missing-semester
materials
Our great sponsors
missing-semester | materials | |
---|---|---|
374 | 199 | |
4,679 | 4,632 | |
1.2% | 1.1% | |
6.8 | 9.5 | |
about 2 months ago | 5 days ago | |
CSS | HTML | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
missing-semester
-
Please advise, still struggling intensely
You mentioned having issues with accessory concepts so perhaps this might help: https://missing.csail.mit.edu/. There's also a chapter on git
-
CS2030S and CS2040S advice
https://missing.csail.mit.edu/ is a good way to pass the Dec-Jan break if you want to prep for CS2030S + some more general stuff.
-
I cancelled my Replit subscription
Reflecting a little bit more I don't think it was replit's fault, per-say. But that change should have been made together with a larger adjustment to the program. Like adding a class/unit in the style of [the missing semester](https://missing.csail.mit.edu/) to make sure people came away with a good range of intuitions.
-
Advice to a Novice Programmer
From MJD's post: I think CS curricula should have a class that focuses specifically on these issues, on the matter of how do you actually write software?
But they never do.
FWIW, MIT's "The Missing Semester of Your CS Education" attempts to deal with this lack, though, even there, it's an unofficial course taught between terms, during MIT's IAP -- Independent Activities Period[1] -- and not an actual CS course.
[0] https://missing.csail.mit.edu/
[1] https://en.wikipedia.org/wiki/Traditions_and_student_activit...
- School of SRE: Curriculum for onboarding non-traditional hires and new grads
-
Advice / Resources from a "Seasoned Beginner"
Link to the "missing semester of your CS degree" course by MIT.
- ¿Recomendaciones sobre que aprender?
- Was soll ich lernen??
-
Help with starting a project in Visual Studio Code- and file management?
No clue, dude. To learn the terminal and git I think you should go through this: https://missing.csail.mit.edu/
-
What are some senior level learning resources you recommend for improving as a backend engineer?
The Missing Semester of Your CS Education. Basic but very useful stuff.
materials
- Think Python, 3rd Edition
-
Collection of resources to get started on your programming journey
Python - Python.org - Official Python website with documentation and tutorials. - Codecademy Python Course - Real Python - Python tutorials and articles for all skill levels.
- I have started my Python self Learning Journey - Is one source enough?
- How to manage procrastination and lack of focus during learning?
-
Other programing options?
Real Python (https://realpython.com/)
- Whats the best way to learn python for free?
-
Best free sites to learn Python Courses
https://realpython.com are very good in my opinion.
-
Recommended learning resources for rust
I know the official sites/books but am looking for something a bit more convenient and guided, similar to https://realpython.com/ which has really good text articles and also video courses covering specific topics.
-
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.
-
FLOSSing for Lent 12/40 - Python
Real Python - A great place to learn 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 - 🎓 HarvardX: CS50 Introduction to Computer Science (CS50x)
vimrc - The ultimate Vim configuration (vimrc)
javascript - JavaScript Style Guide
flexboxfroggy - A game for learning CSS flexbox 🐸
codewars.com - Issue tracker for Codewars
developer-roadmap - Interactive roadmaps, guides and other educational content to help developers grow in their careers.
Projects-Solutions - :pager: Links to others' solutions to Projects (https://github.com/karan/Projects/)
sdk - The Dart SDK, including the VM, dart2js, core libraries, and more.