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Python can be easy to pick up whether you're a first time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way writing programs with Python!
- Subjects:
- Computing
- Keywords:
- Computer programming Python (Computer program language) Information visualization Computer science
- Resource Type:
- Others
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Others
Symbol Table is an important data structure created and maintained by the compiler in order to keep track of semantics of variables i.e. it stores information about the scope and binding information about names, information about instances of various entities such as variable and function names, classes, objects, etc.
- Course related:
- COMP3438 System Programming
- Subjects:
- Computing
- Keywords:
- Compilers (Computer programs)
- Resource Type:
- Others
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Others
Welcome to the Coding Train with Daniel Shiffman! A community dedicated to learning creative coding with beginner-friendly tutorials and projects on YouTube and more.
- Subjects:
- Computing
- Keywords:
- Coding theory Computer programming
- Resource Type:
- Others
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Others
Learn to code, design, and more—all on your own time
- Subjects:
- Computing
- Keywords:
- Coding theory Mobile apps Computer programming
- Resource Type:
- Others
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Video
This channel walks you through the entire process of learning to code in Python; all the way from basics to advanced machine learning and deep learning. The primary emphasis will be on image processing and other relevant functionality. Why did I create this channel? To help you (students and researchers) gain a new skill and succeed in your respective fields.
You may think coding is hard and that it's not your cup of tea, but Python made it easy to code even advanced algorithms. In addition, coding will make you self sufficient, it will teach you how to think, it improves your collaborative skills and it can take your career to new heights. Therefore, if you want to stay ahead of your peers and relevant in your field, overcome your fears and start coding!
- Subjects:
- Computing
- Keywords:
- Computer programming Computer science Python (Computer program language)
- Resource Type:
- Video
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Video
Welcome to Zero to Hero for Natural Language Processing using TensorFlow! If you’re not an expert on AI or ML, don’t worry -- we’re taking the concepts of NLP and teaching them from first principles with our host Laurence Moroney.
- Subjects:
- Computing
- Keywords:
- Machine learning Natural language processing (Computer science)
- Resource Type:
- Video
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Video
This course will give you a full introduction into all of the core concepts in python. Follow along with the videos and you'll be a python programmer in no time! Want more from Mike? He's starting a coding RPG/Bootcamp - https://simulator.dev/
- Course related:
- AF3507 Company Law
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- Video
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Video
This course will give you a full introduction into all of the core concepts in C++. * Contents * -- (0:00:00) Introduction -- (0:01:38) Windows Installation -- (0:04:54) Mac Installation -- (0:08:44) Setup & Hello World -- (0:12:29) Drawing a Shape -- (0:19:55) Variables -- (0:31:43) Data Types -- (0:39:15) Working With Strings -- (0:49:00) Working With Numbers -- (0:59:41) Getting User Input -- (1:05:32) Building a Calculator -- (1:09:28) Building a Mad Libs -- (1:13:45) Arrays -- (1:20:03) Functions -- (1:29:47) Return Statement -- (1:35:22) If Statements -- (1:47:15) If Statements (con't) -- (1:55:58) Building a Better Calculator -- (2:02:20) Switch Statements -- (2:10:47) While Loops -- (2:18:53) Building a Guessing Game -- (2:29:18) For Loops -- (2:38:32) Exponent Function -- (2:45:21) 2d Arrays & Nested Loops -- (2:54:55) Comments -- (2:59:11) Pointers -- (3:13:26) Classes & Objects -- (3:25:40) Constructor Functions -- (3:34:41) Object Functions
- Course related:
- COMP1011 Programming Fundamentals
- Subjects:
- Computing
- Keywords:
- C++ (Computer program language)
- Resource Type:
- Video
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Others
Welcome to Google's Python Class -- this is a free class for people with a little bit of programming experience who want to learn Python. The class includes written materials, lecture videos, and lots of code exercises to practice Python coding. These materials are used within Google to introduce Python to people who have just a little programming experience. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and http connections. The class is geared for people who have a little bit of programming experience in some language, enough to know what a "variable" or "if statement" is. Beyond that, you do not need to be an expert programmer to use this material. To get started, the Python sections are linked at the left -- Python Set Up to get Python installed on your machine, Python Introduction for an introduction to the language, and then Python Strings starts the coding material, leading to the first exercise. The end of each written section includes a link to the code exercise for that section's material. The lecture videos parallel the written materials, introducing Python, then strings, then first exercises, and so on. At Google, all this material makes up an intensive 2-day class, so the videos are organized as the day-1 and day-2 sections. This material was created by Nick Parlante working in the engEDU group at Google. Special thanks for the help from my Google colleagues John Cox, Steve Glassman, Piotr Kaminksi, and Antoine Picard. And finally thanks to Google and my director Maggie Johnson for the enlightened generosity to put these materials out on the internet for free under the Creative Commons Attribution 2.5 license -- share and enjoy!
