missing-semester
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320 | 175 | |
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GNU General Public License v3.0 or later | MIT License |
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missing-semester
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Speak English to me, The secret World of Programmers
> The realization came a few weeks ago when someone shared The Missing Semester of Comp Sci on HN. Itâs full of basic things youâd expect any programmer to somehow magically know ⌠but they donât learn this anymore. https://missing.csail.mit.edu/
I do feel somewhat jealous though that these resources are now available for students to learn in a structured, borderline spoon-fed way when this stuff took me a number of years and hacking around to build up and gain muscle memory over. Still, I think the knowledge you struggle to learn yourself sticks around a lot longer than knowledge that was fed to you from school. :shrug: I could see it either way.
> "Why does it have to be so complicated? I just want to install a program"
> "Why would you do that in the command line? It's way easier using $Program"
A concerning observation thatâs slowly dawning on me is that more and more programmers donât know how computers work. They can write code, build software, and do lots of useful things. But they have no idea how computers work. Theyâre more akin to lusers as we used to call them than they are to hackers of old.
Fantastic at their specialty and the tools they use. But move a button to an unfamiliar place or throw them into a new (but fundamentally same) environment and theyâre lost.
The realization came a few weeks ago when someone shared The Missing Semester of Comp Sci on HN. Itâs full of basic things youâd expect any programmer to somehow magically know ⌠but they donât learn this anymore. https://missing.csail.mit.edu/
Seeing that link shared connected the dots in my mind. Iâve been wondering for months âWhy does everyone at work have so many random local environment issues all the time?â ⌠itâs been working fine for me for years. Same code and hardware. ÂŻ\_(ă)_/ÂŻ
- [CSE] Resource list
- The Missing Semester of Your CS Education
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Advice to be more efficient with the terminal?
This is a webpage I refer people often to: https://missing.csail.mit.edu/
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How much âprogrammingâ should I know?
This from MIT is called "The missing semester of your CS education" and provides some practical hands on skills like Git https://missing.csail.mit.edu/
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Do I need to have a lot of command line knowledge in order to learn Vim?
The Missing Semester: Made to address shortcomings in software engineers and teacher Vim.
- Software Development Engineers
materials
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How do I get started with ML?
Learn Python: Python is the most popular language for ML and AI projects. Start by learning the basics of Python, then move on to more advanced topics. Some great resources for learning Python include: Codecademy's Python course: https://www.codecademy.com/learn/learn-python Real Python: https://realpython.com/ Mathematics: A solid understanding of mathematics, particularly linear algebra, calculus, probability, and statistics, is essential for ML. Here are some resources to help you learn: Khan Academy courses: Linear Algebra: https://www.khanacademy.org/math/linear-algebra Calculus: https://www.khanacademy.org/math/calculus-1 Probability and Statistics: https://www.khanacademy.org/math/statistics-probability 3Blue1Brown's YouTube series on Linear Algebra: https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab Data processing and manipulation: Familiarize yourself with popular Python libraries for data manipulation and analysis, such as NumPy, pandas, and matplotlib: NumPy: https://numpy.org/doc/stable/user/quickstart.html pandas: https://pandas.pydata.org/pandas-docs/stable/getting_started/intro_tutorials/index.html matplotlib: https://matplotlib.org/stable/tutorials/index.html Machine learning concepts: Learn about the basic concepts of ML, including supervised learning, unsupervised learning, and reinforcement learning. Some great resources include: Coursera's Machine Learning course by Andrew Ng: https://www.coursera.org/learn/machine-learning Google's Machine Learning Crash Course: https://developers.google.com/machine-learning/crash-course Fast.ai's Practical Deep Learning for Coders course: https://course.fast.ai/ Deep learning libraries: Get familiar with popular deep learning libraries such as TensorFlow and PyTorch: TensorFlow: https://www.tensorflow.org/tutorials PyTorch: https://pytorch.org/tutorials/ Specialize and work on projects: Choose an area of interest (such as natural language processing, computer vision, or reinforcement learning), and start working on projects to apply your skills. You can find datasets and project ideas from sources like: Kaggle: https://www.kaggle.com/ Papers With Code: https://paperswithcode.com/ Stay up-to-date and join the community: Follow ML blogs, podcasts, and conferences to stay current with the latest developments. Join ML communities and forums like r/MachineLearning on Reddit, AI Stack Exchange, or specialized Discord and Slack groups.
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FLOSSing for Lent 12/40 - Python
Real Python - A great place to learn python
- Donde aprender Python POSTA?
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Best websites to give me tasks?
There's many popular Python educational blogs out there. You can check out RealPython, PythonAlgos, LearnPython, and many more.
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GitHub - antedoro/arberia: Arberia Theme is a fully responsive tech-blogger theme for Hugo with 4 single post layout!
Question - Was this theme created by/for realpython.com and they've decided to open source it?
- Pythont tanulni ?
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Best Communities For Developers To Join
The Real Python is one of the most valuable resources for any budding Python developer â housing thousands of professional video lessons and tutorials on every aspect of the popular programming language.
- Best resources to study Python
- Data Science - Que curso online recomendam para Python e Machine Learning?
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Discussion Thread
Real Python
What are some alternatives?
cs-topics - My personal curriculum covering basic CS topics. This might be useful for self-taught developers... A work in development! This might take a very long time to get finished!
computer-science - :mortar_board: Path to a free self-taught education in Computer Science!
learnxinyminutes-docs - Code documentation written as code! How novel and totally my idea!
CS50x-2021 - đ HarvardX: CS50 Introduction to Computer Science (CS50x)
codewars.com - Issue tracker for Codewars
javascript - JavaScript Style Guide
Projects-Solutions - :pager: Links to others' solutions to Projects (https://github.com/karan/Projects/)
developer-roadmap - Interactive roadmaps, guides and other educational content to help developers grow in their careers.
flexboxfroggy - A game for learning CSS flexbox đ¸
sdk - The Dart SDK, including the VM, dart2js, core libraries, and more.