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Python

Python Cookbook: Recipes for AI and Machine Learning

Published by Pearson

Intermediate content levelIntermediate

Master the art of data science in Python with a showcase of reusable projects

  • Learn time-tested data science "recipes" that you can put into practice immediately in your own data science projects using Python and Jupyter
  • Get hands-on, real-world experience with examples that incorporate the latest Python/data science technologies
  • Create a high-quality portfolio that you can show off to interviewers

In today's data-driven world, data science has become a vital discipline for extracting meaningful insights and making informed decisions. This course empowers learners to navigate the vast landscape of data science with confidence. By exploring several essential recipes, participants will learn how to preprocess and analyze data, implement machine learning algorithms, visualize results, and derive valuable insights. The practical hands-on experience with Jupyter notebooks enables participants to apply these recipes in real-world scenarios, fostering a deeper understanding of data science concepts and topics, such as ChatGPT, and preparing them for success in data-driven industries. This course serves as a stepping stone for individuals aspiring to become proficient data scientists or for professionals seeking to enhance their data science skills using Python and Jupyter.

What you’ll learn and how you can apply it

By the end of the live online course, you’ll understand:

  • The basics of neural networks
  • How to use these concepts to solve real-world problems
  • Key topics such as sentiment analysis, image recognition, and much more

And you’ll be able to:

  • Create and train neural networks in Jupyter
  • Scrape basic data from websites and APIs
  • Perform sentiment analysis on text data

This live event is for you because...

  • You know the basics of data science and working with Python and Jupyter, but want some real-world experience with these tools
  • You want to build a portfolio of high-quality data science projects
  • You want to take your full-stack data science skills to the next level by learning extremely important but seldom-covered strategies

Prerequisites

  • Basic knowledge of Python
  • Basic knowledge of Jupyter

Course Set-up

Recommended Preparation

Recommended Follow-up

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Recipe 1: In a Sentimental Mood: Performing Sentiment Analysis (45 minutes)

  • Sentiment analysis basics
  • What are our options?
  • Coding demo

Q&A (5 minutes)

Break (10 minutes)

Recipe 2: Do I Know You from Somewhere? Performing Image Recognition (45 minutes)

  • Image recognition basics
  • What are our options?
  • Coding demo

Q&A (5 minutes)

Break (10 minutes)

Recipe 3: World Wide Web Whispering: Scraping Data from the Internet (45 minutes)

  • Web-scraping basics
  • What are our options?
  • Coding demo

Q&A (5 minutes)

Break (10 minutes)

Recipe 4: Feeling Chatty: Using ChatGPT in Jupyter (45 minutes)

  • ChatGPT API basics
  • What are our options?
  • Coding demo

Q&A (5 minutes)

Break (10 minutes)

Recipe 5: Neural Networking: Training Neural Nets (45 minutes)

  • Neural networking basics
  • What are our options?
  • Coding demo

Q&A (10 minutes)

Course wrap-up and next steps (5 minutes)

Your Instructor

  • Shaun Wassell

    Shaun Wassell is a lifelong programmer and problem-solving addict. His goal is to help people build incredible software and solve meaningful problems by mastering the art of software development. For the past 2+ years, he's been a trainer at CBT Nuggets, and focuses on creating high-quality web development and certification content. You can check out his extensive collection of React, Angular, Python and JavaScript courses, as well as a huge amount of other software- and IT-training content at cbtnuggets.com.