Python Fundamentals with Paul Deitel, 2nd Edition [Update 04/2026]
English | Size:
Genre: eLearning[/center]
Expanded in 2025
50+ hours of video instruction-Includes Paul's two-hour "What's New in Python" lesson (located between lessons 10 and 11), covering features that were added in Python 3.8-3.12 and several additional features from earlier Python versions, and a new 3.5-hour Lesson 18, Building API-Based Python GenAI Applications with the OpenAI Generative APIs.
Python Fundamentals: with Integrated GenAI, 2/e, Under Development
Paul is recording new and updated lessons that will gradually replace this course's content. The video "Watch This First! Python Fundamentals, 2/e Sneak Peek" outlines the forthcoming Second Edition's updates, including new Python features through Python 3.14, new and enhanced data science and AI lessons, and integrated Generative AI (both prompting and API programming). New lessons will be marked as "New in 2025" or "New in 2026," until the Second Edition is completed.
Overview
The professional programmer's Deitel® video guide to Python development with the powerful IPython interpreter and Jupyter Notebooks. [Note: Paul is developing the second edition of this 50-hour video course and will post new and updated lessons here as they become available.]
Python Fundamentals LiveLessons with Paul Deitel is a code-intensive presentation of Python-one of the world's most popular and fastest growing languages. In the context of hundreds of real-world code examples ranging from individual snippets to complete scripts, Paul demonstrates coding with the interactive IPython interpreter and Jupyter Notebooks. You'll quickly become familiar with the Python language, its popular programming idioms, key Python Standard Library modules and popular third-party, open-source libraries. In the Intro to Data Science videos, Paul lays the groundwork for later lessons in which he introduces some of today's most compelling, leading-edge computing technologies, including natural language processing, data mining social media, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning with a convolutional neural network, sentiment analysis through deep learning with a recurrent neural network, and big data infrastructure topics including Spark™ streaming, NoSQL databases and the Internet of Things (IoT).
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