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Network Systems and Administration
2,500 words
Automated Container Deployment and Administration in the Cloud
This assessment focuses on the practical application of network systems administration, cloud infrastructure and automation technologies. The assignment requires students to design and implement an automated deployment process for a server running a Docker container on a cloud platform such as AWS, Azure or GCP. The assessment develops practical understanding of infrastructure automation, configuration management, containerisation and continuous integration and continuous deployment (CI/CD). The project requires the integration of at least two automation tools from technologies such as Terraform, AWS CloudFormation, Ansible, Azure DevOps, GitHub and GitHub Actions. The first stage involves provisioning the required cloud infrastructure, including a server instance, networking components and appropriate security configurations. Students must provide Terraform scripts, CloudFormation templates or equivalent infrastructure-as-code configurations together with an architecture diagram showing the deployed resources. The second stage focuses on configuration management. Ansible or an equivalent automation tool is used to configure the server environment, including installing and configuring Docker and ensuring that the required services start automatically. Students must provide the relevant playbooks or configuration scripts and a README explaining the overall automation flow. The assessment then requires students to containerise a sample web application using a Dockerfile and automate the deployment of the resulting Docker container to the provisioned cloud server. A CI/CD pipeline must also be implemented using Azure DevOps or another suitable CI/CD platform. The pipeline should automatically build and deploy the Docker container whenever changes are pushed to a version-control repository such as GitHub. The final stage requires comprehensive technical documentation and reflection on the complete automation process. Students must document the different phases of deployment, explain the rationale for the selected tools, discuss alternative solutions and identify the challenges encountered and how they were addressed. The final report must include a detailed architecture diagram, a GitHub repository containing the required scripts and configurations, and a working link to a demonstration video of the end-to-end deployment. The technical report should be approximately 2,000–2,500 words and include a title page, summary, introduction, main content, conclusions, references and appropriate appendices. The report should use Times New Roman 12-point font with 1.5 line spacing, clear headings, diagrams or flowcharts where appropriate, and Harvard referencing. The assessment is evaluated through the demonstration, report quality and reusable deployment artifacts, with the marking scheme allocating 40% to the demo, 50% to report quality and 10% to artifacts.
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Network Systems and Administration / Cloud Computing / DevOps
2,500 words
Automated Container Deployment and Administration in the Cloud
This practical Network Systems and Administration assessment requires students to design and implement an automated cloud deployment workflow using modern DevOps and infrastructure automation technologies. The overall objective is to deploy a cloud-hosted server running a Docker container while integrating at least two automation tools such as Terraform, AWS CloudFormation, Ansible, Azure DevOps, GitHub Actions or GitHub. Students may use a cloud platform such as AWS, Microsoft Azure or Google Cloud Platform. B9IS121 Network Systems and Adm… The first stage focuses on cloud infrastructure provisioning. Students automate the creation of a server instance, such as an AWS EC2 instance or Azure virtual machine, and configure supporting infrastructure including networking and security groups. Infrastructure must be provisioned through tools such as Terraform, GitHub Actions or AWS CloudFormation. The required outputs include reusable infrastructure scripts or templates and an architecture diagram showing the deployed cloud resources. B9IS121 Network Systems and Adm… The second stage addresses configuration management. Students use Ansible or an equivalent automation platform to configure the provisioned server, install Docker and ensure Docker starts automatically when the server boots. Deliverables include Ansible playbooks or equivalent configuration scripts together with a README file explaining the automation workflow. B9IS121 Network Systems and Adm… The third stage requires students to containerise and deploy a web application. A Dockerfile must be created for either an existing or newly developed sample application, and deployment of the resulting container must be automated on the provisioned server. The required artefacts include the Dockerfile, deployment scripts and application repository. B9IS121 