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🤓 My curated lists of awesome data science books and resources.
https://github.com/corralm/awesome-resources

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🤓 My curated lists of awesome data science books and resources.

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# Awesome Data Science Resources 

A curated list of awesome books I've read, courses I've completed, and other resources I use.



## Artificial Intelligence

- `Book` [**Atlas of AI**](https://katecrawford.net): Ethics, power, politics, and the planetary costs of AI.

- `Course` [**AI for Everyone**](https://www.coursera.org/learn/ai-for-everyone): Overview of everything AI.

- `Course` [**AI and Public Health**](https://www.coursera.org/learn/ai-and-public-health): Learn to apply a framework for AI initiatives.

- `Course` [**Building Generative AI Applications with Gradio**](https://www.deeplearning.ai/short-courses/building-generative-ai-applications-with-gradio/): Quickly share ML apps.

- `Course` [**Building Systems With The ChatGPT API**](https://www.deeplearning.ai/short-courses/building-systems-with-chatgpt/): Learn how to chain calls to a LLM.

- `Course` [**ChatGPT Prompt Engineering for Developers**](https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/): Intro to using the ChatGPT API.

- `Course` [**Generative AI with Large Language Models**](https://www.coursera.org/learn/generative-ai-with-llms): Explore the generative AI lifecycle.

- `Course` [**LangChain for LLM Application Development**](https://www.deeplearning.ai/short-courses/langchain-for-llm-application-development/): Expand the capabilities of LLMs.

- `Course` [**LangChain: Chat with Your Data**](https://www.deeplearning.ai/short-courses/langchain-chat-with-your-data/): Learn to build a system with local data.

- `Course` [**Prompt Engineering for ChatGPT**](https://www.coursera.org/learn/prompt-engineering/): Discover various prompt patterns to fully leverage LLMs. 

- `Report` [**AI Fairness**](https://learning.oreilly.com/library/view/ai-fairness/9781492077664/): Explore how to approach fairness and bias.



## Data Analysis and Engineering

- `Book` [**Python for Data Analysis (3rd Edition)**](https://learning.oreilly.com/library/view/python-for-data/9781098104023/): Data analysis handbook.

- `Event` [**Data Engineering for Data Scientists**](https://learning.oreilly.com/live-events/data-engineering-for-data-scientists/0636920303039/0636920053608/): Automating data pipeline workflows.

- `Library` [**Pandas**](https://pandas.pydata.org): Data analysis and manipulation tool.



## Data Science

- `Book` [**Hands-On Machine Learning (2nd Edition)**](https://learning.oreilly.com/library/view/hands-on-machine-learning/9781492032632/): Machine learning handbook with examples.

- `Book` [**Python Data Science Handbook**](https://learning.oreilly.com/library/view/python-data-science/9781491912126/): Intro to iPython, NumPy, Pandas, Matplotlib, and Scikit-Learn.

- `Library` [**Scikit-Learn**](https://scikit-learn.org/stable/): Machine learning and predictive data analysis.

- `Publication` [**The Batch**](https://www.deeplearning.ai/the-batch/): A weekly newsletter about AI news and insights.

- `Publication` [**Towards Data Science**](https://towardsdatascience.com): Medium publication sharing data science concepts, ideas, and codes.

- `Resource` [**Kaggle**](https://www.kaggle.com/): Machine learning and data science community.

- `Resource` [**Machine Learning Mastery**](https://machinelearningmastery.com/start-here): Online machine learning guides and tutorials.



## Data Visualization

- `Book` [**Practical Tableau**](https://learning.oreilly.com/library/view/practical-tableau/9781491977309/): Tableau reference book.

- `Book` [**Storytelling with Data**](https://learning.oreilly.com/library/view/storytelling-with-data/9781119621492/): Influence action through data storytelling.

- `Book` [**The Big Book of Dashboards**](https://learning.oreilly.com/library/view/the-big-book/9781119282716/): Inspiration for building great dashboards.

- `Deck` [**On Presentations**](https://www.beautiful.ai/player/-LiSV45O9K1sE8uv5oMj/On-Presentations): Presentation tips and design.

- `Library` [**Plotly**](https://plotly.com/python/): Python graphing library for interactive and publication-quality graphs.

