GCSE Maths Revision - Ratio, Proportion and Rates of Change
Comprehensive revision of ratio, proportion, and rates of change for GCSE maths, covering key topics and exam board requirements in a concise format.
GCSE Maths Revision - Algebra
Comprehensive algebra revision covering key topics with practice questions. Ideal for GCSE exam preparation, featuring clear explanations and step-by-step problem-solving techniques.
GCSE Maths Revision - Number
Comprehensive revision of GCSE Maths Number topics, covering fractions, decimals, indices, standard form, prime numbers, factors, multiples, percentages, and more for exam preparation.
GCSE Maths Grade 7, 8 and 9 Booster Revision Questions
Comprehensive revision series with 50 challenging questions covering advanced GCSE maths topics. Ideal for students aiming for top grades, with explanations and additional resources available.
Random Variables
Explore continuous random variables, probability density functions, and the normal distribution. Learn to calculate expected values, variances, and use statistical tables for data analysis.
Inverse Trigonometric Functions
Comprehensive exploration of inverse trigonometric functions, covering definitions, graphs, derivatives, integrals, and applications. Ideal for advanced math students seeking in-depth understanding.
Basic Algebraic Techniques
Comprehensive guide to fundamental algebraic concepts, covering expansion, simplification, substitution, and factorization, with practical examples and applications.
Binomial Theorem
Explore proofs and applications of the Binomial Theorem, from basic algebra to probability. Discover connections to Pascal's Triangle and learn to solve complex polynomial problems.
Circle Geometry
Comprehensive exploration of circle geometry, covering key theorems, properties, and problem-solving techniques for angles, chords, tangents, and cyclic quadrilaterals.
Bivariate Data Analysis
Explore scatter plots, correlation coefficients, and lines of best fit to analyze relationships between two variables in this comprehensive introduction to bivariate data analysis.
Basic Single Variable Analysis
Explore misleading graphs, means, medians, and statistical measures through engaging problems and visual representations.
Basic Ratios & Rates
Learn to simplify, divide, and solve problems with ratios and rates, building foundational skills for more advanced mathematical concepts.
Learn Statistics with Python
Master Python for statistical analysis: design matrices, linear models, F distribution, and OLS. Hands-on tutorials using Orange and Patsy libraries for practical data science skills.
Learning Medical Statistics with Python and Jupyter Notebooks
Learn medical statistics using Python and Jupyter notebooks. Covers common tests, data analysis, and visualization techniques. Ideal for healthcare professionals seeking practical skills in statistical analysis.
Healthcare Statistics with SPSS
Learn to analyze healthcare data using SPSS, covering data creation, import, visualization, descriptive statistics, file manipulation, and parametric testing.
Machine Learning
Explore machine learning models through hands-on tutorials in Python and Julia, covering clustering, regression, neural networks, and more. Practical examples with code provided.
Modern Linear Algebra Using Python Instead of a Textbook
Explore linear algebra concepts through hands-on Python programming, covering matrix operations, decompositions, and applications in machine learning and data analysis.
Julia
Learn Julia programming for data analysis, statistics, and linear algebra. Covers databases, plotting, environments, and advanced mathematical concepts with practical tutorials.
R Tutorials
Learn essential R skills for data analysis, visualization, and machine learning, covering statistics, deep learning, Plotly, and real-world applications like COVID-19 data extraction.
Introduction to Deep Learning for Everyone
Learn deep learning fundamentals using Keras and TensorFlow in R, covering regression, neural networks, regularization, and convolutional networks for practical applications.
Binary Logistic Regression
Learn to perform and interpret binary logistic regression, including multivariate analysis and interactions, through a series of three concise video tutorials.