Network Systems and Adm… Students must also create a CI/CD pipeline using Azure DevOps or another suitable CI/CD platform. The pipeline should automatically build and deploy the Docker container whenever new code is pushed to a version-control repository such as GitHub. Students must provide the relevant pipeline configuration, normally in YAML, and demonstrate the pipeline operating successfully. B9IS121 Network Systems and Adm… Documentation is an important part of the assessment. Each student produces an independent PDF report explaining every stage of the automation process, challenges encountered and how those challenges were resolved. A 10-minute walkthrough video must demonstrate the complete end-to-end deployment, and the report must contain a detailed architecture diagram. B9IS121 Network Systems and Adm… The technical report should include a title page, summary, introduction, main technical content, conclusion, references and appropriate appendices. Students are expected to justify the tools selected and critically discuss alternative solutions, advantages and limitations. The report is expected to contain approximately 2,000–2,500 words and should use clear headings, diagrams or flowcharts where relevant, and academic or professional sources such as journal articles, whitepapers, DevOps documentation and industry reports. B9IS121 Network Systems and Adm… B9IS121 Network Systems and Adm… The marking scheme allocates 40% to the demonstration, 50% to report quality and 10% to technical artefacts. Higher-performing submissions are expected to show a working deployment, clear justification of technical actions, strong understanding of automation tools, professional report structure, consistent referencing and reusable scripts that reproduce the same deployment results. B9IS121 Network Systems and Adm… The final submission includes a comprehensive PDF report of approximately 5–8 pages, a detailed README, and links to the relevant scripts, configurations and deployment evidence. B9IS121 Network Systems and Adm…
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Data Science / Time Series Analysis / Machine Learning
Time Series Modelling Case Study: Oil Price Forecasting with ARMA and Alternative Models
This Time Series Modelling Case Study requires students to analyse real-world oil-price time-series data and develop forecasting models capable of predicting future values. The assessment combines traditional statistical time-series techniques with an alternative forecasting approach, requiring students to demonstrate practical modelling skills, critical research engagement and evidence-based interpretation of forecasting results. The coursework is completed individually and contributes 40% of the assessment. assing,,, (1) The assessment is divided into three main parts. Part 1 focuses on developing an ARMA-based forecasting model using daily oil-price data covering approximately 2024 to 2026. Students begin with exploratory data analysis and initial visualisation before testing whether the time series is stationary. Where necessary, appropriate transformations or differencing must be applied to obtain stationarity. Students then define an ARMA model and identify suitable p, d and q parameters using an AIC-based model-selection procedure across the parameter ranges specified in the brief. assing,,, (1) Model adequacy must be assessed using diagnostic analysis. Students inspect residuals, generate additional ACF plots, examine residual distributions and evaluate prediction performance using appropriate metrics such as RMSE. The selected model is then used to forecast oil prices 24 months into the future, with appropriate confidence intervals added to communicate forecast uncertainty. assing,,, (1) Part 2 requires students to research and implement an alternative forecasting approach. Suggested examples include LSTM and Prophet, although another appropriate model may be proposed. Students conduct a literature review supporting the alternative method, build and where relevant hyperparameter-tune the model, generate another 24-month forecast, visualise predictions and confidence intervals, and calculate suitable evaluation metrics. This component is intended to demonstrate independent research and the ability to propose an alternative solution rather than relying only on the conventional ARMA approach. assing,,, (1) Part 3 consists of a 6–8 page technical report explaining the modelling process, forecasting results and resulting inferences. The report should provide a critical analysis rather than simply reproducing numerical outputs. Students are expected to explain why results occurred, justify modelling choices, evaluate how those choices influenced performance, compare forecasts with subsequently observed real data where possible, and construct a coherent narrative supported by plots, images, summary statistics and academic literature. Future improvements to the modelling approach should also be critically discussed. assing,,, (1) Submission consists of both the report and working code. The