Books represent gateways to new worlds, allowing us to gain valuable knowledge on virtually any topic. Those interested in exploring computer science books face two challenges. First, just like you can’t build a good house without a proper foundation, you can’t expand your knowledge if you don’t understand basic concepts. Secondly, technology is always evolving, so besides understanding how things work, you need to stay current with the latest trends.


Finding books that help you build a good foundation and follow innovations isn’t easy. Fortunately, you don’t have to go through hundreds of titles to find the good ones. Here, we’ll introduce you to the best BSc Computer Science books that will set you up for success.


Top BSc Computer Science Books


These BSc Computer Science books can “program” your mind and help you absorb knowledge.


Introduction to Computer Science


Many people are eager to learn how to program and immerse themselves in the IT world. But the first step toward that is adopting fundamentals. Before jumping into the IT industry, you need to learn more about computer science and the basic concepts behind it.


Computer Science Illuminated by Nell Dale and John Lewis


This student-friendly book sheds light on computer science. It explores operating systems, hardware, software, and networks from “neutral ground” (without focusing on particular programming languages). Therefore, if you don’t “speak” programming languages just yet, this book will be your best friend.


Intro to Python for Computer Science and Data Science: Learning to Program With AI, Big Data, and the Cloud by Paul Deitel and Harvey Deitel


If you want to be a programming expert, you may need to speak Python, a universal language with a wide array of applications. This book teaches you how to use Python in computer science and offers the perfect balance between theoretical and practical knowledge. It transforms complex information into comprehensive and engaging data.


Data Structures and Algorithms


Finding the best BSc Computer Science book on data structures and algorithms can feel like trying to find a needle in a haystack. We found the needle for you and offer the best options.


Data Structures and Algorithms Made Easy by Narasimha Karumanchi


This book is a winner in the data structures and algorithms game. It’s the perfect option for beginners interested in learning the topic from scratch and building a solid foundation for more advanced levels. It covers basic concepts and moves on to more complex stuff without overwhelming the readers.


Data Structures and Algorithms in Java by Robert Lafore


If you’re familiar with Java and want to start with data structures and algorithms, this book is the gold standard. It will guide you on a journey from basic Arrays and Strings to advanced structures like Hash-Tables and Graphs.



Computer Networks


Computer networks are grids through which computing devices “talk to” each other and share data. Here are the books you can use to improve your knowledge and get ahead in your career.


Computer Networks by Andrew S. Tanenbaum


If you want to understand the nitty-gritty behind computer networks, this book is the way to go. Hop on a journey through email, the world wide web, video conferencing, and much more, to understand how the networks work and how to use them to your advantage.


Every chapter follows the same, easy-to-follow structure containing basic principles and real-life examples.


Computer Networking: A Top-Down Approach by James F. Kurose and Keith W. Ross


This beginner-friendly book takes a somewhat unusual approach. It first introduces students to applications and uses them to explain fundamental concepts. That way, students are exposed to the “real world” early on and can understand how networking works with ease.

 

Operating Systems


An operating system for a computer is like oxygen for a human; it can’t live without it. Operating systems are interfaces that support everything computers do. Here are the best books about them.


Operating Systems: Three Easy Pieces by Remzi Arpaci-Dusseau and Andrea Arpaci-Dusseau


How do operating systems work? What are the three basic concepts hiding behind every OS? Find the answers to these questions and learn everything OS-related in this book. While beginner-friendly, this amazing study can be combined with more advanced materials and offer a deeper understanding of modern OSs.


Guide to Operating Systems by Greg Tomsho


This book represents a detailed guide on installing, updating, maintaining, and configuring operating systems and everything related to them. Besides offering general info, the book explores specific OSs and allows you to peek into this world without feeling overwhelmed.


Database Systems


Database systems are like virtual warehouses where you can keep your data secure. They’re the ones we can “thank” for easy information retrieval, browsing, and organization. If you want to learn the ins and outs of database systems, these books can help.


