We may earn an affiliate commission when you visit our partners.
Course image
JPDocu School of Technical Writing and Sehrish Aqeel

Are you a technical writer who wants to learn about the Python programming language? Or do you want to advance your career as a technical writer in the software development industry?

If your answer is yes, then this course can help you.

Python is currently the most popular programming language in the world. According to SlashData, "there are now 8.2 million developers in the world who code using Python, and that population is now larger than those who build in the Java language."

Read more

Are you a technical writer who wants to learn about the Python programming language? Or do you want to advance your career as a technical writer in the software development industry?

If your answer is yes, then this course can help you.

Python is currently the most popular programming language in the world. According to SlashData, "there are now 8.2 million developers in the world who code using Python, and that population is now larger than those who build in the Java language."

If you are serious about your technical writing career, you must be able to communicate efficiently with your development team about the software code they have been developing. Moreover, top-paying companies in the software industry often require technical writers to not only read and understand Python source code but also to develop sample code exercises that enrich developers' documentation.

But how can you do that if you're just a technical writer who has never written a single line of code? You should find someone to show and guide you through this software development jungle, preferably quickly so that you can get back to writing documentation that helps your target users.

This course is designed to help technical writers learn Python programming language in order to communicate more efficiently with their development team and develop sample code exercises for documentation.

Ph.D. Sehrish Aqeel, a top expert in Python from JPDocu School of Technical Writing, shares her vast experience with Python in a friendly and relaxed manner. She has over 14 years of experience teaching at the university and online, and now she shares her knowledge with the technical communications community through this course through practical explanations and hands-on exercises.

By the end of the course, participants will become technical writers who can confidently read and understand Python source code, use Python terminology, and develop a simple application following the instructor's guidelines.

You will soon realize that Python language can be easy to understand and learn when you have the right teacher. There is no complicated theory, just practical explanations, and simple hands-on exercises to smoothly introduce you to the language. Of course, this course does not aim to turn you into a developer - do not expect to gain solid development skills here. However, by the end of this course, you will become a technical writer who can read and understand Python source code, use Python's terminology confidently, and get the chance to develop a simple application yourself, following the instructor's guidelines.

So, enroll now and see how simple and easy Python can be. Impress your development team with the skills of a professional technical writer who knows Python language too.

Enroll now

What's inside

Learning objectives

  • You will be able to read the basic syntax of python programming language
  • Set up and install an environment for working with python (anaconda)
  • Understand the meaning and intended use of common python techniques (elif, while, for, comments, etc.)
  • Perform hands-on exercises and a mini-project to practice what you've learned

Syllabus

Introduction
Comments - Exercise 1
Installation and Interface Explanation
Basic Syntax, Input and Output Operations
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Provides hands-on exercises and a mini-project, allowing learners to immediately apply their knowledge and build a portfolio piece
Taught by an instructor with 14 years of experience teaching Python, which can help learners grasp the fundamentals more easily
Covers how to write documentation for a Python application, which is a highly valuable skill for technical writers in the software industry
Focuses on practical explanations and simple exercises, which can be beneficial for technical writers who are new to programming
Uses Anaconda, a distribution of Python, which simplifies package management and deployment, making it easier to set up a development environment
Does not aim to turn learners into developers, which may not be suitable for technical writers seeking in-depth programming knowledge