code may be submitted directly or through an accessible Colab or GitHub repository and must reproduce all models, figures and numerical results presented in the report. The assessment allocates 60% of the marks to code and 40% to the report. Within the coding component, modelling and forecasting completion accounts for 40 marks and code quality and annotation for 20 marks. The report is assessed on analysis and inference, methodological justification, comparison of the two modelling approaches, presentation quality, figures and use of appropriate references. assing,,, (1) Key technical expectations include appropriate testing for stationarity, use of methods such as ADF, ACF, PACF and differencing, systematic model selection, forecasting, evaluation and clear comparison between the traditional ARMA model and the chosen alternative approach. Higher-quality work is expected to interpret what the forecasts mean, identify potential improvements and demonstrate sound technical communication rather than merely reporting model outputs. assing,,, (1) Important for the public Reference Library: the brief explicitly states that students must not use generative AI to write the report, and the rubric indicates that AI text-generation use may result in zero marks for the whole assignment. Therefore, the public entry should remain a high-level description of the assessment rather than material intended for direct submission. assing,,, (1)
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Web Applications / Artificial Intelligence / Software Development
Smart Clinic Appointment and Patient Management System with AI-Based Demand Prediction
This Web Applications and AI coursework requires students to design, implement and evaluate a Smart Clinic Appointment & Patient Management System for a small healthcare clinic. The application combines conventional web-development functionality with an artificial-intelligence component for predicting appointment demand. The system is expected to use Java EE technologies, including Java Servlets, JSP, Web Services and JDBC, together with a relational database such as MySQL or PostgreSQL. f3855340dabd17407efd386c38cfdc3… The patient-facing side of the application should allow users to browse and search clinic services by department or specialty, price, availability and duration. Patients must be able to view detailed service information, select a clinician where appropriate, choose an available date and time, enter their details and confirm an appointment. The system should also provide a booking reference and basic appointment-history functionality. f3855340dabd17407efd386c38cfdc3… The administrative interface focuses on operational management. Staff should be able to add, update and remove services, configure consultation duration and pricing, manage clinician working hours and appointment-slot availability, and generate basic reports. f3855340dabd17407efd386c38cfdc3… A separate machine-learning component requires students to implement appointment-demand prediction using WEKA regression embedded in Java. The provided sample dataset contains Year, Month, Promotions Cost and Booking Requests. Students must expand this dataset to at least 60 realistic rows, including seasonal changes and plausible variation in marketing expenditure and demand. A regression model is then trained to predict booking requests for the following year based on promotional spending, including estimation of future demand if promotions expenditure increases by 10%. f3855340dabd17407efd386c38cfdc3… The assessment also requires evidence of professional software-development practice. Students must provide application-design artefacts such as design patterns, ER diagrams, wireframes and sketches, document the development process, demonstrate correct use of JSP, Servlets, Web Services and JDBC, and provide evidence of implementation through code, database content and screenshots. Regular GitHub commits are required to demonstrate ongoing development. f3855340dabd17407efd386c38cfdc3… f3855340dabd17407efd386c38cfdc3… The final submission includes a DOCX or PDF report containing system-design and implementation information, links to a private GitHub repository and a demonstration video of no more than five minutes. The assessment is classified as Green for AI use, meaning AI tools may support tasks such as generating example datasets, suggesting code snippets and brainstorming features or tests, provided their use is clearly declared in the report. f3855340dabd17407efd386c38cfdc3… Overall, the coursework integrates full-stack Java web development, relational database design, web services, software engineering and machine-learning regression within a healthcare appointment-management scenario. Important: the uploaded brief states that it is for Coventry University Group students' own use and must not be passed to third parties or posted publicly. f3855340dabd17407efd386c38cfdc3… So for a public Reference Library, use an original summary like the one above rather than publishing the original brief itself.