Database Systems: The Complete Book by Hector Garcia-Molina, Jeffrey D. Ullman, and Jennifer Widom


This book is the holy grail for many computer science students. It offers a comprehensive approach and detailed explanations of everything related to database system design, use, and implementation. The book is extensive, but it’s written in an engaging way, so reading through it is a breeze.


Database Systems: Design, Implementation, & Management by Carlos Colonel and Steven Morris


Building your virtual warehouses for storing data may seem impossible. But it can become your reality thanks to this excellent book. It contains clear and comprehensive instructions on building database systems, offers concrete examples, but also focuses on the bigger picture and latest industry trends.


Software Engineering


Designing and constructing software is no walk in the park. If you’re interested in this industry, you need to build your skills meticulously. Books that can help you on this exciting (and sometimes frustrating) journey are reviewed below.


Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin


In this book, Robert C. Martin, a software engineering legend, discusses the seemingly insignificant differences between bad and poorly-written codes. He explains which “symptoms” bad codes manifest and how to clean them.


Code Complete: A Practical Handbook of Software Construction by Steve McConnell


One of the first (and smartest) steps toward building quality code is getting this book. Here, the author summarized everything there is to know about constructing software. Since the book contains both the basics and the more advanced construction practices, everyone finds it useful, both beginners and pros.


Additional Resources for BSc Computer Science Students


BSc Computer Science books aren’t the only spring you should drink water from if you’re thirsty for knowledge on the subject.


Online Platforms and Courses


Online platforms and courses are great resources for those who want to expand their knowledge and learn how to cash it in. The internet is overflowing with great courses focusing on various aspects of computer science. Here are a few ideas to get you started:

  • Open Institute of Technology (OPIT) – The institute offers a comprehensive online BSc in Computer Science. Throughout the program, students get acquainted with everything computer science-related. After completing their studies, they’ll be able to land high-paying jobs.
  • Udemy and Coursera – Although not “official” institutes and universities, these platforms deserve a seat at the table. Both Udemy and Coursera offer quality computer science courses held by some of the most respected names in the industry.

Coding Practice Websites


You’ve read books, attended courses, and feel like you know everything there is to know about the theoretical part. But is there a way to put this theory into practice and see whether your codes work? The answer is yes! Practice makes perfect, and coding practice websites will become your best friends and help you conquer programming.

  • Coderbyte – Solve real-life coding issues and drive your skills to perfection. With over a dozen available programming languages, you can try out as many ideas as you’d like.
  • HackerRank – HackerRank is home to hundreds of coding challenges. Plus, it has leaderboards, so you can see how you compare to other coders. It’s also home to useful tutorials, and since the website is popular, you may even be able to land your dream job.

Computer Science Forums and Communities


Is there a better place for like-minded people to meet and discuss the topics they’re passionate about? Computer science forums and communities should be an important stop on your way to becoming an expert on the subject.


Tips for Success in BSc Computer Science


Success doesn’t happen overnight (at least for most people). If computer science is your true passion, here’s how to master it:

  • Focus on the basics to create a good foundation.
  • Put your thinking cap on and practice problem-solving and critical thinking skills.
  • Participate in group projects and collaborations (teamwork makes the dream work).
  • Keep up with the latest industry trends.
  • Gain valuable hands-on experience through internships.

Acquire Computer Science Knowledge Effectively


Although books don’t offer practical knowledge, they can be invaluable allies in setting a great theoretical foundation. By carefully choosing the best books and putting effort into developing your skills, you’ll become a pro in a jiff.

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CCN: Australia Tightens Crypto Oversight as Exchanges Expand, Testing Industry’s Appetite for Regulation
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Mar 31, 2025 3 min read

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  • CCN, published on March 29th, 2025

By Kurt Robson

Over the past few months, Australia’s crypto industry has undergone a rapid transformation following the government’s proposal to establish a stricter set of digital asset regulations.