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.
Save

Reviews summary

Technical python introduction for writers

According to learners, this course is a highly effective introduction to Python for technical writers with little to no prior coding experience. Students praise the clear explanations provided by the instructor and the useful hands-on exercises and final project, which help build confidence in reading and understanding code. Some learners with prior programming knowledge found the pace slow or the depth limited, which aligns with the course's stated goal of not creating developers. A few students also reported difficulties with the initial software setup, occasionally requiring external troubleshooting. Overall, it successfully helps technical writers bridge the gap and communicate more effectively with development teams.
Course includes helpful hands-on examples and projects.
"Practical examples were helpful."
"...the hands-on exercises are excellent."
"The final project was a good way to tie things together."
Instructor explains concepts effectively and clearly.
"Dr. Aqeel explains things so clearly and the hands-on exercises are excellent."
"The instructor is very knowledgeable and presents the material in an engaging way."
"I feel much more confident discussing code now."
Highly effective for technical writers new to Python.
"As a technical writer with zero coding experience, this course was perfect."
"This course is exactly what a tech writer needs to get a foothold in understanding Python codebases."
"It's probably good for absolute beginners though."
Some learners encountered issues with installation steps.
"Setup instructions were a bit tricky on my specific OS."
"I struggled with the Anaconda installation mentioned in the setup."
"Had to find external resources to get it working."
May be too slow or basic for those with prior coding skills.
"Too slow and basic for me. I have a little programming background..."
"It's not deep, but it gives you the language and basic structure knowledge."
"Don't expect to become a developer, which is fine as the course states."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Technical Writing: Getting Started with Python with these activities:
Review Basic Programming Concepts
Reinforce fundamental programming concepts like variables, data types, and control flow to better understand Python's syntax and structure.
Browse courses on Programming Fundamentals
Show steps
  • Review online tutorials or introductory programming books.
  • Practice writing simple programs in any language.
  • Focus on understanding variables, loops, and conditional statements.
Review "Python Crash Course"
Gain a comprehensive understanding of Python through a project-based approach, reinforcing concepts learned in the course.
Show steps
  • Work through the initial chapters covering Python basics.
  • Choose a project from the book that aligns with documentation tasks.
  • Complete the project, paying attention to code clarity and documentation.
Review "Automate the Boring Stuff with Python"
Learn practical Python skills for automating tasks, which can be directly applied to creating documentation examples and understanding code.
Show steps
  • Read the chapters relevant to basic Python syntax and data structures.
  • Complete the practice exercises in each chapter.
  • Try to adapt the examples to documentation-related tasks.
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice Python Syntax Exercises
Reinforce Python syntax through repetitive exercises, focusing on areas like loops, conditionals, and data structures.
Show steps
  • Find online resources with Python syntax exercises.
  • Complete at least 10 exercises per week, focusing on different concepts.
  • Review solutions and understand any mistakes.
Write a Blog Post on Python for Technical Writers
Solidify understanding by explaining how Python can be used in technical writing, targeting other technical writers as the audience.
Show steps
  • Research common Python use cases in technical writing.
  • Outline the blog post with clear sections and examples.
  • Write the blog post, explaining concepts in simple terms.
  • Edit and proofread the post before publishing.
Create a Simple Python Script for Documentation
Apply learned Python concepts by creating a script that automates a documentation-related task, such as generating a table of contents or formatting code snippets.
Show steps
  • Identify a repetitive documentation task that can be automated.
  • Write a Python script to perform the task.
  • Test the script and refine it as needed.
  • Document the script's functionality and usage.