- Course related:
- COMP1002 Computational Thinking
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- Others
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MOOC
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- MOOC
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MOOC
This course is designed to teach you the foundations in order to write simple programs in Python using the most common structures. No previous exposure to programming is needed. By the end of this course, you'll understand the benefits of programming in IT roles; be able to write simple programs using Python; figure out how the building blocks of programming fit together; and combine all of this knowledge to solve a complex programming problem. We'll start off by diving into the basics of writing a computer program. Along the way, you’ll get hands-on experience with programming concepts through interactive exercises and real-world examples. You’ll quickly start to see how computers can perform a multitude of tasks — you just have to write code that tells them what to do.
- Course related:
- COMP1001 Problem Solving Methodology in Information Technology
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- MOOC
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Video
This precalculus video tutorial provides a basic introduction into linear programming. It explains how to write the objective function and constraints of linear programming word problems. It discusses how to find all of the corner points including the point of intersection where you have to solve the system of linear inequalities. It discusses which region to shade and how to determine the maximum profit or sales produced by a company or business and how to determine the number of items that should be produced to maximize such profit or revenue. This video contains plenty of examples and practice problems on linear programming.
- Course related:
- LGT3102 Management Science
- Subjects:
- Computing
- Keywords:
- Linear programming
- Resource Type:
- Video
-
MOOC
In this course, you'll learn the fundamentals of the Python programming language, along with programming best practices. You’ll learn to represent and store data using Python data types and variables, and use conditionals and loops to control the flow of your programs. You’ll harness the power of complex data structures like lists, sets, dictionaries, and tuples to store collections of related data. You’ll define and document your own custom functions, write scripts, and handle errors. Lastly, you’ll learn to find and use modules in the Python Standard Library and other third-party libraries.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- MOOC
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Others
We're like Duolingo for learning to code. When learning to code, most people get stuck on the "bridge" between memorizing syntax and understanding the logic that makes it all work. We believe the most effective way to learn a programming language is to break the process into three phases:(1)Memorize syntax; (2) Solve problems; and (3) Make stuff. Most beginners jump from memorizing syntax directly into making stuff (or trying) without fully understanding how syntax is used to solve problems. In other words, they haven't learned how to think like a programmer, yet they're trying to solve problems like a programmer. Edabit was created to bridge this gap, while also making the process fun and addictive.
- Course related:
- COMP1011 Programming Fundamentals
- Subjects:
- Computing
- Keywords:
- Computer programming
- Resource Type:
- Others
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Others
SQL is a standard language for storing, manipulating and retrieving data in databases. Our SQL tutorial will teach you how to use SQL in: MySQL, SQL Server, MS Access, Oracle, Sybase, Informix, Postgres, and other database systems.
