London South Bank University (LSBU)

Personal Finance is an option module for students studying Accounting and Finance. This document covers: income, state benefits in the UK, sources of income, 'informal' economy, minimum wage, payslip, income tax, National Insurance, where do taxes come from, where do taxes go, tax year, income tax rates, National Insurance Contributions, employment income, benefits in kind, dividends income, self-employment, graduate considerations, income level by occupation, public sector versus private sect...

This is an option module for students studying Accounting and Finance. This document covers: the power of budgeting, the theories behind our spending decisions, different types of budgeting systems, how to prepare a budget, different types of consumer behaviours, what is budgeting, purpose of budgeting, why people budget, why people don't budget, budgeting building process, managing household finances.

This document contains the lecture notes to the first lecture class for the module Personal Finance. The first session covers on how students are going to be assessed and an overview of what the learning objectives and learning outcomes are for this module. It also covers the advantages of personal financial planning. This is an option module for students studying Accounting and Finance.

This thesis explores the possibilities of emotional detection on social media. A practical goal of analyzing emotions detected on Twitter over Brexit in 2019 using "senti strength" on python.

This document is very short but exploring how data plays a part in identifying counter-terrorism. Specifically exploring Link analysis and how it has been used in the past. This is simply a review paper with lots of sources and references that would be good to use for further reading.

This document is an introduction to data pipelines if anything, mostly focusing on Luigi and apache airflow with their similarities and differences. Please only buy this document if you are trying to learn either Luigi or Apache airflow. Or perhaps in a situation where you need to learn about the two.

This document shows a step-by-step guide to exploring data using python libraries pandas and seaborn. Finding the most popular times an uber has been ordered in New York City and the popular locations.

This document is a step-by-step guide on creating a decision tree model using R to analyze the statistics of the iris flower dataset.

The review paper goes over cloud security, behind the scenes of how it works and the threats against it. This is a good paper to read for absolute beginners in cyber security especially in cloud computing.

This just shows mathematical formulas for some boosting, bagging, and tree ensemble methods in machine learning. Including explanation and diagrams