Career center

Learners who complete Technical Writing: Getting Started with Python will develop knowledge and skills that may be useful to these careers:
Technical Communicator
A technical communicator specializes in translating complex technical information into easily understandable content for various audiences. The ability to read and understand Python source code, as emphasized in this course, helps a technical communicator collaborate more effectively with development teams. Understanding Python empowers them to create accurate and insightful documentation, tutorials, and user guides. Learning Python programming language allows a technical communicator to better support developers and end-users. This course specifically helps by providing a foundation in Python syntax, data types, and control structures, ensuring that the technical communicator can confidently navigate and interpret code.
Documentation Specialist
A documentation specialist creates and maintains documentation for software, hardware, and other technical products. This course helps documentation specialists because it provides a practical introduction to Python. By learning to read and understand Python source code, documentation specialists can improve the accuracy and relevance of their work. The course's focus on hands-on exercises and a mini-project provides valuable experience in applying Python concepts, helping the documentation specialist to create more effective examples and tutorials. This understanding allows documentation specialists to communicate more effectively with developers, leading to higher quality documentation.
Content Developer
Content developers design and create engaging content for various platforms, often focusing on technical subjects. This course helps a content developer in the software space by giving them familiarity with Python. Python is a very commonly used language. Understanding Python enables them to develop more effective learning materials, tutorials, and documentation for software products. The course's emphasis on practical explanations and hands-on exercises helps content developers gain a solid understanding of Python concepts. This course provides a practical and efficient way for content developers to quickly acquire the skills they need to create high-quality, Python related content.
API Writer
An API writer is responsible for creating documentation for Application Programming Interfaces, which are crucial for software integration. This course can be invaluable for API writers, particularly those working with Python-based APIs. The ability to read and understand Python code helps the API writer to accurately document API endpoints, data structures, and usage examples. The course's focus on practical exercises enables them to create more effective and user-friendly API documentation. By understanding Python's syntax and structure, an API writer can significantly improve the clarity and completeness of their documentation.
Technical Trainer
A technical trainer develops and delivers training programs on technical topics, often related to software or hardware. This course will be useful for technical trainers who need to teach Python or related technologies. The course's practical approach and hands-on exercises help technical trainers gain a solid understanding of Python concepts. The ability to read and understand Python source code, as taught in this course, allows technical trainers to provide more effective instruction and support to their students. By learning Python through this course, technical trainers can enhance their expertise and deliver more engaging and informative training sessions.
Instructional Designer
An instructional designer creates learning experiences and materials, often for online courses or training programs. This course may be especially useful for instructional designers who are developing courses related to software development or data science. The course's focus on Python programming and practical exercises enables instructional designers to create more effective and engaging learning materials. By understanding Python syntax and structure, instructional designers can develop more accurate and relevant content for their courses, thus improving the learning experience for students.
Software Support Specialist
A software support specialist provides technical assistance to users of software applications. This course may be beneficial for software support specialists who need to troubleshoot Python-related issues. The ability to read and understand Python source code allows software support specialists to diagnose problems more effectively and provide more accurate solutions to users. The course's practical exercises and hands-on learning approach can help software support specialists develop the skills they need to excel in their role. This course can help software support specialists to better assist users who are working with Python-based software.
Curriculum Developer
Curriculum developers research and create educational content and associated materials to guide learning within a subject area. This course may be helpful for curriculum developers who are building Python related subject matter. By learning the syntax of the Python programming language, curriculum developers can be more effective at designing a curriculum about Python. The course's structure of practical explanation and simple exercises gives curriculum developers insight into what will be effective when creating a curriculum as well as what content may be useful.
eLearning Developer
An eLearning developer designs and creates online learning materials, often using multimedia and interactive elements. This course may be useful for eLearning developers who are creating content related to software development or data analysis. The course's practical approach and hands-on exercises help eLearning developers gain a solid understanding of Python concepts. The ability to read and understand Python source code, allows eLearning developers to create more engaging and effective online learning modules. Completing this course lets eLearning developers better support the learning of Python.
Digital Learning Specialist
A digital learning specialist integrates technology into the educational process, creating engaging and effective online learning experiences. This course may be useful for digital learning specialists seeking to incorporate Python into their projects. The course's practical approach and hands-on exercises help digital learning specialists gain a solid understanding of Python concepts. The ability to read and understand Python source code, allows digital learning specialists to create more engaging and effective digital learning modules. Learning Python could improve one's ability to create effective digital learning.
Technical Sales Engineer
A technical sales engineer combines technical knowledge with sales skills to promote and sell complex technical products or services. This course may be helpful for technical sales engineers who are selling software or hardware solutions that involve Python. The ability to read and understand Python source code enables technical sales engineers to better understand the technical aspects of the products. The course's focus on practical exercises can also help them demonstrate the value of the product to potential customers. This course may let technical sales engineers better communicate with technical decision-makers.
Business Analyst
A business analyst analyzes an organization's processes and systems to identify areas for improvement. This course may be useful for business analysts who work with data-intensive projects or software development teams. While not directly related to the core responsibilities of a business analyst, the ability to read and understand Python source code can facilitate better communication with developers. The course's focus on practical exercises may also enhance their understanding of software development processes. Understanding Python may allow one to extract better insights.
Project Manager
A project manager is responsible for planning, executing, and closing projects, ensuring they are completed on time and within budget. While project managers may not directly write code, understanding Python, as taught in this course, may facilitate communication and collaboration with software development teams. The course's introduction to Python syntax and concepts can help project managers better grasp the technical aspects of software projects. This course may improve team member collaboration and project outcomes, especially in Python-focused projects.
Data Analyst
A data analyst examines data to identify trends, patterns, and insights that can inform business decisions. While this course primarily focuses on using Python for technical writing rather than data analysis, the foundational knowledge of Python programming can be a stepping stone for learning data analysis libraries like Pandas and NumPy. The ability to read and understand Python code, acquired through this course, helps a data analyst collaborate more effectively with data engineers. This course may be useful for data analysts looking to expand their skillset.
Marketing Manager
Marketing managers plan and execute marketing campaigns to promote products or services. This course may be useful for marketing managers in the software or technology industries. While not directly related to marketing, understanding Python can provide insights into product development and technical aspects of the business. The ability to read and understand Python code may facilitate better communication with technical teams. This course may help marketing managers who want a deeper understanding of the products they are marketing.

