Tuesday, 5 March 2019

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.



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