This topic will touch on the different types of integrated development environments (IDEs), their installation and set up. We will also cover creation of virtual environments and installation of Python packages.
Integrated Development Environment
Package Installation
Must-know fundamentals – 1
In this topic, we will cover fundamental topics that are critical parts of a Data Scientist's toolbox. In this first part, we will cover topic such as functions, positional and keyword arguments, and *args and **kwargs.
Functions
Positional and keyword arguments, *args and **kwargs
Must-know fundamentals – 2
In this topic, we will continue on the fundamental topics that are critical parts of a Data Scientist's toolbox. In this first part, we will cover list, list comprehension, and tuples.
Lists and List Comprehension
Tuples
Must-know fundamentals – 3
Still building on the fundamental topics that are critical parts of a Data Scientist's toolbox, we will cover dictionaries, lambda expressions, and sets.
Dictionaries
Lambda Expressions
Sets
Packages for Data Science
In this topic, we will now touch the the most popular and powerful Python packages for data science, including Numpy, Pandas, Matplotlib and Scikit Learn
Numpy (Numerical Python)
Pandas
Matplotlib
Scikit Learn (sklearn)
Concluding Remarks
Here, we will talk about the logical next step and briefly touch on some advanced topics to give you some possible directions.