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Technical Writing: Getting Started with Python.
Save
Focuses on the use of if statements in the Scala programming language. It covers the syntax, semantics, and common idioms used in Scala, and provides numerous examples to help readers master the topic. The book is written in a clear and concise style, making it suitable for both beginners and experienced Scala programmers.
Focuses on the use of if statements in the Rust programming language. It covers the syntax, semantics, and common idioms used in Rust, and provides numerous examples to help readers master the topic. The book is written in a clear and concise style, making it suitable for both beginners and experienced Rust programmers.
Focuses on the use of if statements in the Ruby programming language. It covers the syntax, semantics, and common idioms used in Ruby, and provides numerous examples to help readers master the topic. The book is written in a clear and concise style, making it suitable for both beginners and experienced Ruby programmers.
Focuses on the use of if statements in the PHP programming language. It covers the syntax, semantics, and common idioms used in PHP, and provides numerous examples to help readers master the topic. The book is written in a clear and concise style, making it suitable for both beginners and experienced PHP programmers.
Focuses on the use of if statements in the C++ programming language. It covers the syntax, semantics, and common idioms used in C++, and provides numerous examples to help readers master the topic. The book is written in a clear and concise style, making it suitable for both beginners and experienced C++ programmers.
Similar to the previous book, this one focuses on the use of if statements in the Java programming language. It covers the syntax, semantics, and common idioms used in Java, and provides numerous examples to help readers master the topic. The book is written in a clear and concise style, making it suitable for both beginners and experienced Java programmers.
Gathers hundreds of battle-tested recipes covering network programming, memory management, data structures, and functional decorators for veteran application developers.
This widely used textbook that provides a comprehensive foundation in technical communication, covering essential elements from audience analysis to document design. It offers practical advice and real-world examples, making it suitable for beginners and those seeking to refresh their skills. is commonly used in academic settings.
Delivers the canonical blueprint for numeric analysis from the creator of pandas, thoroughly detailing NumPy structures, data cleaning, and high-speed transformations.
Specifically focused on the increasingly important area of API documentation, this book guides technical writers on how to create clear, accurate, and user-friendly documentation for Application Programming Interfaces. It's a valuable resource for technical writers specializing in or looking to specialize in API documentation.
This handbook provides a comprehensive overview of the core tools for data science in Python, including IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. It balances theory with practical examples presented in a Jupyter notebook format, making it highly relevant for users of Anaconda. It's a valuable reference for gaining a solid understanding of the data science stack in Python.
Introduces clean architecture, domain-driven design, and event-driven microservices to Python developers, demonstrating repository patterns and dependency inversion.
Demystifies programming for practical utility, guiding beginners through real-world automation projects including web scraping, spreadsheet generation, and file audits.
Focuses on static typing, structural subtyping, and defensive design techniques, demonstrating how modern type annotations prevent regressions in enterprise codebases.
Serves as a comprehensive reference for technical writers, covering a wide range of topics from grammar and style to document formats and project management. It is an invaluable resource for quick lookups and detailed explanations, making it a useful desk reference for both students and professionals. The Handbook is often recommended as a core text or supplementary material in technical writing programs.
Explores the impact of artificial intelligence on the field of technical writing, discussing how AI tools can be used in the documentation process and the ethical considerations involved. It provides a contemporary perspective on the evolving landscape of technical communication and the role of AI.
Comprehensive guide to software documentation, covering everything from the basics to advanced topics such as information architecture and content management. It is an essential resource for anyone who wants to learn about the best practices for software documentation.
