Top 6 Hardest Subjects in Computer Science

Is computer science a difficult course? Well, most people think so. Being a technical course, it is obvious that most people expect to encounter some difficulties when studying it. However, most people believe that generally, computer science is not that hard. There are a few topics that are very simple to grasp. However, there are other topics that seem to be quite hard.

Hardest Subjects in Computer Science

Instead of generalizing the whole course, let’s look at some of the hardest topics or subjects in Computer science.

1. Artificial Intelligence

Artificial Intelligence (AI) tops the list of the most difficult subjects in Computer Science. It focuses on teaching students how to program intelligent machines. These are simple machines that are programmed to think and act like real human beings. The intelligent machine should have particular traits that are needed for solving problems. These traits include the ability to learn, reason, perceive and accept changes depending on various circumstances.

So, why is AI a difficult topic in computer science? The first reason is it requires a cross-disciplinary approach. You need to combine different disciplines of computer science in order to understand and implement the theories of AI. Some of these disciplines include programming, mathematics, psychology, linguistics, and even database management. Combining all these disciplines into one product is not a walk in the park.

Another reason why this subject is difficult is the evolving nature of AI technology. AI is not a static field. It keeps changing as technology advances with time. The concepts that worked a few years ago may not be applied now. This means that AI students are always subjected to new concepts every time.

Otherwise, AI is one of the most lucrative fields in computer science. There is no doubt that AI experts are in very high demand.

2. Theory of Computation

As a computer science student, you don’t just need to use your computer to solve problems. You need to have an in-depth understanding of how the computer is able to come to a particular solution. The theory of computation is a topic in computer science that elaborates how problems can be solved using a particular algorithm and model of computation.

Basically, the theory of computation is divided into three distinct branches. These are computability theory, automata theory, and complexity theory. All these branches will equip you with the knowledge of how to explore the limitations and capabilities of a computer.

Theory of computation covers the mathematical abstraction of computers which is also known as the model of computation. Here students cover several models including the most common one which is known as the Turing machine.

Apart from just analyzing how a problem can be solved, the theory of computation also teaches a student to analyze whether the methods and algorithms used will solve the existing problems effectively. This means that computer scientists have to look at several other aspects including the memory space required and the time that will be taken to come up with the solution.

3. Microprocessors

Another computer science topic that is deemed difficult is the microprocessor. Microprocessors are also known as logic chips and are the engines of computers. A typical microprocessor contains all the central processing unit functions. It performs both the arithmetic and logic functions of a computer.

Sounds easier, right? As a computer science student, you will go beyond defining what a microprocessor is. You will learn how it works and even how to design one. Since microprocessors form an integral part of any computing system, a computer science student must be open to receiving lots of information about these devices.

The topic of the microprocessor is quite wide and very technical. First, you will need to learn about logical operations and mathematical computations. As if this is not enough you will immerse yourself in some fundamentals of electronics. This is because microprocessors consist of thousands of electronic components such as transistors and integrated circuits. You will also learn about different designs of microprocessors and how each design solves a particular problem.

This topic will equip you with the relevant knowledge and skills that you will use to be a microprocessor designer.

4. Advanced Database Systems

Perhaps you are aware of the basics of a database. Obviously, you didn’t have a hard time understanding the fundamentals of a database. However, advanced database systems is a bit difficult computer science topic. Although it may also cover the fundamentals of a database system, it goes deeper to cover advanced and sophisticated database concepts.

While the fundamentals of database systems are applied in conventional business applications, advanced database systems go beyond ordinary business use. They are used to manage data in complex applications, especially in emerging technologies. Despite covering the most sophisticated concepts, the topic also covers the basics of database systems.

5. Compiler Design

Compiler design is also ranked among the hardest topics in computer science. First things first, a compiler is a program that converts a program written in a high language into machine language. This topic provides in-depth information about the whole translation and optimization process.

Computer science students learn the mechanisms of translation and error detection during the compilation process. They also learn lexical and syntax analysis during the code generation process. The topic is deemed difficult as it requires one to be good at coding. You need to have a good grasp of various programming languages.

6. Image Processing and Computer Vision

Image processing and computer vision are two topics that are closely related. Image processing entails giving a computer the power to add some extra transformations into an image. The computer will make the image more attractive or appealing. On the other hand, computer vision analyzes images and various real-world data in order to produce more appealing symbolic information.

These two topics are quite difficult. They require a student to be fully committed and dedicated. However, we must agree that they have a wide range of applications, especially in the modern world. It is also an evolving topic as learners have to keep learning about emerging technologies.

In conclusion, the above are the most perceived difficult topics in computer science. However, with a positive attitude and determination, you will be able to conquer them.