Training that fits your needs
At Arborian, we recognize that each training need is unique. We customize each training delivery to match exactly the pace, content, and hands-on labs for your students. Our instructors are also practitioners, so our courses focus on information that students can immediately put into use.
Course catalog
These are the standard courses we offer for on-site and virtual instructor-led training. All courses include a significant lab component, and students will have several hours of hands-on experience by the end of the course.
Purpose
Learn the basics of the Python programming language
Objectives
- Learn to install and configure Python
- Create basic Python scripts
- Perform text processing in Python
- Create a modular Python application
Purpose
Help new Python programmers expand their Python skills
Objectives
- Understand and apply Python's iteration protocols
- Apply test-driven design (TDD) concepts to Python application development
- Use multithreading and multiprocessing to scale out Python programs
- Build a simple web application using Flask
Purpose
Learn the basics of the Python programming language
Objectives
- Use metaclasses and descriptors to customize Python class creation
- Use Python's asyncio module to build explicitly asynchronous programs
- Packaging Python libraries and applications for distribution
Purpose
Learn to use Python to automate system administration tasks
Objectives
- Use Python for processing and generating text files
- Build Python command-line applications
- Build a web API and UI using Flask and Python
- Create a Python module for use with Ansible
Purpose
Learn how to use Ansible to automate remote system administration
Objectives
- Use Ansible to execute ad hoc tasks on remote servers
- Use Ansible playbooks to configure infrastructure in repeatable ways
- Create and use Ansible roles for code reuse
Purpose
Put data science and machine learning to work with Python
Objectives
- Learn to use Python the data science stack
- Familiarization with several machine learning algorithms
- Evaluation of machine learning models
- Productionalization of machine learning tools