A series of recent enforcement measures and exchange launches highlight the growing maturation of Australia’s crypto landscape.

Experts remain divided on how the new rules will impact the country’s burgeoning digital asset industry.

New Crypto Regulation

On March 21, the Treasury Department said that crypto exchanges and custody services will now be classified under similar rules as other financial services in the country.

“Our legislative reforms will extend existing financial services laws to key digital asset platforms, but not to all of the digital asset ecosystem,” the Treasury said in a statement.

The rules impose similar regulations as other financial services in the country, such as obtaining a financial license, meeting minimum capital requirements, and safeguarding customer assets.

The proposal comes as Australian Prime Minister Anthony Albanese’s center-left Labor government prepares for a federal election on May 17.

Australia’s opposition party, led by Peter Dutton, has also vowed to make crypto regulation a top priority of the government’s agenda if it wins.

Australia’s Crypto Growth

Triple-A data shows that 9.6% of Australians already own digital assets, with some experts believing new rules will push further adoption.

Europe’s largest crypto exchange, WhiteBIT, announced it was entering the Australian market on Wednesday, March 26.

The company said that Australia was “an attractive landscape for crypto businesses” despite its complexity.

In March, Australia’s Swyftx announced it was acquiring New Zealand’s largest cryptocurrency exchange for an undisclosed sum.

According to the parties, the merger will create the second-largest platform in Australia by trading volume.

“Australia’s new regulatory framework is akin to rolling out the welcome mat for cryptocurrency exchanges,” Alexander Jader, professor of Digital Business at the Open Institute of Technology, told CCN.

“The clarity provided by these regulations is set to attract a wave of new entrants,” he added.

Jader said regulatory clarity was “the lifeblood of innovation.” He added that the new laws can expect an uptick “in both local and international exchanges looking to establish a foothold in the market.”

However, Zoe Wyatt, partner and head of Web3 and Disruptive Technology at Andersen LLP, believes that while the new rules will benefit more extensive exchanges looking for more precise guidelines, they will not “suddenly turn Australia into a global crypto hub.”

“The Web3 community is still largely looking to the U.S. in anticipation of a more crypto-friendly stance from the Trump administration,” Wyatt added.

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Agenda Digitale: Generative AI in the Enterprise – A Guide to Conscious and Strategic Use
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Mar 31, 2025 6 min read

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By Zorina Alliata, Professor of Responsible Artificial Intelligence e Digital Business & Innovation at OPIT – Open Institute of Technology

Integrating generative AI into your business means innovating, but also managing risks. Here’s how to choose the right approach to get value

The adoption of generative AI in the enterprise is growing rapidly, bringing innovation to decision-making, creativity and operations. However, to fully exploit its potential, it is essential to define clear objectives and adopt strategies that balance benefits and risks.

Over the course of my career, I have been fortunate to experience firsthand some major technological revolutions – from the internet boom to the “renaissance” of artificial intelligence a decade ago with machine learning.

However, I have never seen such a rapid rate of adoption as the one we are experiencing now, thanks to generative AI. Although this type of AI is not yet perfect and presents significant risks – such as so-called “hallucinations” or the possibility of generating toxic content – ​​it fills a real need, both for people and for companies, generating a concrete impact on communication, creativity and decision-making processes.

Defining the Goals of Generative AI in the Enterprise

When we talk about AI, we must first ask ourselves what problems we really want to solve. As a teacher and consultant, I have always supported the importance of starting from the specific context of a company and its concrete objectives, without inventing solutions that are as “smart” as they are useless.

AI is a formidable tool to support different processes: from decision-making to optimizing operations or developing more accurate predictive analyses. But to have a significant impact on the business, you need to choose carefully which task to entrust it with, making sure that the solution also respects the security and privacy needs of your customers .

