This episode  focuses on data types, specifically floating-point and fixed-point arithmetic. It begins by contrasting the limitations of fixed-point numbers in terms of range and accuracy with the advantages of floating-point numbers for representing very large or very small values using a mantissa and exponent. The document then provides detailed instructions and examples for converting floating-point binary numbers to denary and vice versa, including handling negative mantissas and negative exponents through two's complement. Finally, it explains the crucial process of normalisation to maintain precision and outlines the steps for adding and subtracting floating-point numbers by converting them to fixed-point for calculation.