sql │ │ └── Fundamental SQL Using FUNCTION and GROUP BY.sql │ ├── Fundamental SQL Using INNER JOIN and UNION │ │ ├── Data │ │ │ ├── customers.sql │ │ │ ├── ms_item_kategori.sql │ │ │ ├── ms_item_warna.sql │ │ │ ├── ms_pelanggan.sql │ │ │ ├── ms_produk.sql │ │ │ ├── ms_produk_1.sql │ │ │ ├── ms_produk_2.sql │ │ │ ├── suppliers.sql │ │ │ ├── tabel_a.sql │ │ │ ├── tabel_b.sql │ │ │ └── tr_penjualan.sql │ │ └── Fundamental SQL Using INNER JOIN and UNION.sql │ └── Fundamental SQL Using SELECT Statement │ │ ├── Data │ │ ├── ms_pelanggan.sql │ │ ├── ms_produk.sql │ │ └── tr_penjualan.sql │ │ └── Fundamental SQL Using SELECT Statement.sql │ └── Preliminary │ └── Fundamental SQL with SELECT Statement │ ├── Data │ └── ms_produk.sql │ └── Fundamental SQL with SELECT Statement.sql ├── Project ├── Python │ ├── Data Engineer Challenge with Python │ │ ├── Data Engineer Challenge with Python.ipynb │ │ ├── Data Engineer Challenge with Python.py │ │ └── Indonesia_Demography_by_Province.csv │ ├── Data Science Challenge with Python │ │ ├── Data Science Challenge with Python.ipynb │ │ └── Data Science Challenge with Python.py │ ├── Project Machine Learning with Python Building Recommender System with Similarity Function │ │ ├── Project Machine Learning with Python Building Recommender System with Similarity Function.ipynb │ │ └── Project Machine Learning with Python Building Recommender System with Similarity Function.py │ └── Project Machine Learning with Python Building Recommender System │ │ ├── Project Machine Learning with Python Building Recommender System.ipynb │ │ └── Project Machine Learning with Python Building Recommender System.py ├── R │ ├── Project Data Analysis for Finance Performa Cabang │ │ ├── Project Data Analysis for Finance Performa Cabang.R │ │ ├── Project Data Analysis for Finance Performa Cabang.Rmd │ │ └── Project-Data-Analysis-for-Finance-Performa-Cabang.html │ ├── Project Data Analysis for Finance Proses Investasi Investor │ │ ├── Project Data Analysis for Finance Proses Investasi Investor.R │ │ ├── Project Data Analysis for Finance Proses Investasi Investor.Rmd │ │ └── Project-Data-Analysis-for-Finance-Proses-Investasi-Investor.html │ └── Project Machine Learning for Retail with R Product Packaging │ │ ├── Project Machine Learning for Retail with R Product Packaging.R │ │ ├── Project Machine Learning for Retail with R Product Packaging.Rmd │ │ ├── Project-Machine-Learning-for-Retail-with-R-Product-Packaging.html │ │ ├── bottom10_item_retail.txt │ │ ├── kombinasi_retail.txt │ │ ├── kombinasi_retail_slow_moving.txt │ │ ├── test_project_retail_1.txt │ │ ├── top_10.txt │ │ └── transaksi_dqlab_retail.tsv └── SQL │ ├── Data Analysis for E-Commerce Challenge │ ├── Data Analysis for E-Commerce Challenge.sql │ └── Data │ │ ├── order_details.sql │ │ ├── orders.sql │ │ ├── products.sql │ │ └── users.sql │ ├── Data Engineer Challenge with SQL │ ├── Data Engineer Challenge with SQL.sql │ └── Data │ │ ├── ms_pelanggan.sql │ │ ├── ms_produk.sql │ │ ├── tr_penjualan.sql │ │ └── tr_penjualan_detail.sql │ ├── Project Data Analysis for B2B Retail Customer Analytics Report │ ├── Data │ │ ├── customer.sql │ │ ├── orders_1.sql │ │ └── orders_2.sql │ └── Project Data Analysis for B2B Retail Customer Analytics Report.sql │ ├── Project Data Analysis for Retail Sales Performance Report │ ├── Data │ │ └── dqlab_sales_store.sql │ └── Project Data Analysis for Retail Sales Performance Report.sql │ └── Project Fundamental SQL Group By and Having │ ├── Data │ ├── customer.sql │ ├── invoice.sql │ ├── product.sql │ └── subscription.sql │ └── Project Fundamental SQL Group By and Having.SQL ├── README.md ├── README ├── 4.1.png ├── 4.2.png ├── 4.png ├── 5.1.png ├── 5.png ├── 6.png ├── Career.jpg ├── DQLab.jpg ├── DQ_Lab2.png ├── Learn.jpg ├── Poster.png ├── Poster2.png ├── Project.jpg ├── Yuk.png ├── analytics.png ├── analytics2.png ├── data analyst.png └── hal.png └── _config.yml /.gitattributes: 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