Learn Python and Data Science in Just an Hour

Overview

This course aims to teach the basics of data science and Python in just an hour. By working with student data to predict grades based on study hours, learners will acquire skills such as using Visual Studio Code, Anaconda, Jupyter Notebooks, Pandas, and Matplotlib. The teaching method involves hands-on practice with creating charts, histograms, box plots, and regression lines. This course is intended for beginners in data science and Python, even those without prior knowledge in these areas.

Syllabus

Getting started with Visual Studio Code and Anaconda
Installing Jupyter Notebooks and Python
Creating a Jupyter Notebook
Working with data
Introduction to Pandas
Working with Data Frames
Read a CSV file into a Pandas Data Frame
Remove Null values in data
Adding a column to a Data Frame
Grouping data using 'groupby'
Creating charts from data
Rainbow CSV
Using Matplotlib to make charts
Customizing charts with Matplotlib
Creating a pie chart with Matplotlib
Creating a chart directly from Data Frame
Data Science, Samples, and Distributions
Creating a histogram with Matplotlib
Central Tendencies, Mean, Median, and Mode
Creating a boxplot with Matplotlib
Visualizing probability density with Matplotlib
Creating a Jupyter Notebook
Statistical Outliers
Variance, Range, and Standard Deviation
68% Rule
Analyzing box plots
Normalizing ranges
Calculating Correlation value
Using regression lines
Least squares regression
Things are getting interesting
Thank you for learning with us!