scholarly, a module that allows you to retrieve author and publication information from Google Scholar in a friendly, Pythonic way, https://pypi.org/project/scholarly/
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
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
Python Logic (3 Jam) * (Nested – hierarchical) if Logic * Looping For (& list comprehension) * Iterator VS Iterable * Looping while * Breaking Loop * Python Exception * TQDM
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
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
Python Function (2 Jam) * Fungsi di Python * Global & local variable * vars, dirs** * Recursive in Python * Lamda Function
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.