A curated list of free/open source resources for you to learn Computer Science.
- GitHub - trekhleb/learn-python: 📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
- GitHub - Asabeneh/30-Days-Of-Python: 30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.
- GitHub - microsoft/c9-python-getting-started: Sample code for Channel 9 Python for Beginners course
- py4e - building a set of free materials, lectures, book and assignments to help students learn how to program in Python.
- GitHub - huangsam/ultimate-python: Ultimate Python study guide for newcomers and professionals alike.
- GitHub - satwikkansal/wtfpython: What the f*ck Python? 😱
- GitHub - wilfredinni/python-cheatsheet: Basic Cheat Sheet for Python (PDF, Markdown and Jupyter Notebook)
- GitHub - mattmakai/fullstackpython.com: Full Stack Python source with Pelican, Bootstrap and Markdown.
- GitHub - jerry-git/learn-python3: Jupyter notebooks for teaching/learning Python 3
- python-guide
- realpython - Learn Python online: Python tutorials for developers of all skill levels, Python books and courses, Python news, code examples, articles, and more.
- GitHub - Pierian-Data/Complete-Python-3-Bootcamp: Course Files for Complete Python 3 Bootcamp Course on Udemy
- GitHub - TomasBeuzen/python-programming-for-data-science: Content from the University of British Columbia's Master of Data Science course DSCI 511.
- GitHub - microsoft/Data-Science-For-Beginners: 10 Weeks, 20 Lessons, Data Science for All!
- GitHub - jakevdp/PythonDataScienceHandbook: Python Data Science Handbook: full text in Jupyter Notebooks
- GitHub - datasciencemasters/go: The Open Source Data Science Masters
- GitHub - ujjwalkarn/DataSciencePython: common data analysis and machine learning tasks using python
- Learn Python, Data Viz, Pandas & More | Tutorials | Kaggle
- GitHub - DataTalksClub/data-engineering-zoomcamp: Free Data Engineering course!
- GitHub - donnemartin/data-science-ipython-notebooks: Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
- GitHub - ossu/data-science: Path to a free self-taught education in Data Science!
- GitHub - joelgrus/data-science-from-scratch: code for Data Science From Scratch book
- GitHub - ujjwalkarn/DataSciencePython: common data analysis and machine learning tasks using python
- GitHub - andkret/Cookbook: The Data Engineering Cookbook
- GitHub - guipsamora/pandas_exercises: Practice your pandas skills!
- Data Flair - Free Online Courses from Industry Experts
- GitHub - microsoft/ML-For-Beginners: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
- GitHub - d2l-ai/d2l-en: Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.
- Machine Learning Crash Course | Google Developers
- GitHub - m2dsupsdlclass/lectures-labs: Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris
- GitHub - awslabs/amazon-sagemaker-mlops-workshop: Machine Learning Ops Workshop with SageMaker: lab guides and materials.
- GitHub - visenger/awesome-mlops: A curated list of references for MLOps
- GitHub - trekhleb/homemade-machine-learning: 🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
- GitHub - EthicalML/awesome-production-machine-learning: A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
- GitHub - graviraja/MLOps-Basics
- Full Stack Deep Learning
- GitHub - Yorko/mlcourse.ai: Open Machine Learning Course
- GitHub - trekhleb/machine-learning-experiments: 🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
- GitHub - hangtwenty/dive-into-machine-learning: Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)
- GitHub - afshinea/stanford-cs-229-machine-learning: VIP cheatsheets for Stanford's CS 229 Machine Learning
- GitHub - ujjwalkarn/Machine-Learning-Tutorials: machine learning and deep learning tutorials, articles and other resources
- GitHub - rasbt/python-machine-learning-book: The "Python Machine Learning (1st edition)" book code repository and info resource
- GitHub - instillai/machine-learning-course: Machine Learning Course with Python:
- GitHub - ZuzooVn/machine-learning-for-software-engineers: A complete daily plan for studying to become a machine learning engineer.
