RC
This course helped me refresh my mathematics and built a solid foundation for computing

The Essential Mathematics for Computer Science specialisation provides the fundamental toolkit needed to excel in computing, data science, and software engineering. Across five courses, you will progress from core mathematical foundations to advanced topics that underpin modern computer science. You’ll begin with sets, number systems, functions, and relations, move into advanced mathematical methods such as algebra, vectors, combinatorics, and probability, then explore geometry, trigonometry, and calculus for modelling motion and change. The pathway continues with logic and reasoning, where you’ll master propositional and predicate logic, Boolean algebra, and proof strategies, before concluding with algorithms and complexity, analysing efficiency, recursion, and computational limits. By completing this specialisation, you will gain industry-relevant skills in discrete mathematics, logic, algebra, calculus, probability, and algorithmic reasoning. These competencies prepare you to design efficient algorithms, analyse complexity, reason formally, and apply mathematical methods to real computing challenges. Whether your goal is to pursue further study in computer science, strengthen your programming and problem-solving skills, or advance in fields such as data science, artificial intelligence, or systems design, this specialisation ensures you have the rigorous mathematical foundation that employers and universities expect.

RC
This course helped me refresh my mathematics and built a solid foundation for computing
Showing: 2 of 2
This course helped me refresh my mathematics and built a solid foundation for computing
The pedagogical approach of this course is fundamentally flawed, characterized by a persistent lack of structural consistency and terminological clarity. The instructor’s reliance on niche "Bourbakist" abstractions—without providing a necessary glossary or defining the mapping of basic indices (i, j) and set notations (n_A, |A|)—imposes an unnecessary cognitive load that forces students to rely on external AI tools for even basic clarification. This failure to declare variables and bridge logical gaps suggests a lecture style that prioritizes the instructor's self-indulgent theoretical display over actual knowledge transfer, creating a "one-way" experience that lacks any genuine intent to ensure student comprehension. Furthermore, the striking misalignment between these idiosyncratic lectures and the standard "American-style" notation used in assessments constitutes a clear breach of instructional alignment. As tuition-paying students, we expect a professional educational service, not an inaccessible monologue that places learners at a severe disadvantage. Because the instruction is so profoundly incoherent and unpleasant, I have found the lecture videos unbearable and have ceased watching them entirely. I am now in the absurd position of paying tuition fees solely to access the assessments, while relying on YouTube and AI to actually learn the material. This course has been an absolute waste of my money, as the only thing I will gain is a certificate, while the actual education has been entirely self-sourced.