Coursera

Select Topics in Python: Packaging (Coursera)

Offered by Codio,
Select Topics in Python: Packaging (Coursera)

Code and run Django websites without installing anything! This course is designed for learners who some experience with Python. The modules in this course cover modules and packages, third-party packages, and packing for distribution.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to slowly building features, resulting in large coding projects at the end of the course.
Course Learning Objectives:

  • Use pip to venv to manage virtual environments and packages
  • Use third-party package managers to manage virtual environments and packages
  • Package Python scripts and applications for a wider audience

Course 1 of 4 in the Select Topics in Python Specialization.

What You Will Learn

  • Manage packages and virtual environments with Python's built-in tools
  • Manage packages and virtual environments with third-party tools
  • Package Python scripts and applications for a wider audience

Syllabus

WEEK 1
Packaging in Python
Welcome to Week 1 of the Select Topics in Python: Packaging course. These assignments cover what is a Python package and how they relate to modules, creating your own package, importing and using third-party packages, and how to bundle your package into a wheel to be used by others. The module ends with a hands-on lab and graded coding exercises.

WEEK 2
Alternative Package Managers
Welcome to Week 2 of the Select Topics in Python: Packaging course. These assignments cover the Poetry and Conda package managers. You will learn how to create virtual environments, install and remove packages, create a requirements file, and bundle packages for use by a wider audience. The module ends with a hands-on lab and graded coding exercises.

WEEK 3
Packaging for Distribution
Welcome to Week 3 of the Select Topics in Python: Packaging course. These assignments cover packaging a Python project into something easily used by others. Learn how to take text-based and graphical projects and turn them into executable files, as well as bundle a Flask web app for hosting. The module ends with a hands-on lab and graded coding exercises.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Python Project: pillow, tesseract, and opencv (Coursera) Coursera
University of Michigan

Python Project: pillow, tesseract, and opencv (Coursera)

CS: Software Engineering CS: Programming

This course will walk you through a hands-on project suitable for a portfolio. You will be introduced to third-party APIs and will be shown how to manipulate images using the Python imaging library (pillow), how to apply optical character recognition to images to recognize text (tesseract and py-tesseract), and how to identify faces in images using the popular opencv library. By the end of the course you will have worked with three different libraries available for Python 3 to create a real-world data-analysis project.

Jun 8th 2026
3 Weeks
Programming Python OpenCV
Details
AI Workflow: Machine Learning, Visual Recognition and NLP (Coursera) Coursera
IBM

AI Workflow: Machine Learning, Visual Recognition and NLP (Coursera)

Data Science

This is the fourth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Course 4 covers the next stage of the workflow, setting up models and their associated data pipelines for a hypothetical streaming media company.

Jun 8th 2026
2 Weeks
Artificial Intelligence NLP Machine Learning
Details
AI Workflow: Business Priorities and Data Ingestion (Coursera) Coursera
IBM

AI Workflow: Business Priorities and Data Ingestion (Coursera)

Data Science

This is the first course of a six part specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. This first course in the IBM AI Enterprise Workflow Certification specialization introduces you to the scope of the specialization and prerequisites.

Jun 8th 2026
2 Weeks
Artificial Intelligence Machine Learning Data Science
Details
M2M & IoT Interface Design & Protocols for Embedded Systems (Coursera) Coursera
University of Colorado Boulder

M2M & IoT Interface Design & Protocols for Embedded Systems (Coursera)

CS: Design & Product Computer Science

This course can also be taken for academic credit as ECEA 5348, part of CU Boulder’s Master of Science in Electrical Engineering degree. M2M and IoT Interface Design and Protocols is the third of three classes in the Embedded Interface Design (EID) specialization, an online version of the on-campus EID class taught in graduate embedded systems design. This course is focused on connecting devices to each other and to the cloud to create prototypes and actual systems that flow data from devices to consumers. The class includes an introduction to M2M (Machine-to-Machine) and IoT (Internet of Things) concepts, using the cloud to develop IoT systems (specifically AWS (Amazon Web Services) and its IoT framework), a review of common communications protocols at every level of connected devices, and other IoT design concerns such as security, message queuing approaches, and the use and design of APIs and microservices .

Jun 8th 2026
4 Weeks
Python Cloud Prototyping
Details
Introduction to Data Science in Python (Coursera) Coursera
University of Michigan

Introduction to Data Science in Python (Coursera)

CS: Software Engineering Statistics & Data Analysis

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

Jun 8th 2026
4 Weeks
Python Data Analysis Data Science
Details
The Raspberry Pi Platform and Python Programming for the Raspberry Pi (Coursera) Coursera
University of California, Irvine

The Raspberry Pi Platform and Python Programming for the Raspberry Pi (Coursera)

CS: Software Engineering

The Raspberry Pi is a small, affordable single-board computer that you will use to design and develop fun and practical IoT devices while learning programming and computer hardware. In addition, you will learn how to set up up the Raspberry Pi environment, get a Linux operating system running, and write and execute some basic Python code on the Raspberry Pi. You will also learn how to use Python-based IDE (integrated development environments) for the Raspberry Pi and how to trace and debug Python code on the device.

Jun 8th 2026
4 Weeks
Programming Python Computer Programming
Details
Applied Data Science Capstone (Coursera) Coursera
IBM

Applied Data Science Capstone (Coursera)

Statistics & Data Analysis Data Science

This capstone project course will give you a taste of what data scientists go through in real life when working with data. You will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize Python and its pandas library to manipulate data, which will help you refine your skills for exploring and analyzing data. Finally, you will be required to use the Folium library to great maps of geospatial data and to communicate your results and findings.

Jun 8th 2026
5-12 Weeks
HTML Clustering Data Analysis
Details
Data Analysis Using Python (Coursera) Coursera
University of Pennsylvania

Data Analysis Using Python (Coursera)

Statistics & Data Analysis Data Science

This course provides an introduction to basic data science techniques using Python. Students are introduced to core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib. This course provides an overview of loading, inspecting, and querying real-world data, and how to answer basic questions about that data. Students will gain skills in data aggregation and summarization, as well as basic data visualization.

Jun 8th 2026
3 Weeks
Data Analysis Data Science Data Visualization
Details
Machine Learning with Python (Coursera) Coursera
IBM

Machine Learning with Python (Coursera)

Data Science

This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms.

Jun 8th 2026
5-12 Weeks
Programming Python Machine Learning
Details