Courseware access: https://www.softwaretutorialservices.com/course/55264b
55264B is a five-day, beginner-level Instructor-Led / Self-paced Python course developed in 2026 using Courseware Studio. It modernizes the earlier 55264A Introduction to Programming Using Python course authored by Neil Tucker for Microsoft Learning.
55264B is an independently developed successor and is not presented as a current Microsoft course or Microsoft-endorsed product.
The course is grounded in Python 3.12 and emphasizes practical programming skills for current AI, machine learning, data-processing, API, and cloud-deployment workflows. Students learn to write, debug, document, and deploy Python applications while working with Google Colab, REST APIs, LLM integrations, Streamlit, GitHub, and cloud-hosted application platforms.
The Software Tutorial Services course provides access to both delivery modes:
- Instructor-Led Training (ILT) - structured learner content, labs, module reviews, and supporting course resources.
- Self-paced eLearning - an independent narrated learning experience produced from the same approved course foundation.
The Self-paced experience includes module introductions, narrated learning scenes, knowledge checks, guided application, labs/practice, module reviews, and learner resources.
Courseware Studio Self-paced eLearning supports Standalone HTML5, SCORM 1.2, SCORM 2004, xAPI, and cmi5 delivery formats. The LMS packages themselves are not distributed from this public repository.
- Course number: 55264B
- Title: Introduction to Programming Using Python
- Duration: 5 days
- Modules: 16
- Audience level: Beginner
- Format: Instructor-Led / Self-paced
- Primary runtime: Python 3.12
- Primary lab environment: Google Colab
This 5-day course teaches Python programming with a strong emphasis on AI and machine-learning infrastructure. Students build clean Python code, work with data structures and data pipelines, consume REST APIs, integrate LLM services, apply debugging and exception-handling techniques, and deploy interactive Python applications.
Hands-on work uses Google Colab for low-configuration development. Later modules introduce GitHub-based workflows and deployment of Streamlit applications to cloud-hosted platforms.
AI Chat Assistant: This course features an integrated, interactive AI Tutor available 24/7 directly within the courseware platform at no additional cost. Learners can ask questions in real time to explore Python 3.12 syntax, examine data pipeline architectures, investigate REST API and LLM integrations, and all other course topics.
Students will be able to:
- Implement Python 3.12 data structures, type annotations, and mathematical operations used in machine-learning data workflows.
- Construct data-processing pipelines using loops, comprehensions, generators, and functional programming patterns.
- Build Web API integrations, JSON serialization workflows, and authenticated LLM API connections.
- Create maintainable programs using exception handling, custom exceptions, structured logging, and PEP 8-aligned practices.
- Develop and deploy interactive Python AI web applications using Streamlit and GitHub-based deployment workflows.
- Experience performing basic command-line operations on Windows, Linux, or macOS.
- Approximately six months of experience writing code in any programming language is recommended.
- Variables, Type Hinting, and Mathematical Operators
- Data Collections for Feature Engineering
- Standard Library Utilities for Data Workflows
- Dependency Management and ML Runtimes
- Algorithmic Branching and Decision Logic
- Loops and Iterative Data Pipelines
- Pythonic Comprehensions and Performance Optimization
- File System Pipelines and Stream I/O
- Data Serialization and Cloud API Interactivity
- Modularizing Code with Functional Programming
- Code Standards, PEP 8, and Maintainability
- Debugging and Algorithmic Diagnosis
- Exception Handling and System Logging Workflows
- Machine Learning Integrations and LLM Pipelines
- Building Python Web Applications and Cloud Deployment
- AI-Powered Web Application Capstone
See COURSE_OUTLINE.md for module descriptions and labs.
55264B_EN_Syllabus.pdf- current course syllabusCOURSE_OUTLINE.md- module-by-module outline and lab listSELF_PACED_ELEARNING.md- explanation of the Self-paced eLearning version and its relationship to ILT55264B-Readme.txt- compact course/repository notes
- Course access: https://www.softwaretutorialservices.com/course/55264b
- Courseware Studio: https://coursewarestudio.ai
- Previous course repository (55264A): https://github.com/neiltucker/55264A
This repository provides public course information and companion resources. Full courseware, learner materials, instructor resources, and Self-paced eLearning access are provided through Software Tutorial Services or authorized delivery arrangements.