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Computer Networks / Network Security / Cloud and Software Defined Networking
3,500 words
Network Systems and Security: Ad Hoc, Cloud and Software Defined Networking Emulation
This Network Systems and Security coursework requires students to design, implement and critically evaluate a series of practical network-emulation environments covering wireless Ad Hoc networking, cloud services and Software Defined Networking (SDN). The project combines Python-based network configuration with practical connectivity testing, cloud deployment, controller-based networking and theoretical evaluation of contemporary network-security technologies. The first task involves designing an Ad Hoc wireless network representing an emergency-response scenario. Students configure at least three wireless stations using Mininet-WiFi, assign appropriate network parameters and demonstrate connectivity through ICMP communication. The task requires discussion of the design and implementation together with the Python script used to configure the emulated environment. 7COM1076+ref+def+CW+2025+26+ The second task focuses on cloud-service emulation. Students develop a simple static website, deploy it through Render.com and GitHub, and access the hosted service from a Mininet-emulated network. Required evidence includes the Python implementation, cloud configuration screenshots, commands used to provide internet connectivity, webpage access through an xterm environment and the associated HTML code. 7COM1076+ref+def+CW+2025+26+ The third practical component examines Software Defined Networking using the ONOS controller. Students construct an emulated topology containing hosts, servers and programmable switches, demonstrate complete ICMP connectivity and perform a TCP transmission lasting 600 seconds. Evidence must include the network-emulation script, ONOS graphical interface and connectivity results. 7COM1076+ref+def+CW+2025+26+ The final analytical section critically evaluates whether Software Defined Networking and Network Functions Virtualisation (NFV) complement one another and examines security algorithms used within cloud computing. Students compare two selected cryptographic approaches, evaluating their respective advantages and disadvantages. 7COM1076+ref+def+CW+2025+26+ Overall, the coursework integrates network modelling, wireless networking, cloud deployment, SDN control, Python scripting, connectivity testing and security analysis. The marking scheme gives substantial weight to system modelling, cloud and SDN implementation, ICMP/TCP functionality, technical analysis and overall report quality. 7COM1076+ref+def+CW+2025+26+
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7COM1076
4,000 words
7COM1076 Network Design, Modelling and Evaluation Coursework
This 7COM1076 coursework requires students to design, model, emulate, test and evaluate networking environments for a new department building at the University of Hertfordshire. The assessment combines practical network modelling with theoretical analysis and evaluation, covering wireless and mobile networking, cloud networking, Software Defined Networking (SDN), network applications and contemporary networking technologies. The assignment is designed to develop practical knowledge through Python-based network emulation and critical understanding through academic research. Task 1 focuses on wireless and mobile networking. Students must use Python to emulate a building containing three WiFi access points and two user stations, identified as UE1 and UE2. The access points are connected using a physical linear topology, while the stations use Class C private IP addresses. The task requires configuration of SSIDs, passwords, channels, ranges and coordinates, with WPA2 encryption and standalone fail mode. The stations must also be configured with mobility, following specified movement sequences and speed ranges. Students must discuss the design and implementation, complete the configuration and mobility tables, provide the Python script used with the Mininet API, and include screenshots demonstrating mobility, access-point association and successful ping connectivity. Task 2 examines cloud services using Mininet and Render.com. Students must emulate a network containing three switches and two hosts and deploy a simple static website using Render.com. Host H1 must access the deployed webpage through the xterm environment. Deliverables include a discussion of the design and implementation, the Python script, evidence of configuring Render.com with the GitHub repository, commands used to connect H1 to the internet and access the webpage, screenshots of the webpage through xterm, and the HTML code of the website. Task 3 focuses on Software Defined Networking and connectivity. Students must emulate an environment containing ten hosts and three servers using a linear topology, with an ONOS controller enabled for control-plane programmability. The task requires configuration of assigned IP and MAC addresses, demonstration of connectivity between hosts and servers, and a UDP transmission using a duration of 600 seconds and bandwidth of 100 Mbps. Students must provide a design discussion, Python emulation script, ONOS GUI screenshot, full ping connectivity evidence and the required UDP transmission results. Task 4 is the analysis and evaluation component. Students must critically discuss three contemporary networking issues using academic sources. These include the challenges faced by a small-to-medium organisation providing services to the UK National Health Service when migrating from on-premises infrastructure to cloud computing; the opportunities and challenges of incorporating Software Defined Networking into future optical networks; and whether WiFi and 5G should coexist to provide ubiquitous services to users. The final report must use 12-point font, normal margins and Harvard referencing in accordance with University of Hertfordshire guidelines. The required report length is 4,000 words with a permitted variation of plus or minus 10%, excluding the title page, contents page, references and appendix, with a maximum page limit of 25 pages. The recommended structure includes an introduction, discussions and results for Tasks 1–3, the three Task 4 analysis sections, conclusion, references and an appendix containing the Task 1, Task 2 and Task 3 code. The assessment covers wireless and mobile networking, cloud and SDN networking, network applications, analysis and evaluation, MCQ tests and overall report quality. The marking allocation includes WiFi networking, mobility and ICMP, cloud configuration, SDN networking, cloud web page, UDP, three analysis sections, two MCQ tests and quality of the report.
