what to do once i learn to code
What to do after "Learning how to Code" ?
When I start learned virtually computers, I learned FORTRAN programming. It was the programming linguistic communication that dominated the scene back in, and before, the early 70s. In today's globe, we have numerous efforts that go by monikers such as "code." We are told, "learning how to code" is skilful for your career, and it is fun. While I favor the phrase "programming" because "code" is a bit too narrow (think of Morse code or the ENIGMA code), programming is not without its double meanings. When Boob tube producers talk nearly programming, they are referring to listings and scheduling. Coding or programming? Either will do.
The issue I have with coding is that it really does not represent true figurer science. Consider chemistry or physics lab. In such a lab, y'all explore the science. In chemical science lab, in that location are Bunsen burners, sources for gas and water, lots of differently shaped glass containers, and rubber tubing. When you engage in chemistry lab, you are doing practical chemistry but you lot are not learning the essence of chemistry: how atoms are defined, how reactions occur. This is how you tin can view coding. Coding is like going to chemistry lab. You learn applied modes of doing informatics. But, if you desire to learn real reckoner scientific discipline, you must await elsewhere.
This is where "theory" comes into play. Informatics at its most fundamental conception is a theory of information. How is data stored, retrieved, and structured? How does data flow? This theory goes well beyond computers. You may have heard that a food recipe is similar an algorithm. That is true. An algorithm is a type of menstruum of control that can explain everything from how y'all open and close a door to the flowcharts defining how society regulates industry. Hither are some example theoretical concepts:
Set Theory & Logic — representing knowledge nearly something. Logic is often taught by starting with the Greeks and Aristotle's syllogism. From syllogism, nosotros progress to propositional logic. "Fred eats potatoes and Mary drinks soda" in propositional logic would be coded as P ^ Q with P="Fred eats potatoes" and Q="Mary drinks soda". From at that place, we can add inference and we can also grouping terms together. Predicate (First order) logic takes things to the next level. Set up theory is our way of organizing the world. A lot of diagrams are rooted in logic. For instance, you may know of concept maps, semantic networks, or heed maps. Essentially, these are diagrammatic representations of logic.
Automata — Alan Turing offered the thought that "a machine" could be virtual. In doing and then, reckoner scientists over the by seventy years accept created classes of machines. A uncomplicated one called a "Finite State Machine" defines a machine that can remember just i land at a time. For example, if "brawl is going upwardly" is State Ane and "ball going down" is State Two, then we know from gravity and friction, that eventually, State One will transition to State Two. Find how this line of reasoning has zip intrinsically to do with reckoner software or hardware; the state machine is not bars to technology. The state is considered an attribute of the ball object. One can teach physics with such observations.
Linguistic communication — nosotros normally understand language by writing and speaking one. For example, I write and speak English language. Noam Chomsky in the late 50s created classes of languages, from simple to complicated and more expressive. These languages turn out to be correlated with automata. A key conceptual part of learning languages is to acquire programming linguistic communication concepts. For example, the thought of object oriented (OO) design is a design concept that applies to numerous programming languages. What is more vital? Learning Python or learning the principles of languages? You oftentimes need to know one or ii languages before wading into the sea of concepts, simply it is in the concepts you tin can connect to worlds exterior of the computer: think — apply object oriented design to Alice in Wonderland (i of the projects I had in last semester'south modeling form). OO is conceptual, and thus, mathematical. OO has multiple representations and realizations.
At this betoken, yous might wonder "Why is theory such a big bargain?" It seems like coding is much simpler and approachable than theory. That depends entirely on how it is taught. It is possible to convey all theoretical concepts in everyday linguistic communication, spaces, and things. That is why theory is more vital than coding — because by focusing on the concepts and principles (i.e., computer science), you lot become beyond engineering science, beyond programming languages, and you tin easily cantankerous-connect with many other disciplines. Finite State Machines in business, biology, or physics? Sure —theory is mathematically grounded, and so transferable. Fourth dimension to clamber out of the metal box.
If mathematics is the "scientific discipline of patterns" then computer science, which came from applied mathematics, is the "scientific discipline of information patterns."
It is time to push the boundaries and go out the chemistry lab — meaning evolving out of the "coding" obsession. Coding is not real computer scientific discipline whatsoever more than then telescopes are real astronomy, microscopes are real microbiology, or Bunsen burners are real chemistry. As a group, we computer scientists need to take the theory and employ information technology on a wide scale. There are some efforts to practice this, but nosotros demand to do a lot more work. Many other disciplines can use what information science has created in the way of theory. To do this, we have to shift beyond coding and non limit theory to computer scientific discipline majors.
If you want to learn procedural literacy, algorithmic thinking, or computational thinking, there is a phrase for this: informatics. The field has been evolving since the inception of the mathematical components in the 1930s. Time to put away the Erlenmeyer flasks and go dorsum into mathematics. Time to convey the mathematics as broadly as possible, using multiple disciplines and representations.
Source: https://medium.com/creative-automata/what-to-do-after-learning-how-to-code-60867602c495
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