Understanding Generative AI to Adopt It Effectively

A widespread risk, in fact, is that of being guided by enthusiasm and deploying sophisticated technology where it is not really needed. For example, designing a system of reviews and recommendations for films requires a certain level of attention and consumer protection, but it is very different from an X-ray reading service to diagnose the presence of a tumor. In the second case, there is a huge ethical and medical risk at stake: it is necessary to adapt the design, control measures and governance of the AI ​​to the sensitivity of the context in which it will be used.

The fact that generative AI is spreading so rapidly is a sign of its potential and, at the same time, a call for caution. This technology manages to amaze anyone who tries it: it drafts documents in a few seconds, summarizes or explains complex concepts, manages the processing of extremely complex data. It turns into a trusted assistant that, on the one hand, saves hours of work and, on the other, fosters creativity with unexpected suggestions or solutions.

Yet, it should not be forgotten that these systems can generate “hallucinated” content (i.e., completely incorrect), or show bias or linguistic toxicity where the starting data is not sufficient or adequately “clean”. Furthermore, working with AI models at scale is not at all trivial: many start-ups and entrepreneurs initially try a successful idea, but struggle to implement it on an infrastructure capable of supporting real workloads, with adequate governance measures and risk management strategies. It is crucial to adopt consolidated best practices, structure competent teams, define a solid operating model and a continuous maintenance plan for the system.

The Role of Generative AI in Supporting Business Decisions

One aspect that I find particularly interesting is the support that AI offers to business decisions. Algorithms can analyze a huge amount of data, simulating multiple scenarios and identifying patterns that are elusive to the human eye. This allows to mitigate biases and distortions – typical of exclusively human decision-making processes – and to predict risks and opportunities with greater objectivity.

At the same time, I believe that human intuition must remain key: data and numerical projections offer a starting point, but context, ethics and sensitivity towards collaborators and society remain elements of human relevance. The right balance between algorithmic analysis and strategic vision is the cornerstone of a responsible adoption of AI.

Industries Where Generative AI Is Transforming Business

As a professor of Responsible Artificial Intelligence and Digital Business & Innovation, I often see how some sectors are adopting AI extremely quickly. Many industries are already transforming rapidly. The financial sector, for example, has always been a pioneer in adopting new technologies: risk analysis, fraud prevention, algorithmic trading, and complex document management are areas where generative AI is proving to be very effective.

Healthcare and life sciences are taking advantage of AI advances in drug discovery, advanced diagnostics, and the analysis of large amounts of clinical data. Sectors such as retail, logistics, and education are also adopting AI to improve their processes and offer more personalized experiences. In light of this, I would say that no industry will be completely excluded from the changes: even “humanistic” professions, such as those related to medical care or psychological counseling, will be able to benefit from it as support, without AI completely replacing the relational and care component.

Integrating Generative AI into the Enterprise: Best Practices and Risk Management

A growing trend is the creation of specialized AI services AI-as-a-Service. These are based on large language models but are tailored to specific functionalities (writing, code checking, multimedia content production, research support, etc.). I personally use various AI-as-a-Service tools every day, deriving benefits from them for both teaching and research. I find this model particularly advantageous for small and medium-sized businesses, which can thus adopt AI solutions without having to invest heavily in infrastructure and specialized talent that are difficult to find.

Of course, adopting AI technologies requires companies to adopt a well-structured risk management strategy, covering key areas such as data protection, fairness and lack of bias in algorithms, transparency towards customers, protection of workers, definition of clear responsibilities regarding automated decisions and, last but not least, attention to environmental impact. Each AI model, especially if trained on huge amounts of data, can require significant energy consumption.

Furthermore, when we talk about generative AI and conversational models , we add concerns about possible inappropriate or harmful responses (so-called “hallucinations”), which must be managed by implementing filters, quality control and continuous monitoring processes. In other words, although AI can have disruptive and positive effects, the ultimate responsibility remains with humans and the companies that use it.

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