Hainadine Chamane - ePortfolio

This ePortfolio showcases the outcomes of my M.Sc. in Computer Science studies at the University of Essex in the UK.

See the complete content in my e-Portfolio of the subjects below.

Induction Module

• Module aims
• Learning Outcomes
• First Assignment
• Reflections on my learning experience

Module 1: Launching into Computer Science (LCS)*

• Unit 1: Computing as a Profession – Responsibilities and Challenges
• Unit 2: Introduction to Computer Architecture and the Functionality
• Unit 3: Emerging Trends in Computer Science
• Unit 4: Computing Infrastructure and Network
• Unit 5: Software as a Tool – Its Functionality and Development Methodologies
• Unit 6: System Software – Operating Systems
• Unit 7: Data Abstraction
• Unit 8: An Introduction to Algorithms and Basic Programming Concepts
• Unit 9: Solving Problems Using Python
• Unit 10: Data Representation using Database Concepts
• Unit 11: Advanced SQL
• Unit 12: Research Topics in Computer Science – Data Science, AI, and Standards

Module 2: Object-oriented Programming

• Unit 1: An Introduction to Python Programming and the OO Programming Paradigm
• Unit 2: Object Oriented Analysis - Initial Steps towards Programming in Python
• Unit 3: UML
• Unit 4: Applying a UML Model to a Program Implementation: UML in Practice
• Unit 5: More on Classes
• Unit 6: Abstract Methods and Interfaces
• Unit 7: Debugging / Error Handling, Data Structures and Data Search
• Unit 8: Data Structures and Data Search in Practice
• Unit 9: Packaging and Testing
• Unit 10: Testing Code in Practice
• Unit 11: Pointers, References & Memory, and Design Patterns
• Unit 12: Working with Design Patterns to Structure Code

Module 3: Secure Software Development

• Unit 1: Introduction to Secure Software Development
• Unit 2: UML Modelling to Support Secure System Planning
• Unit 3: Programming Languages: History, Concepts & Design
• Unit 4: Exploring Programming Language Concepts
• Unit 5: An Introduction to Testing
• Unit 6: Using Linters to Support Python Testing
• Unit 7: Introduction to Operating Systems
• Unit 8: Cryptography and Its Use in Operating Systems
• Unit 9: Developing an API for a Distributed Environment
• Unit 10: From Distributed Computing to Microarchitectures
• Unit 11: Future Trends in Secure Software Development
• Unit 12: The Great Tanenbaum-Torvalds Debate Revisited

Module 4: Network Security

• Unit 1: History of Network Security, Vulnerabilities and Approaches
• Unit 2: Advanced Persistent Threats: Applying the Cyber Kill Chain Model to a Case Study
• Unit 3: Vulnerability Assessments
• Unit 4: Breach Analysis and Mitigation
• Unit 5: Logging, Forensics and Future Trends
• Unit 6: The Great Debate: The Future of the Internet

Module 5: Information Security Management

• Unit 1: An Introduction to Security and Risk Management
• Unit 2: Threat Modelling Exercises
• Unit 3: Introduction to Threat Modelling and Management
• Unit 4: Security Standards, Frameworks and Disaster Recovery
• Unit 5: Future Trends in Security and Risk Management
• Unit 6: The Great Debate - What Will be the Most Influential Trend in ISM in the Next 5 Years?

Module 6: Software Engineering Project Management

• Unit 1: Introduction to Software Engineering Project Management
• Unit 2: Study: Why Projects Fail and Gathering Requirements Exercise
• Unit 3: Estimating, Planning and Risk
• Unit 4: Estimating Tools and Risk Assessment
• Unit 5: User Experience
• Unit 6: pytest and Test-Driven Development
• Unit 7: Software Development Life Cycles
• Unit 8: Python Data Structures
• Unit 9: Quality Management Strategy
• Unit 10: Software Quality Monitoring in Python
• Unit 11: Software Engineering Project Management: Future Trends
• Unit 12: The Case for the Future Direction of Software Engineering Project Management

Module 7: Research Methods and Professional Practice

• Unit 1: Introduction to Research Methods. The Scientific Investigation and Ethics in Computing
• Unit 2: Research Questions, the Literature Review and the Research Proposal
• Unit 3: Methodology and Research Methods
• Unit 4: Case Studies, Focus Groups and Observations
• Unit 5: Interviews, Survey Methods, and Questionnaire Design
• Unit 6: Quantitative Methods - Descriptive and Inferential Statistics
• Unit 7: Inferential Statistics and Hypothesis Testing
• Unit 8: Data Analysis and Visualisation
• Unit 9: Validity and Generalisability in Research
• Unit 10: Research Writing
• Unit 11: Going Forward: Professional Development and Your e-Portfolio
• Unit 12: Project Management and Managing Risk

*= Core Module