Offers a structured and in-depth approach to programming fundamentals using the C programming language. It covers essential concepts such as data structures, algorithms, and memory management, making it well-suited for both beginners and experienced programmers seeking a deeper understanding of C.
This comprehensive textbook covers the fundamental concepts of algorithms, data structures, and analysis techniques. It provides a deep understanding of how algorithms work and how to design efficient and effective solutions to programming problems. While not specifically focused on programming fundamentals, it is an essential resource for programmers looking to develop a strong foundation in algorithm design and analysis.
Known as 'CLRS', this comprehensive reference for algorithms. Loops are integral to the implementation and analysis of many algorithms, and this book provides a rigorous treatment of their application in various computational problems. It standard textbook for undergraduate and graduate-level algorithms courses and is an essential reference for anyone looking to deepen their understanding of how loops are used in efficient problem-solving.
Provides a comprehensive overview of variables in Python. It covers topics such as data types, scope, and memory management. It valuable resource for students and professionals who want to gain a deeper understanding of variables in Python.
Provides a comprehensive overview of variables in JavaScript. It covers topics such as data types, scope, and memory management. It valuable resource for students and professionals who want to gain a deeper understanding of variables in JavaScript.
Provides a comprehensive overview of variables in Ruby. It covers topics such as data types, scope, and memory management. It valuable resource for students and professionals who want to gain a deeper understanding of variables in Ruby.
Offers insights into the role of technical documentation within a product development team, particularly in agile environments. It emphasizes treating documentation as a product and the importance of collaboration between writers and developers. It's highly relevant for technical writers working in software companies.
A practical guide specifically aimed at developers and engineers who need to create technical documentation. It covers essential aspects of writing effective documentation for a technical audience, including understanding user needs and structuring information. is valuable for those with a technical background looking to improve their writing skills.
Unpacks professional testing methodologies using pytest, explaining fixture management, parameterized tests, coverage tracking, and automated CI test execution.
Provides a practical introduction to machine learning using the scikit-learn library, a key component of the Anaconda distribution for machine learning. It focuses on the practical aspects of building and evaluating machine learning models, making it suitable for those looking to apply these techniques after gaining foundational Python knowledge. It's a good resource for beginners in machine learning with some Python background.
Delves into the complexities of data systems, covering various data models and their underlying principles. It's highly relevant for professionals and graduate students dealing with large-scale data, offering insights into how data types and structures impact system design, reliability, and scalability.
Investigates advanced software craft, detailing packaging distribution, bytecode internals, scaling architectures, and maintainability across large distributed systems.
This handbook provides practical guidelines and best practices for creating high-quality technical documentation that is clear, concise, and user-focused. It's a valuable resource for understanding the principles behind effective information development and is often used as a reference for improving the quality of technical content.
Delves into the principles of topic-based writing, a modular approach to creating technical documentation that is highly relevant in the age of online information. It explains how to structure content so that each topic can stand alone, making it ideal for web-based help systems and knowledge bases.
Provides a comprehensive guide to using the Darwin Information Typing Architecture (DITA), an XML standard for technical documentation that facilitates content reuse and single-sourcing. It covers best practices for writing, editing, and architecting content in DITA, making it essential for those working with or planning to adopt this standard.
Bridges volumetric point cloud analysis with Python, teaching LiDAR processing, spatial meshing, and 3D machine vision using modern scientific computing toolchains.
