Description
This microcredential provides a comprehensive introduction to the essential tools and techniques required for modern computational data analysis. The program combines classroom and self-study learning to build foundational skills in Linux, Python, version control with Git, cybersecurity, and high-performance computing (HPC).
Participants gain hands-on experience with essential computational tools and methods and develop practical skills.
Whether you are beginning to integrate computational tools into your workflow or seek to expand your knowledge, this microcredential offers a structured pathway to becoming proficient in key areas of data analytics.
Prerequisites
Basic math and intermediate experience with computers, including working with documents and spreadsheets.
Details
Learning Objectives
Synchronous courses:
Linux and the Command Line
- Navigate a file system via the command line
- Create and edit text files
- Integrate wildcards to sort output
- Redirect command output to files
- Combine commands using pipes
Programming in Python
- Write and execute code in Python
- Interact with Python using the command line
- Run Python in both interactive and scripting modes
- Execute Python code inside Jupyter Lab
- Write and execute Python code in different environments, including Integrated Development Environments (IDEs)
- Define variables in Python
- Slice strings into substrings
- Explain differences between lists and tuples in Python
- Demonstrate the use of dictionaries
- Explain the use of “for” loops
- Write programs that use “if” and “else” statements, and simple Boolean expressions
- Write a function that uses a fixed number of arguments and produces results
Version Control
- Describe the importance of Git for version control in collaborative projects
- Configure Git and manage the workflow of additional changes to track version control
- Establish and configure remote Git repositories on platforms like GitHub for effective project management
- Execute commands to push local changes to a remote repository or pull changes from a remote source
- Work collaboratively on a repository, identifying and resolving conflicts that arise when multiple contributors make changes to the same codebase
High Performance Computing (HPC)
- Describe and demonstrate what distinguishes HPC from conventional computing
- Communicate with remote computers and migrate data
- Write and execute a basic Slurm submission script
- Submit and monitor computing jobs with Slurm
- Maintain a consistent software environment within jobs
Asynchronous courses:
Computers and Overview of Programming Languages
- Identify the main components of a computer and describe how a computer works
- Explain the differences between operating systems, modern tools and platforms
- Describe the advantages and disadvantages of various types of programming languages and decide which one best suits a project’s requirements
Cybersecurity
- Summarize the different types of cyber threats and how they can occur
- Adopt incremental changes to improve personal cybersecurity
- Implement data storage best practices on HPC clusters
- Secure logins to remote computers with SSH keys
Who Should Enrol
Designed for professionals, researchers, and students who seek to build a strong technical foundation for data analytics. This course serves as a stepping stone for those who aim to develop their data analytics capabilities and apply them in more advanced computing environments.