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Secure Design and Development
2,000 words
Secure Design and Development – PixelForge Nexus (UITS)
This assessment for Coventry University’s Secure Design and Development module requires students to design and develop a functional secure online system with the aid of a Large Language Model (LLM). The assignment is based on a practical scenario involving Creative SkillZ LLC and its proposed “PixelForge Nexus” system. The submission combines a functional prototype, an individual 2,000-word report, source code hosted in the Coventry University GitHub environment, and a video report demonstrating the completed prototype. The PixelForge Nexus prototype is intended to provide secure project management and basic asset and resource management for a game-development environment. Core functionality includes adding and removing projects, viewing active projects, assigning developers to projects, allowing developers to view their assigned projects, uploading project documents, and allowing authorised users to access documents associated with their projects. The system must implement privilege separation between Admin, Project Lead and Developer roles. Security is a central requirement of the assignment. Administrators are responsible for managing projects and user accounts, Project Leads can assign developers and upload project documents, while Developers can view assigned projects and associated documents. The system must include a robust login mechanism with secure password hashing and storage, with Multi-Factor Authentication recommended as an additional security measure. Proposed pages include Sign In/Register, a role-based User Dashboard, Account Settings and a Project Details page. The practical assessment evaluates four major areas: System Design, Security Testing and Analysis, System Development, and Formal Methods. System design requires consideration of secure design principles and their application to the development lifecycle. Security testing requires critical evaluation of security techniques, identification of issues and proposed mitigation measures. System development requires a functional prototype that follows the proposed design and considers legal and ethical requirements. Formal methods require a behavioural model and appropriate verification techniques to establish whether the system meets its specification. The individual report must document the methods and techniques used to develop the prototype and discuss the stages of the development lifecycle, including specification, design and development. It must also explain the deployment and testing approach, limitations of the prototype, possible improvements, security techniques and the formal model used. The submission must include links to the Coventry University GitHub repository and Microsoft OneDrive video, while the required appendix contains the LLM prompt history and other resources used with APA-style referencing.
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Computer Networks and Network Engineering
3,500 words
Wireless, Cloud and Software Defined Networking: Network Modelling, Emulation and Evaluation
This technical networking assignment focuses on the design, implementation, emulation and evaluation of wireless, cloud and Software Defined Networking environments. It combines practical network modelling with analytical discussion and requires students to demonstrate their understanding of modern networking architectures through Mininet-WiFi, Mininet, cloud deployment technologies and an ONOS Software Defined Networking controller. The first task involves creating an ad-hoc wireless network for an emergency-response scenario. A minimum of three wireless stations must be configured using specified parameters such as transmission range, antenna height, antenna gain, SSID and wireless capabilities. Students are required to explain the network design and implementation, provide the Python configuration script used with Mininet-WiFi, and demonstrate connectivity using ICMP communication between appropriate stations. The second task examines cloud-service emulation. Students must construct a Mininet topology containing a switch and two hosts and deploy a simple static website using Render.com. The task requires evidence of cloud configuration, GitHub repository integration, commands used to provide internet access to the emulated host, webpage access through Xterm, screenshots of the resulting webpage and the associated HTML code. The third task addresses Software Defined Networking (SDN). Students create an emulated environment involving three hosts and three servers, implement the required network topology and use the ONOS controller to provide control-plane programmability. Evidence must include the Python emulation script, ONOS GUI output, host-to-server connectivity testing and TCP transmission testing. The final analytical component requires students to critically evaluate the relationship between Software Defined Networking and Network Functions Virtualisation (NFV) and assess security algorithms used in cloud computing, including a comparison of the advantages and disadvantages of two selected algorithms. The coursework therefore integrates practical network configuration, connectivity testing, cloud deployment, programmable networking and academically referenced technical evaluation. Overview word count: approximately 335 words. Important: the brief explicitly states that AI-generated report or code content is prohibited, so this Reference Library description should be treated only as catalogue/metadata content, not as coursework material for submission.
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