Python for data science - How to write programs(practice)

Final project part 1 - collecting, exploring, cleaning, analyzing, and visualizing a car dataset.

Final project part 2 - collecting, exploring, cleaning, analyzing, and visualizing a car dataset

Pandas and Jupyter-notebooks setup - How to install Python libraries using pip

Environment setup to start writing python programs.

Python for data science - part 2 - Data Structures

Data visualization using the Matplotlib Library - Intro

The "Series" - manipulating tabular data

Key statistical concepts - part 1 - the measures of central tendency, dispersion, and position

Python for data science - part 1 - Introduction to python

Python for data science - Midpoint project - putting together what we learned

Python for data science - part 3 - practicing conditionals and loops

Python for data science - How to write programs(practice)

Python for data science - Functions

Key statistical concepts - part 2 - Data distribution (center, spread, shape, and unusual features)

Data analysis using the Pandas Library - Intro

DataFrames - manipulating tabular data - Part 2

Python for data science - part3 - Conditionals

Key statistical concepts - part 4 - populations vs samples

Python for data science - part 4 - Code Tracing

DataFrames - manipulating tabular data - Part 1

Data visualization using the Matplotlib Library - Creating graphs

What skills you are expected to learn in this series?

Python for data science - Part 3 - Loops

Python for data science - part 6 - Object-Oriented Programming