Authored by the creator of Keras, this book offers a conceptual and practical introduction to deep learning using Python and Keras. It's highly relevant for courses covering neural networks and deep learning. While it delves into advanced topics, the clear explanations and practical examples make it accessible for those with a solid understanding of Python and machine learning fundamentals.
Presents a welcoming, foundational ramp into computational logic and programming, establishing syntax literacy, object modeling, and error handling for total beginners.
Affectionately known as the 'Dragon Book,' this comprehensive text on compiler design. Understanding data types is crucial in compiler construction for type checking and code generation. provides in-depth coverage of how data types are handled within the compilation process, making it essential for graduate students and professionals in programming languages and compilers. (Consider the latest edition).
This guide provides a comprehensive overview of the technical writing profession, covering everything from getting started in the field to advancing one's career. It offers practical advice and insights into the day-to-day realities of being a technical writer. It's a useful resource for those considering a career in technical writing or looking to grow in their role.
Presents the fundamental concepts of computer science in a clear and concise manner. It covers topics such as data structures, algorithms, and software engineering, making it suitable for beginners with no prior programming experience who are looking to gain a broad understanding of computer science.
While not solely focused on basic data types, this book must-read for Java developers. It provides in-depth guidance on best practices for using Java's types, including primitive types, objects, generics, and collections. It's highly relevant for undergraduate and graduate students, as well as working professionals, seeking to deepen their understanding of Java's type system and write robust code.
Provides a comprehensive introduction to deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It is suitable for students with a strong background in mathematics and computer science.
This widely acclaimed book emphasizes clarity, simplicity, and humanity in writing nonfiction. Zinsser's approach is highly relevant to technical writing, which benefits greatly from accessible and engaging prose. It's a valuable resource for technical writers looking to improve their overall writing craft and connect with their readers.
Provides a comprehensive introduction to machine learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning. It is suitable for students with a strong background in mathematics and computer science.
Provides a comprehensive introduction to artificial intelligence, covering topics such as machine learning, natural language processing, and computer vision. It is suitable for students with a strong background in mathematics and computer science.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Technical Writing: Getting Started with Python.
First Steps in Python with Jupyter Notebooks
Most relevant
Dive Deep into Python
Most relevant
Introduction to Open Source Application Development
Most relevant
Python for the Absolute Beginner
Most relevant
Python PCAP: Pass Certified Associate in Python...
Most relevant
Python PCEP: Become Certified Entry-Level Python...
Most relevant
Practical Neural Networks and Deep Learning in Python
Most relevant
Get Started with Python and Django Fundamentals
Most relevant
The Python Bible™ | Everything You Need to Program in...
Most relevant

Udemy Buyer Protection & Guarantee

Verified partner policies & purchase protections

Global Marketplace Leader
Free Trial & Audit

Free Lecture Previews

Free preview video lectures available for all courses; optional 7-day free trial on Personal Plan subscriptions (cancel before trial ends to avoid conversion).

Return & Refund Policy

30-Day Money-Back Guarantee

30-day money-back guarantee on all eligible individual course purchases (provided course content has not been substantially consumed or downloaded). Subscription fees are non-refundable once billed.

Buyer Protections

Verified Academic & Industry Partner

Lifetime access to purchased individual courses and future updates, verifiable certificate of completion, and direct student Q&A forums.

Key Purchase Protections
30-day 100% money-back guarantee on course purchases
Lifetime access on web, mobile, and offline
Certificate of completion included with purchase
Direct instructor Q&A and active student community
OpenCourser Verified Partner Policy details last reviewed: 2026-10-22
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser