Reproducible Software with Python training course

Highlights

The course offers a practical overview of basic software engineering techniques. These are the topics:

Creating environments and installing packages with conda and friends
Basics of version control with git
Testing basics with pytest
Explore Documentation with sphinx
Creating and deploying Python packages
Example project

Course Details

Managing Environments: Set up and manage Python environments with conda.
Package Installation: Use pip and conda for installing dependencies.
Version Control Basics: Understand the fundamentals of git for version tracking.
Collaboration with GitHub: Learn how to collaborate using GitHub repositories.

Writing Tests with Pytest: Introduction to unit testing and using pytest.
Test Automation: Automate tests and integrate them into your development workflow.
Generating Documentation: Use Sphinx to create professional, readable documentation.
Code Quality Tools: Improve code quality with flake8 and black for linting and formatting.
Creating Python Packages: Learn how to structure and package your Python code for distribution.
Deploying Python Packages: Techniques for deploying your packages on PyPI and other platforms.
Project-Based Learning: Apply skills to an example project, incorporating all course concepts.

Who should attend

This course is designed for participants with Python programming experience who would like to improve their development process.

Participants learn how to applies solid engineering techniques to their daily programming task

Feedback

4.8 out of 5 average

"I wanted to say this has been a really good course. The best one I have done. It's been very insightful and I have learnt a lot. Great solid foundation and goes in depth for OOP." DH, Software Engineer, OO Python, November 2024

Certification

Every delegate will be entitled to a certificate of achievement on completion of the course.

If you are missing your certificate - please use the link below to apply - you can also use this link to sign up for the JBI Training newsletter to receive technology tips directly from our instructors - Analytics, AI, ML, DevOps, Web, Backend and Security.

More about this course

This course is designed for participants with Python programming experience who wish to enhance their development process. Participants will learn how to apply solid engineering practices to their daily programming tasks. It is strongly recommended to attend our Python for Programmers course beforehand, or possess equivalent Python knowledge, to fully benefit from this course.

Many Python users, including scientists and engineers, who programme and develop software, may not have formal training in software engineering. As a result, the software they create often falls short of established standards, which can have a significant impact on reproducibility.

This scenario is quite common: the programme worked fine yesterday, but today the results are different, and it's unclear what caused the change. Additionally, it can be difficult to locate the last working version. A solid understanding and application of fundamental software engineering techniques can greatly improve the reproducibility and reliability of software.

FAQs

JBI Training offers a structured range of Python courses covering every level, from complete beginners through to advanced developers. Available courses include Python for Data Analysts and Quants, Python Introduction, Advanced Python, Python for Financial Traders, Python Machine Learning, AI-Assisted Python, Python Data Wrangling, Clean Code with Python, and Python NLP. All courses are available as instructor-led classroom sessions in London or as live remote online training, with onsite delivery available for corporate teams.

The Python for Data Analysts and Quants course is designed specifically for professionals working with data, including data analysts, financial analysts, quantitative analysts, business intelligence specialists, and data scientists who are new to Python. It covers core Python, data processing with Pandas and NumPy, data visualisation, and applying Python to real-world analytical workflows. No prior Python experience is required.

Yes. All Python courses can be delivered as customised onsite or online programmes for corporate teams. Content can be tailored to match the team's current skill level, industry context, existing tools, and specific objectives — such as automating data workflows, developing internal applications, or integrating Python with AI and machine learning pipelines. JBI has delivered Python training for organisations including the BBC, NHS, RBS, Cisco, and Capita.

Yes. Several Python courses are designed for non-developers or those with limited programming experience, particularly in data and analytics roles. The Python for Data Analysts course requires no prior programming knowledge. Business professionals and analysts can learn Python for automating tasks, processing data from Excel and databases, and creating visualisations — without needing a software development background.

Power BI is a point-and-click business intelligence tool best suited for building interactive dashboards and sharing visual reports quickly. Python is a general-purpose programming language that provides greater flexibility for handling large datasets, automating complex processes, building machine learning models, and performing statistical analysis. Many organisations use both tools together — Power BI for reporting and Python for data preparation, transformation, and modelling.

Yes. JBI offers several Python courses that address AI and machine learning, including Python Machine Learning, Introduction to AI and ML with Python, Data Science and AI/ML with Python, TensorFlow, and AI-Assisted Python — which covers how to use AI coding assistants alongside Python development. These courses are suitable for data scientists and developers who want to build, train, and deploy machine learning models using Python.

Course duration varies by topic and level. Introductory Python courses typically run for three days. Specialist courses such as Python for Financial Traders or Python Machine Learning are generally two to three days. Advanced programmes such as Advanced Python Mastery run for four days. Single-day focused courses are also available, including Pandas Beyond the Basics and AI-Assisted Python. Corporate programmes can be structured flexibly to suit team schedules.

Yes. JBI's Python courses are continuously reviewed and updated to reflect the latest stable Python releases and current best-practice libraries and frameworks. This includes updates to Pandas, NumPy, scikit-learn, TensorFlow, and the latest AI-assisted coding tools. Course content reflects how Python is actively used in professional development, data science, and AI engineering roles today.

This course is designed for participants with Python programming experience who would like to improve their development process.

Public Courses

Customised Courses

Highlights

Course Details

Who should attend

Feedback

4.8 out of 5 average

Certification

More about this course

FAQs

Highlights

Course Details

Who should attend

Feedback

4.8 out of 5 average

Certification

More about this course

FAQs

What Python training courses are available in London and online?

Which Python course is suitable for data analysts?

Can Python training be customised for corporate teams?

Is Python training available for non-developers or business users?

What is the difference between Python and Power BI for data analysis?

Do Python training courses cover AI and machine learning topics?

How long does it take to complete a Python course?

Are Python courses kept up to date with the latest releases and libraries?

Email this page to yourself