Launch into Computing
This page is my e-portfolio evidence for Launch into Computing, part of the MSc Artificial Intelligence with the University of Essex (delivered through University of Essex Online). The overview and outcomes below follow the module handbook; my own artefacts, reflection, and meeting notes follow further down.
Module aims and learning outcomes
The following is my own summary of what Launch into Computing aims for me to learn, and what I am expected to be able to do when I complete the module — drawn from the official module handbook and kept here for my e-portfolio.
Module aims
- Building a broad introduction to Computing across Software Engineering, Artificial Intelligence, Data Science, and Cyber Security.
- Developing my grasp of the basic principles, processes, and procedures of software design and implementation methodologies.
- Learning how functional and non-functional requirements map onto Cyber Security processes and procedures.
- Strengthening my understanding of the technologies and principles that underpin Artificial Intelligence in practice.
- Forming a clearer appreciation of current and future challenges, limitations, and opportunities in the field.
- Practising how to present critical arguments for specific actions or outcomes to a diverse audience.
- Exploring how computing concepts and devices can help overcome barriers to equality, diversity, and inclusion.
- Using this module to reflect on and evaluate my own academic and professional development.
Learning outcomes
- Identify and critically analyse computing challenges and processes in business systems, accounting for the current enterprise landscape.
- Gather and synthesise information from multiple sources (including internet resources and business publications) to support the systematic design and analysis of computing challenges.
- Critically evaluate appropriate methodologies, tools, and techniques to mitigate or solve computing issues and their business impact.
- Articulate the legal, social, ethical, and professional issues that computing professionals encounter in practice.
Artefacts
| Unit | Description | Peer feedback |
|---|---|---|
| Unit 1 |
How do different computing disciplines (AI, cybersecurity, software engineering) contribute to AI-powered assistants? by Eziuche Emmanuel - Wednesday, 29 April 2026, 12:32 PM An AI Assistant is like a stack of several computing disciplines working together where the software engineering contributes provides the scalability and architecture, data science focuses on data curation cleaning and validation, Cybersecurity protects the system from attacks. In that stack, AI as a discipline acts as the brain that interpretes, reasons and decides. |
by Ben - Saturday, 2 May 2026, 5:37 PM I agree with your main point that AI-powered assistants are not created by AI alone, but I would describe them as an interdependent system rather than a stack. A stack can suggest fixed layers, while AI assistants require constant interaction between disciplines. Software engineering supports deployment and integration, data science helps evaluate accuracy and bias, and cybersecurity protects against risks such as data leakage or prompt-based attacks. AI may provide the reasoning capability, but the assistant becomes useful and trustworthy only when these disciplines work together throughout its design, deployment and monitoring. |