Data Science with Python 4 days (32 hours)

Audience: Previous experience with Python is required.

Description: Python has become the premier language of data science. Not only is the syntax short and readable, but Python now has widely-used libraries to cover any use case.

This course will cover the essentials of the Python data science ecosystem. Students will use Numpy and Pandas to analyze tabular data, create graphs with Matplotlib, and build predictive models with Scikit-Learn.

By the end of the course, students will be able to extract data from various sources, do exploratory analysis and basic machine learning.

This course will alternate between short lectures and exercise sessions, so that students leave with both theoretical and hands-on understanding. All slides, exercises and solutions will be available online afterwards for further practice

For availability and pricing, please schedule a call or send a message.

Syllabus

Review

• Jupyter Notebooks
• Functions and Methods
• Booleans
• Lists
• Dictionaries
• Importing Packages

Numpy

• Numpy Arrays
• Broadcasting
• Element-Wise Operations
• Boolean Indexing
• Boolean Filters
• Numpy Methods

Pandas Dataframes

• Dataframe
• Series & Index
• Filtering a Dataframe

Data Analysis

• Summary Statistics
• Group By
• Pivot Tables

Sources of Data

• Database Tables
• APIs
• Timeseries data

Matplotlib

• PyPlot
• Style Configuration
• Line Plots
• Bar Charts
• Histograms

Scikit-Learn

• Linear Regression
• Logistic Regression