- Course related:
- COMP2411 Database Systems
- Subjects:
- Computing
- Keywords:
- SQL (Computer program language)
- Resource Type:
- Others
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e-book
How to Think Like a Computer Scientist: Learning with Pythonis an introduction to programming using Python.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers) Textbooks Python (Computer program language)
- Resource Type:
- e-book
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e-book
Unlike some other textbooks, this one does not follow a top-down narrative. Rather it has the flow of a conversation, with backtracking. We will often build up programs incrementally, just as a pair of programmers would. We will include mistakes, not because I don't know the answer, but because this is the best way for you to learn. Including mistakes makes it impossible for you to read passively: you must instead engage with the material, because you can never be sure of the veracity of what you're reading. At the end, you'll always get to the right answer. However, this non-linear path is more frustrating in the short term (you will often be tempted to say, “Just tell me the answer, already!”), and it makes the book a poor reference guide (you can't open up to a random page and be sure what it says is correct). However, that feeling of frustration is the sensation of learning. I don't know of a way around it. At various points you will encounter this: ExerciseThis is an exercise. Do try it. This is a traditional textbook exercise. It's something you need to do on your own. If you're using this book as part of a course, this may very well have been assigned as homework. In contrast, you will also find exercise-like questions that look like this: Do Now!There's an activity here! Do you see it? When you get to one of these, stop. Read, think, and formulate an answer before you proceed. You must do this because this is actually an exercise, but the answer is already in the book—most often in the text immediately following (i.e., in the part you're reading right now)—or is something you can determine for yourself by running a program. If you just read on, you'll see the answer without having thought about it (or not see it at all, if the instructions are to run a program), so you will get to neither (a) test your knowledge, nor (b) improve your intuitions. In other words, these are additional, explicit attempts to encourage active learning. Ultimately, however, I can only encourage it; it's up to you to practice it. The main programming language used in this book is Racket. Like with all operating systems, however, Racket actually supports a host of programming languages, so you must tell Racket which language you're programming in. This textbook has been used in classes at: Brown University, Cal Poly, Columbus State University, Northeastern University, NYU, Reed College, UC-San Diego, UC-Santa Cruz, University of Rhode Island, University of Utah, Westmont College, Williams College, Worcester Polytechnic Institute.
- Subjects:
- Computing
- Keywords:
- Programming languages (Electronic computers) Textbooks
- Resource Type:
- e-book
-
e-book
Comunidad creada para compartir experiencias en torno al uso de Tecnologías de la Información como apoyo a procesos de enseñanza-aprendizaje usando modelos de aprendizaje colaborativo
- Subjects:
- Computing
- Keywords:
- Education--Effect of technological innovations on Computer-assisted instruction Textbooks
- Resource Type:
- e-book
-
e-book
The book is based on “First semester in Numerical Analysis with Julia”, written by Giray Ökten. The contents of the original book are retained, while all the algorithms are implemented in Python (Version 3.8.0). Python is an open source (under OSI), interpreted, general-purpose programming language that has a large number of users around the world. Python is ranked the third in August 2020 by the TIOBE programming community index, a measure of popularity of programming languages, and is the top-ranked interpreted language. We hope this book will better serve readers who are interested in a first course in Numerical Analysis, but are more familiar with Python for the implementation of the algorithms. The first chapter of the book has a self-contained tutorial for Python, including how to set up the computer environment. Anaconda, the open-source individual edition, is recommended for an easy installation of Python and effortless management of Python packages, and the Jupyter environment, a web-based interactive development environment for Python as well as many other programming languages, was used throughout the book and is recommended to the readers for easy code development, graph visualization and reproducibility.
- Subjects:
- Computing
- Keywords:
- Numerical analysis Computer programming Programming languages (Electronic computers) Textbooks Python (Computer program language)
- Resource Type:
- e-book
-
e-book
Think Raku is an introduction to computer science and programming intended for people with little or no experience. This aim of this book is not primarily to teach Raku, but instead to teach the art of programming, using the Raku language. After having completed this book, you should hopefully be able to write programs to solve relatively difficult problems in Raku, but my main aim is to teach computer science, software programming, and problem solving rather than solely to teach the Raku language itself. Think Raku is a free book available under a Creative Commons license. Readers are free to copy and distribute the text; they are also free to modify it, which allows them to adapt the book to different needs, and to help develop new material.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers) Textbooks
- Resource Type:
- e-book
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