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Freshman highschool level?

First, play games. I don't mean video games, I mean pencil and paper games that you will find in places like Games Magazine. Not so much for the word puzzles, but for the logic puzzles - but when trying to solve them think about the ways you solve them. Also wood logic puzzles and Sudoku puzzles are another type to do - all while thinking about how you go about solving them while solving them.

If you are considering a 4 year university degree at most US colleges, a Computer Science degree is really a specialization of mathematics. Important here is calculus, linear algebra (the calculus of systems of equations), probability & statistics, and discrete mathematics (the calculus of countable integer numbers).

If you are considering "computer science" degree at a 2 year vocational/technical college, this is going to focus more on specific programming skills and not the science behind computation. Here learning to program might be helpful to get ahead of the coursework, but it also might backfire as you have to "relearn" what you thought you knew.

A Software Engineer program is a 4 year degree where you learn an engineering approach to designing software. You have to get a solid understanding of Computer Science during this time, so that is still important - but you will also be learning design patterns, software architecture, and methods of large scale programming. This means you don't need to know a specific programming language, but will need one to implement solutions - however, much of it can be learned without doing any programming and instead using pseudocode.

Computer Engineering is a sub-field of Electrical Engineering, and it often is done in tandem with a Computer Science degree due to the overlap (at least, at the university I attended). Here you focus on the hardware and engineering level of computer components.

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I think it is important to remember that computer science is a science, but not in the traditional experimental type. Instead, it is akin to a mathematical science where you deal with abstract concepts that you conduct thought experiments on and do proofs.

One big area of focus is what happens with how you solve a problem as the problem size gets big. For example, suppose you have a computer directory where you keep all your user created files in it. How do you go about finding a particular file you created? Now ask how you go about finding that file among all the files on your computer and not that directory. That's one step up in the problem size, but let us go further - how do you find it on all the computer devices in your home (cellphones, laptops, desktops, cars, "Internet of Things" ready appliances, and so on)? Step up the problem again, how do you find that file on all the computers in an institution. Keep stepping up until you get to all the computers in the world - how do you go about finding one specific file where you only know the name/size/date of creation "fingerprint" among all the files that exist?

This finding a file issue does matter. You finding a file in a single directory that you created might not be too difficult, especially if you organized them in some way to make searching easier. For example, maybe you have a folder for each letter of the alphabet and all files are sorted by the first letter in them - thus if you are looking for "Computer_Science_Textbook.pdf" you can go straight to the C section, then start searching alphabetically. This solution, however, does not work when you consider a site like YouTube and you search for a video called "Rules for Rulers" - how does that site search through all its files to find you the right one?

Another example would be sorting objects. Suppose you have a bag of 0 or 1 items, they come pre-sorted. Now what do you do to sort a bag of 2 items? 10 items? 100 items? 1000 items? 1000000 items? 1000000000 items? What if you have a 10^100 items to sort? Here is a side-by-side visual comparison of different algorithms on sorting.

So computer science isn't just about coming up with efficient ways to solve problems, but ways to solve problems as they get incomprehensibly big.

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Of course, just like Biology, there are a lot of sub-fields within computer science. Since you will often be dealing with computers, knowing how they work helps. What is a computer and a Turing machine? How do a bunch of 1s and 0s (on/off switches) make a modern operating system? How does an operating system work - storing instructions for computers, being able to have "plug and play" components like drive storage or keyboards, how does it manage memory, and so on? When typing a program and then "compiling" it, what is happening? When executing a program, what does it do? As you get to understand things like the stack and heap, you start to understand more the limit and capabilities of a computer and how to use them in solving problems.

When exploring the field, start thinking about what really interest you. Maybe you are interested in how businesses store vasts amount of data and then use it to make recommendations for customers on products, maybe you are interested in computer vision and how to make a robot "see", maybe you are interested in how files system works on a computer system, or maybe you are interested in how a user interfaces with a computer - there are tons of different sub-fields in computer science.

Most importantly, start doing hard problems. Push yourself on mathematics and problem-solving games, all while thinking about how you think about solving them. Explore how computers work, how the internet works, what happens when problems get very big (and where these problems get bit), what types of things are getting computerized and why, and so on. Doing this will help you identify what areas of computer science might interest you.

Good luck and have fun learning!