Re: English Learning For Beginners
Austin Vermont
I am a fairly athletic person. Growing up, I was always picked at least in the top 1/3rd or so of any people, for any sport or game that was being played, no matter what it was. I was a jack of all trades and master of none. This inspired in me a sort of mildly inappropriate feeling of entitlement to skill without a lot of effort, and so it went when I became a bowler.
Most people who bowl put a thumb and two fingers in the ball and carefully cultivate tossing the bowling ball in a pattern that causes the ball to start wide and hook into the middle. With no patience for learning that, I discovered I could do a pretty good job faking it by putting no fingers and thumbs in the ball and kind of twisting my elbow and chucking the ball down the lane.
In 1980, a couple of brothers with the last name Dreyfus proposed a model of skill acquisition that has gone on to have a fair bit of influence on discussions about learning, process, and practice. Later they would go on to publish a book based on this paper and, in that book, they would refine the model a bit to its current form, as shown on wikipedia.
This is actually the exact path that my bowling game followed in my path from bowling incompetence to some degree of bowling competence. I rapidly improved to the point of competence and then completely leveled off. In my case, improvement hit a local maximum and then stopped altogether, as I was too busy to continue on my path as-is or to follow through with my retooling.
And so we have chronicled the rise of the Expert Beginner: where they come from and why they stop progressing. In the next post in this series, I will explore the mechanics by which one or more Expert Beginners create a degenerative situation in which they actively cause festering and rot in the dynamics of groups that have talented members or could otherwise be healthy.
If I could turn back time, I'd do things much differently. This article will guide you through the steps to learning Python the right way. If I had this information when I started, it would have fast-tracked my career, saved thousands of hours of wasted time, and prevented much stress.
As a beginner, I struggled to keep myself awake when trying to memorize syntax. However, when I needed to apply Python fundamentals to build an interesting project, I happily stayed up all night to finish it.
My first independent project consisted of adapting my automated essay-scoring algorithm from R to Python. It didn't look pretty, but it gave me a sense of accomplishment and started me on the road to building my skills.
Learning Python is also a great way to impress at work (or get that promotion you've been vying for). To those who can't code, the ability to program sometimes seems like a superpower. Programming gives you the ability to leverage your knowledge and multiply your output. With it, you may be able to get ten times as much work done in the same amount of time. As we mentioned above, when you learn Python, you'll be able to gather data quickly and translate the numbers to real-world solutions. For example, in a business setting, you could add value by doing things like web scraping, sending emails automatically, or even analyzing supply chain production to find missed opportunities for cost savings or quality control. If your boss has mentioned that understanding data science could help you move toward your career goals, a self-paced Python course that helps you learn Python online could be the perfect way to balance a data career and personal development.
In the age of generative AI, Python's significance in 2024 cannot be overstated. It serves as the foundation for AI and machine learning, with key frameworks like TensorFlow and PyTorch relying on Python for development and innovation. Its effectiveness in automating tasks and analyzing large datasets is crucial for training AI models. Python's seamless integration with AI tools and its widespread use in AI research makes it indispensable for anyone involved in this field. The language's extensive community support, resource availability, and versatility across various domains, including web development and data science, further enhance its importance. Additionally, understanding Python is vital for navigating the ethical and governance aspects of AI, ensuring responsible development and application of AI technologies. Thus, Python's role extends beyond mere programming, becoming a crucial tool for shaping and understanding the future of AI.
Yes, it's very possible to learn Python on your own. There are many learning resources available on the web to help you learn Python for everything from web development to artificial intelligence. Here at Dataquest, we've helped thousands of students learn Python and get jobs in data science, all on their own schedules and from the comfort of their own homes. Teaching yourself Python does take time, though. You must also be sure that you're writing code and applying what you learn in real-world scenarios rather than just watching lecture videos and answering multiple-choice questions. Taking the right approach to learning Python can also be the difference between success or failure when you're learning through self-study.
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This introductory tutorial does not assume any prior experience of LaTeX but, hopefully, by the time you are finished, you will not only have written your first LaTeX document but also acquired sufficient knowledge and confidence to take the next steps toward LaTeX proficiency.
Various arguments can be proposed for, or against, learning to use LaTeX instead of other document-authoring applications; but, ultimately, it is a personal choice based on preferences, affinities, and documentation requirements.
The first line of code, \documentclassarticle, declares the document type known as its class, which controls the overall appearance of the document. Different types of documents require different classes; i.e., a CV/resume will require a different class than a scientific paper which might use the standard LaTeX article class. Other types of documents you may be working on may require different classes such as book or report. To get some idea of the many LaTeX class types available, visit the relevant page on CTAN (Comprehensive TeX Archive Network).
Having set the document class, our content, known as the body of the document, is written between the \begindocument and \enddocument tags. After opening the example above, you can make changes to the text and, when finished, view the resulting typeset PDF by recompiling the document. To do this in Overleaf, simply hit Recompile, as demonstrated in this brief video clip:
Any Overleaf project can be configured to recompile automatically each time it is edited: click the small arrow next to the Recompile button and set Auto Compile to On, as shown in the following screengrab:
where \documentclass[12pt, letterpaper]article defines the overall class (type) of document. Additional parameters, which must be separated by commas, are included in square brackets ([...]) and used to configure this instance of the article class; i.e., settings we wish to use for this particular article-class-based document.
Of course other font sizes, 9pt, 11pt, 12pt, can be used, but if none is specified, the default size is 10pt. As for the paper size, other possible values are a4paper and legalpaper. For further information see the article about page size and margins.
Importing graphics into a LaTeX document needs an add-on package which provides the commands and features required to include external graphics files. The above example loads the graphicx package which, among many other commands, provides \includegraphics... to import graphics and \graphicspath... to advise LaTeX where the graphics are located.
You can create different types of list using environments, which are used to encapsulate the LaTeX code required to implement a specific typesetting feature. An environment starts with \beginenvironment-name and ends with \endenvironment-name where environment-name might be figure, tabular or one of the list types: itemize for unordered lists or enumerate for ordered lists.
For further information you can open this larger Overleaf project which demonstrates various types of LaTeX list or visit our dedicated help article on LaTeX lists, which provides many more examples and shows how to create customized lists.
Longer documents, irrespective of authoring software, are usually partitioned into parts, chapters, sections, subsections and so forth. LaTeX also provides document-structuring commands but the available commands, and their implementations (what they do), can depend on the document class being used. By way of example, documents created using the book class can be split into parts, chapters, sections, subsections and so forth but the letter class does not provide (support) any commands to do that.
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