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Exploring the difference - IT and Computer Science !

Published by: CCA Publications

A special thanks to Ellen Loh for making this article possible.

Thinking of pursuing a degree in tech but unsure of whether to choose a CS (Computer Science) or IT (Information Technology) degree? 

Technology has become an integral part of society allowing us to communicate and interact with the world around us, encouraging more individuals to pursue a degree within this field. However, deciding between the two degrees can be difficult and confusing. Understanding the differences will enable you to choose the degree best suited to your interests!

Monash offers both degrees as a 3-year undergraduate course and can be further combined with a double degree. 

Application vs Theory 

A Bachelor of Information Technology (IT) offers a broad overview of a range of IT topics with its main focus on the practical applications of technology. It deals with the maintenance and management of computer systems, networks and databases. Students studying this degree often gain an understanding of how to administrate the application such as improving security measures, managing big data, using IT solutions to make business recommendations or even creating games. 

On the other hand, a Bachelor of Computer Science (CS) provides more in-depth knowledge that focuses on the theoretical and mathematical foundations of computing. Students studying this degree work towards designing algorithms and data structures and use their acquired programming skills to solve computing problems. 


Learning and Skills 

During the course of your studies, you will be equipped with core units - which form the basic fundamentals of your degree. Both degrees require students to take four compulsory core units: FIT1045 - Intro to programming, FIT1047 - Introduction to computer systems, networks and security, FIT1049 - IT professional practice, and FIT2094- Databases.

Nonetheless, the other units are unique to each degree, allowing you to develop skills specific to that degree. For example, the depth of learning varies. After the Intro to programming unit (FIT1045), the Bachelor of Computer Science will go into more detail with algorithms and programming in subsequent compulsory units like FIT1008 - Fundamentals in algorithms and FIT2004 - Algorithms and data structures, whereas FIT1045 is the minimum level of depth required by an IT student which covers the basics of programming.

The skills you gain during your studies will also differ but are highly valuable for career progression. Both degrees will expose you to some form of programming language, the common two being Python and Java. 

CS students will be equipped with skills such as: 

  • Data analysis and database tools

  • Experience in coding platforms 

  • Mathematics and statistics 

IT students will be equipped with skills such as: 

  • Troubleshooting methods 

  • Security infrastructure

  • Network configuration 

  • Project management

  • Customer Service  

IT majors vs CS specialisations

As you advance through the course of your degree, you will then have to choose a main area of focus. At Monash, undergraduate courses are organised into either comprehensive or specialist degrees.

Bachelor of IT is a comprehensive course meaning that you will be exposed to a broad range of subjects within the field before choosing a particular field of interest.

As a result, Bachelor of IT offers 4 majors and 8 minors:

  • Business information systems: working with business and technical professionals to analyse problems, identify data patterns,  trends and create new IT processes

  • Cybersecurity: design computer systems, networks and applications that protect from cyber attacks and improve overall security 

  • Games and immersive media: engage with a range of technologies such as VR and AR, design and develop games 

  • Software development: analyse and understand business requirements and develop software applications that assist in maximising business operations 

  • Minors: 3D modelling and animation, Games Design, Games development, Mobile App development, Web development, Software Engineering, Computer Science and Data Science

Bachelor of CS has only two specialisation streams as it is classified as a specialist course and is recommended for those that already know they want to pursue this degree. This means that you will begin studying in your area of interest and further progress to either one of the specialisations offered:  

  • Advanced computer science: explore a range of programming paradigms, analyse and construct advanced algorithms and data structures 

  • Data science: collating, interpreting, analysing big data and presenting it in a way that allows businesses to understand 

Both degrees are versatile. Even if you decide to study a Bachelor of IT, there are options to minor in Computer Science or Data Science. Depending on your interests, this enables you to explore units offered in Bachelor of CS as secondary specialisations to your main degree.


Career Pathways 

There’s a common misconception that CS degrees are better (or more highly recognised) than IT degrees! Is this true? - Absolutely not!

It is important to understand that no degree is better than the other and pursuing one degree does not necessarily limit you to a career only within that area. Ultimately, it comes down to the skills you obtain during the course of your studies. As mentioned previously, the skills obtained differ between the two degrees. Therefore, whichever degree you end up choosing, the potential career pathways are endless. 

Bachelor of IT graduates often pursue areas involving business and technical skills such as network administration, database administration, data analytics, cybersecurity, IT consulting, IT project management, business analytics, web development and software development. 

Bachelor of CS graduates are tailored towards roles that require more advanced technical and theoretical knowledge skills. This includes computer science, data science, software development, software engineering and AI or machine learning engineering.