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1
Sesi 1-6: Fundamental Python for Data Science (00:00)
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Sesi 1: Intro to Python
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Sesi 2: Control Flow: Conditional, Looping
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Sesi 3: Function, Module, Package
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Sesi 4: Numpy
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Sesi 5: Pandas Introduction
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Sesi 6: Data Cleaning with Pandas
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2
Sesi 7: Visualisasi Dasar (00:00)
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Exploring Dataset with Pandas
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Visualisasi Dasar: Overview
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3
Sesi 8: Visualisasi Menengah (00:00)
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Word Cloud dan Waffle Charts
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Map with Folium
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4
Sesi 9: Membuat Report dan Visualisasi (00:00)
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Publication-Grade Plot for London Crime Dataset
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5
Sesi 10-12: Statistics (00:00)
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Sesi 10: Descriptive Statistics
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Sesi 11: Inferential Statistics
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Sesi 12: Statistical Treatment for Retail Datasets
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6
Sesi 13: Machine Learning Introduction and Regression Models (00:00)
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Introduction to Machine Learning
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Machine Learning Models: Overview
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Regression Models
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7
Sesi 14-15: Classification Models (00:00)
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Sesi 14: Logistic Regression, KNN
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Sesi 15: Naive Bayes, Decision Tree, Random Forest, SVM
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8
Sesi 16: Building a Supervised Machine Learning Model (00:00)
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Insurance Charges Prediction
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Term Deposit Subscription Prediction
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9
Sesi 17: Unsupervised Machine Learning Models (00:00)
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Copy of Unsupervised
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Clustering Model Evaluation
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10
Sesi 18: Feature Engineering (00:00)
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Feature Engineering
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11
Sesi 19-20: Time Series (00:00)
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Sesi 19: Time Series 1
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Sesi 20: Time Series 2
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Time Series Demo
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12
Sesi 21: Python Data Science Final Project (00:00)
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Solving a Problem with Machine Learning Model
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13
SQL (00:00)
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Sesi 1: Inroduction to Database and SQL
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Sesi 2: Basic DDL, DML and Query
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Membuat ecommerce_DB
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Sesi 3: Advanced Query (Joining Multiple Tables)
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Latihan SQL dengan ecommerce_DB
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Sesi 4: Aggregation Function
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Sesi 5: Subquery and Common Table Expression
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Latihan Aggregation di SQL
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File untuk Project SQL
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Sesi 6: Project SQL
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Sesi 6: TSQL
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File untuk Sesi 7
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Sesi 7: Handling Concurrency with Transaction
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Sesi 8: Stored Procedure and User privileges
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Latihan Stored Procedure and User Privileges
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File untuk Sesi 9
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Sesi 9: Database Indexing
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File untuk Sesi 10
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Sesi 10: Final Project
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14
Data Engineering with AWS (00:00)
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Sesi 1: Data Warehouse
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Sesi 2: Data Ingestion with AWS
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Day 3: Data Engineering Overview
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Day 4: ETL with AWS
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Sesi 5: Visualization with AWS
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Sesi 6: Project - ETL dengan AWS
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Sesi 7: Data Governance
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Sesi 8: Final Project - Membuat End to End Data Ingesion, Warehouse, Visualization di AWS
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Sesi 9: Docker
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