Silabus Belajar Bareng Python

Silabur belajar ini diambil dari tau-data.id :

Python for Data Science I – Beginner:

1. Pendahuluan (1 Jam):
   * The Zen of Python
   * Python “distro” : Python, Anaconda/miniconda, WinPython, etc.
   * Editor Jupyter & Spyder
   * Python VS (R, Julia, Matlab, Java, C, PHP, etc)
   * beberapa kelemahan & kelebihan Python
   * Google Colab
2. Dasar Python (1 Jam)
   * Syntax Format (indenting, multiline, import, deklarasi/inisialisasi)
   * Code descriptor & Comments
   * integer, float, Bytes, Boolean
   * list, tuple, dictionary
   * (Frozen) Set
   * types : Beginner Pitfall
   * Slicing in Python
3. Python Logic (3 Jam)
   * (Nested – hierarchical) if Logic
   * Looping For (& list comprehension)
   * Iterator VS Iterable
   * Looping while
   * Breaking Loop
   * Python Exception
   * TQDM
4. Penggunaan & Instalasi Modul (1 Jam)
   * Full and Partial Import
   * Import all functions as first level implicitly
   * Personal Library
   * Conda/pip/easy_install
   * Adding repository modul
   * Automatic update all modules
   * Pure Python vs compiled Modules
   * Module’s Wheels
   * Check modules dependency
   * Installing from Source
   * Installing modul from script
5. Going Deeper in Python (2 jam)
   * Deeper with Print Function
   * Reference/pointer to variable(s)
   * Deeper with Python string
   * List/Dictionary comprehension
   * Zipping List
   * List again : Kelebihan List di Python
   * Optimal Python Data Type use case
6. Python Function (2 Jam)
   * Fungsi di Python
   * Global & local variable
   * vars, dirs**
   * Recursive in Python
   * Lamda Function
7. Python as Numerical computing & (simple) Visualizations (2 Jam)
   * Numpy Matrix:
   * List VS Arrays/Matrix: best use scenarios, etc.
   * Linear Algebra Functions
   * Numpy Operations, etc.
   * DataFrame Basics
   * MatplotLib & Seaborn: Visualisasi dasar di Python
   Scatter plot, histogram, barchart, boxplot, etc.