- GitHub - eugeneyan/applied-ml: 📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
- GitHub - kailashahirwar/cheatsheets-ai: Essential Cheat Sheets for deep learning and machine learning researchers
- GitHub - DataTalksClub/mlops-zoomcamp: Free MLOps course from DataTalks.Club
- mlbookcamp-code/course-zoomcamp at master · alexeygrigorev/mlbookcamp-code · GitHub
- Introduction: Coding for Economists
- GitHub - christianversloot/machine-learning-articles
- AI Campus - The learning platform for artificial intelligence
- pathmind - A.I. Wiki
- GitHub - Accel Brain Code: From Proof of Concept to Prototype
- GitHub - ajaymache/machine-learning-yearning: Machine Learning Yearning book by
🅰️ 𝓷𝓭𝓻𝓮𝔀 🆖 - Deep Learning by I. Goodfellow, Y. Bengio and A. Courville
- Michael Nielsen's online book on Neural Networks and Deep Learning
- Hastie, Tibshirani and Friedman, Elements of Statistical Learning
- David Forsyth's Applied Machine Learning textbook draft
- University of Illinois, Spring 2021 CS 498 Introduction to Deep Learning
- InsideAIML
- Analytics Vidhya Data Science Immersive Bootcamp
- Stanford CS231n: Convolutional Neural Networks for Visual Recognition
- U Michigan EECS 498: Deep Learning for Computer Vision
- MIT 6.S191: Introduction to Deep Learning
- Princeton COS 495: Introduction to Deep Learning
- UT Austin CS 342: Deep Learning
- IDIAP EE559: Deep Learning
- ENS Deep Learning: Do It Yourself
- U of I IE 534: Deep Learning
- MIT Structure and Interpretation of Deep Networks
- Berkeley CS285: Deep Reinforcement Learning
- Full Stack Deep Learning
- InsideAIML
- codebasics
- Analytics Vidhya Data Science Immersive Bootcamp
- pyimagesearch
- Rubik's Code
- Find Open Datasets and Machine Learning Projects | Kaggle
- UCI Machine Learning Repository
- GitHub - awesomedata/awesome-public-datasets: A topic-centric list of HQ open datasets.
- Google Dataset Search
- GitHub - JovianML/opendatasets: A Python library for downloading datasets from Kaggle, Google Drive, and other online sources.
- GitHub - huggingface/datasets: 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
- GitHub - GoogleTrends/data: An index of all open-source data
- GitHub - fighting41love/funNLP: Chinese NLB datasets
- Registry of Open Data on AWS
- Data Portals - A Comprehensive List of Open Data
- Open Data Inception - 2600+ Open Data Portals Around the World
- data.gov - The home of the U.S. Government’s open data
- Database - Eurostat
- re3data - Registry of Research Data Repositories
- FAIRsharing - # A curated, informative and educational resource on data and metadata standards, inter-related to databases and data policies.
- Academic Torrents - Making over 127.15TB of research data available!
- DataHub - help organizations of all sizes to design, develop and scale solutions to manage their data and unleash its potential
- Open Data Community | Join the Movement to Change the World!
- Harvard Dataverse
- Knoema - World and regional statistics, national data, maps, rankings
- Open Source Guides
- choosealicense - an open source license protects contributors and users. Businesses and savvy developers won’t touch a project without this protection.
- Github - microsoft/Web-Dev-For-Beginners: About 24 Lessons, 12 Weeks, Get Started as a Web Developer
- Github - bradtraversy/50projects50days: 50+ mini web projects using HTML, CSS & JS
- Github - h5bp/Front-end-Developer-Interview-Questions: A list of helpful front-end related questions you can use to interview potential candidates, test yourself or completely ignore.
- Frontend Roadmap
- Egghead.io - The Beginner's Guide to React
- Css Tricks - Css Series Tutorials
- Scrimba - Learn React for free
- ui.dev - The Free React Bootcamp
- Frontend Masters — Learn JavaScript, React, Vue & Angular from Masters of Front-End Development!
- Udemy - Node JS API Development for Beginners
- Coursera - Server-side Development with NodeJS, Express and MongoDB
- pluralsight - Node.js 12: Getting Started
- NestJS - Official NestJS Courses - Learn to build Node.js apps at any scale