Hardest Comp Sci Classes to Master

Computer science classes can be a real challenge, but some stand out as particularly tough.

Algorithms is one of the hardest comp sci classes to master, with its focus on developing efficient solutions to complex problems.

Data structures is another difficult class, requiring students to understand how to organize and manipulate large amounts of data.

Computer systems is also a demanding course, where students learn about the inner workings of computers and how to design and implement efficient systems.

These classes are not just about memorizing formulas and code, but about developing problem-solving skills and critical thinking.

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Comp Sci classes can be brutal, but some stand out as particularly challenging.

Data Structures and Algorithms is notorious for its complexity and abstract thinking, with courses that often involve solving problems on a whiteboard with no computers.

Theory of Computation is another tough one, requiring students to grasp the fundamental limits of computation and the power of different computational models.

Computer Systems is all about understanding how computers work, from hardware to software, and it can be overwhelming to learn about CPU architecture, memory management, and networking fundamentals.

Algorithms is a class where students learn to analyze and design algorithms, which can be a real brain-twister, especially when dealing with NP-hard problems.

Compilers and Interpreters is a class that delves into the world of programming languages, requiring students to understand parsing, syntax analysis, and code generation.

Additional reading: What Is the Hardest Code Language to Learn

Theoretical Foundations are the backbone of Computer Science, providing a solid understanding of the subject. This branch of study lays the groundwork for more advanced classes, ensuring that students have a firm grasp of the underlying principles.

Computer Science is built on mathematical foundations, with courses like Discrete Math and Linear Algebra being essential for understanding complex algorithms and data structures. These classes are notorious for being challenging, but they're also crucial for a deep understanding of Computer Science.

Theoretical Foundations also involve the study of computability theory, which explores the limits of what can be computed. This includes understanding the concept of the halting problem, which states that there cannot exist an algorithm that can determine whether any given program will run forever or eventually halt.

Courses like Automata Theory and Formal Languages provide a deeper understanding of how computers process information and the limitations of computation. These classes are often considered some of the hardest in Computer Science, but they're also incredibly rewarding for those who persevere.

Theoretical Foundations are not just about math and algorithms; they also involve the study of logic and reasoning. Courses like Propositional and Predicate Logic provide a solid understanding of how to reason about complex systems, which is essential for advanced Computer Science topics.

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Computer Science 61A, for example, amplifies college calculus and expands into new difficulties, requiring a thorough understanding of calculus to "manage program complexity."

This course is no joke, and it's a major roadblock for computer science majors, who need to take it to complete their degree.

Calculus is a major part of the course, which makes sense given that it's one of the hardest majors at Berkeley, with four major courses ranking among the top 10 hardest.

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CompSci 70 — Discrete Math is a notoriously hard class for many computer science majors. It's often considered one of the most challenging classes they'll take.

The class is called Discrete Mathematics and Probability Theory, but as one student noted, "Nothing really discrete about this one." This is because the class focuses on problem-solving and proof-writing, which can be frustrating without immediate feedback.

Learning to apply logical thinking used in coding problems to problems on paper is a major hurdle for many students. As UC Berkeley student Joshua Baum said, "The most difficult part of CS70 for me was learning to apply the logical thinking used in coding problems to problems on paper."

Math 54 — Linear Algebra and Differential Equations is notorious for its challenging nature.

The class is a "weeder" version of linear algebra, meaning many students start but few finish.

Exam averages in the 50-60% range are considered normal, and getting a C is a realistic expectation.

Standard deviations become crucial in this class, as they can make or break your grade.

If you're a Berkeley student who's never earned a B before, getting a C in Math 54 might be a hard pill to swallow.

The class is so feared that even math, engineering, and CS majors cringe at the mention of it.

In Computer Science 61C, you'll dive into memory management and operating systems, expanding your knowledge beyond math and code.

This class is often considered the easiest of the CS61 trinity, but don't be fooled - it still contends for a top spot on many graduates' lists of their hardest courses ever taken.

You'll feel proud knowing you've made it this far and will likely complete the last required class with a sense of accomplishment.

Computer science majors must complete all required classes with an average GPA of 3.0 or higher to apply for the CS major, a feat in itself.