To help you feel prepared for your university studies, we’ve gathered together a range of course related activities including suggested reading, useful websites and some great things to do right now. Open the links below to find out more:
When you begin studying, you’ll be given lots of information describing which textbooks to read for your modules. You’ll also be introduced to the University Library. The library will provide you with free access to many eBooks, as well as physical books too.
In the meantime, there are a couple of books you might like to read. We don’t recommend rushing out to buy these before you arrive, and it’s completely up to you which books you read (if any!).You may be able to access them for free online or perhaps you’ll find them in a local public library. You may even be able to pick them up second hand from bookshops.
Books that will help boost your programming skills
Downey, A. B., 2015, Think Python: How to Think Like a Computer Scientist, Green Tea Press, Open-Source Edition. Available FREE. Hardcopy also published by O’Reilly, ISBN-13: 978-1491939369.
Books that will help build your overall computing and data science knowledge
- Forouzan, B., 2017, Foundations of Computer Science, Cengage Learning EMEA. ISBN-978-1473751040. Accessible via EHU library.
- Parsons, J. J. & Oja, D., Introductory computer concepts 2016: new perspectives, 2016, Boston, MA, Parsons. ISBN-13: 978-1305387751. Available in EHU library.
- VanderPlas, J., Python Data Science Handbook: Essential Tools for Working with Data, O’Reilly, Available FREE. Hardcopy also published by O’Reilly, ISBN-13: 978-1491912058.
- Warford, J. S., 2016, Computer Systems, Jones and Bartlett Publishers, Inc. ISBN-13: 978-1284079630. Available in EHU library.
Books that will enlighten and inspire
- Altraide, D., 2019, New Thinking: From Einstein to Artificial Intelligence, the Science and Technology That Transformed Our World, Mango Media.
- Christian, B. & Griffiths, T., 2016, Algorithms to Live By: The Computer Science of Human Decisions, William Collins.
- Fry, H., 2018, Hello World: How to be Human in the Age of the Machine, Transworld Digital.
- Mueller, J. P. & Massaron, L., 2021, Machine Learning for Dummies, For Dummies. ISBN-13: 978-1119724018.
Whilst at Edge Hill, you’ll have access to all the facilities and equipment you need to complete your studies (we have excellent computer labs). Yet we realise that some students prefer to use their own equipment. There are some peripheral devices you may like to obtain:
- Portable Hard Disk Drive – Whilst you can store files online (in places such as Dropbox) we advise that you purchase a portable disk drive. A 500GB shock proof USB 3.0 self-powered hard disk drive (approx. £50 in 2022) will be sufficient and is invaluable for backing up your work.
- Portable USB stick – As an alternative to a portable hard disk drive, you could obtain a 32GB USB 3.0 stick (approx. £6 in 2022), or a 64GB drive (approx. £10 in 2022).
For those who prefer the independence of using their own computer to complete work outside of our departmental labs, we advise using a computer that meets or exceeds the following specification:
|CPU||Intel i5 or processor (or AMD equivalent).|
|DISK||750 GB free.|
|OS||Microsoft Windows 9, MacOS 10.15, or a Linux distribution that supports Gnome, KDE, or Unity DE.|
If you do not possess a computer that meets these minimum specifications, you may be able to borrow a laptop from our department.
Programming skills are essential for computer scientists. To ensure everyone has the opportunity to develop these skills, we’ll tackle the Python programming language in semester one.
If you are new to coding, we understand that learning to program can sometimes feel overwhelming. Newcomers often have lots of questions, e.g., “What tools do I need?” or “How do I setup a programming environment?”. Thankfully help is available. There is an online tool that provides a ready-made Python coding environment that you can use for free – this is called Google Collaboratory. Using the “Colab” you can write and execute Python code in your web-browser (Google Chrome). There are even tutorials available online that will help you understand how the Colab works.
There are other useful resources relevant to your studies. For example, why not:
- Keep up to date with KD Nuggets, a site that reports on developments in A.I. / data science and provides useful links to training / free resources.
- Follow updates in the tech industry via sites such as Tech Crunch, The Register, MIT News, Science Daily or WIRED.
- Explore the current tech job market on IT Jobs Watch and join the developer community on DZone.
- Get familiar with StackOverflow, the go to site for programmers to seek help and ask technical questions.
Start learning more about A.I. and data science. There are some great resources online that can help you master the subject. There are excellent introductory videos available on YouTube, such as StatQuest.
Things to do over summer
Here are a few ideas for you to try before you begin your studies:
- For those who’ve never programmed – start to learn a programming language. We recommend starting with Python, which you can begin to learn via Code Academy or Solo Learn. You can also brush up your web development skills using sites such as w3schools.com or css-tricks.com.
- For those already comfortable with the Python basics, this is a great time to develop your skills and stretch yourself. Websites like Code Wars and Edabit provide coding challenges that will help you become better programmers. The more coding you do now, the better!
- If coding challenges don’t really interest you, then why not start a small project? It can be fun to Develop your own application ideas and explore the tech used to create them. Succeed or fail, you’ll learn a lot. The hard part is finding an idea that interests you. Maybe something like a password generator, your own interactive website, a game like connect four or minesweeper etc. There are lots of project suggestions online, so search for a beginner’s project that suits you.
- If you want to get ahead with A.I. & data science, why not tackle some real-world problems via Kaggle. Here you’ll be able to take part in competitions, gain access to learning resources and see first-hand how more experienced researchers solve problems.
- Computer science isn’t all programming. There’s a great deal of reading and writing too. It’s therefore useful to hone your reading and writing skills before, during and after your studies – something which students often overlook. It will be particularly useful if you can spend a little time learning how to use the Harvard referencing approach correctly.
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