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A functional, Data Science focused introduction to Python
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Functional, Data Science Intro To Python

The first section is an intentionally brief, functional, data science centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible.

The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, commandline tools, recommendation engines, Sentiment Analysis and Cloud Computing.

Pragmatic AI Labs

Pragmatic AI Labs

These notebooks and tutorials were produced by Pragmatic AI Labs. You can continue learning about these topics by:

Safari Online Training: Essential Machine Learning and Exploratory Data Analysis with Python and Jupyter Notebook

Recommended Preparation Material:

Day1-Part1-Google Colab Notebook

1.1-1.2: Introductory Concepts in Python, IPython and Jupyter

  • Introductory Concepts in Python, IPython and Jupyter
  • Functions

Day1-Part2-Google Colab Notebook

1.3: Understanding Libraries, Classes, Control Structures, Control Structures and Regular Expressions

  • Writing And Using Libraries In Python
  • Understanding Python Classes
  • Control Structures
  • Understanding Sorting
  • Python Regular Expressions

Day2-Part1-Google Colab Notebook

2.1: IO Operations in Python and Pandas and ML Project Exploration

  • Working with Files
  • Serialization Techniques
  • Use Pandas DataFrames
  • Concurrency in Python
  • Walking through Social Power NBA EDA and ML Project

Day2-Part2-Google Colab Notebook:

2.2: AWS Cloud-Native Python for ML/AI

  • Introducing AWS Web Services: Creating accounts, Creating Users and Using Amazon S3
  • Using Boto
  • Starting development with AWS Python Lambda development with Chalice
  • Using of AWS DynamoDB
  • Using of Step functions with AWS
  • Using of AWS Batch for ML Jobs
  • Using AWS Sagemaker for Deep Learning Jobs
  • Using AWS Comprehend for NLP
  • Using AWS Image Recognition API

Local, non-hosted versions of these notebooks are here:

Screencasts (Can Be Watched from 1-4x speed)

  • Data Science Build Project
  • Data Science Build Project

Older Version of Python Fundamentals (Safari Version Is Newer)

Additional Topics

Python Programming Recipes

Managed ML and IoT

Software Carpentary: Testing, Linting, Building

Concurrency in Python

Cloud Computing-AWS-Sentiment Analysis

Recommendation Engines

Cloud Computing-Azure-Sentiment Analysis

Cloud Computing-AWS

Cloud Computing-GCP

Machine Learning and Data Science Full Jupyter Notebooks

Data Visualization

Seaborn Examples


Creating Commandline Tools

Creating a complete Data Engineering API

Statically Generated Websites

Deploying Python Packages to PyPi

Web Scraping in Python

Logging in Python

Conceptual Machine Learning

Linear Regression

Machine Learning Model Building for Regression

Mathematical and Algorithmic Programming



The text content of notebooks is released under the CC-BY-NC-ND license

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