- `Resource` [**Tableau Visual Vocabulary**](https://public.tableau.com/app/profile/andy.kriebel/viz/VisualVocabulary/VisualVocabulary): Types of charts within Tableau.



## Developer Surveys

- `Publication` [**JetBrains Python Developer Survey**](https://www.jetbrains.com/resources/industry-reports/): Reveal the current state of Python.

- `Publication` [**Stack Overflow Annual Developer Survey**](https://insights.stackoverflow.com/survey): Examines all aspects of the developer experience.



## Git

- `Article` [**How to Write a Git Commit Message**](https://cbea.ms/git-commit/): Commit messages matter. Here's how to write them well.

- `Book` [**Git for Programmers**](https://learning.oreilly.com/library/view/git-for-programmers/9781801075732/): Ultimate guide to git.

- `Book` [**Git Essentials (2nd Edition)**](https://learning.oreilly.com/library/view/git-essentials/9781787120723/): Short guide on git fundamentals.

- `Course` [**Git Essentials LiveLessons**](https://learning.oreilly.com/videos/git-essentials-livelessons/9780134655284/): Step-by-step git lessons.

- `Resource` [**Git Commit Types**](https://github.com/pvdlg/conventional-changelog-metahub#commit-types): List of conventional commit types.



## Oh My Zsh

- `Framework` [**Oh My Zsh**](https://ohmyz.sh): An open source framework for managing Zsh configuration.

- `Plugin` [**git**](https://github.com/ohmyzsh/ohmyzsh/tree/master/plugins/git): Provides many aliases and a few useful functions.

- `Plugin` [**macos**](https://github.com/ohmyzsh/ohmyzsh/tree/master/plugins/macos): Provides a few utilities to make it more enjoyable on macOS.

- `Plugin` [**vscode**](https://github.com/ohmyzsh/ohmyzsh/tree/master/plugins/vscode): Provides many aliases to simplify the interaction between the command line and VS Code.

- `Plugin` [**zsh-autosuggestions**](https://github.com/zsh-users/zsh-autosuggestions): Suggests commands as you type based on history and completions.

- `Plugin` [**zsh-safe-rm**](https://github.com/mattmc3/zsh-safe-rm): Put files in your OS's trash instead of permanently deleting them.

- `Plugin` [**zsh-syntax-highlighting**](https://github.com/zsh-users/zsh-syntax-highlighting): Provides syntax highlighting for Zsh.



## Productivity Apps

- `App` [**Anki**](https://apps.ankiweb.net): A program which makes remembering things easy. Here's a [primer](http://augmentingcognition.com/ltm.html).

- `App` [**Magnet**](https://magnet.crowdcafe.com): A window manager for macOS.

- `App` [**Things**](https://culturedcode.com/things/): A beautiful task manager for macOS & iOS.

- `App` [**Typinator**](https://www.ergonis.com/products/typinator/): Automates the process of inserting frequently used text/code.



## Programming Fundamentals

- `App` [**iTerm2**](https://iterm2.com): macOS Terminal replacement.

- `App` [**Visual Studio Code**](https://code.visualstudio.com/): Free coding editor with support for many languages.

- `Book` [**A Common-Sense Guide to Data Structures and Algorithms**](https://learning.oreilly.com/library/view/a-common-sense-guide/9781680502794/): Practical DSA guide.

- `Book` [**The Linux Command Line (2nd Edition)**](https://learning.oreilly.com/library/view/the-linux-command/9781492071235/): Command line fundamentals.

- `Resource` [**W3Schools**](https://www.w3schools.com): The largest web developer site on the internet.



## Project Management

- `Book` [**Agile Practical Guide**](https://learning.oreilly.com/library/view/agile-practice-guide/9781628253993/): Agile guide created by the Project Management Institute and Agile Alliance.

- `Book` [**Mastering the Requirement Process**](https://www.amazon.com/Mastering-Requirements-Process-Getting-Right/dp/0321815742): Getting requirements right.

- `Course` [**An Agile Crash Course**](https://learning.oreilly.com/videos/an-agile-crash/9781789533415/): Agile for Dummies.



## Python

- `App` [**PyCharm**](https://www.jetbrains.com/pycharm/): The Python IDE for Professional Developers.

- `Book` [**Python Testing with pytest**](https://learning.oreilly.com/library/view/python-testing-with/9781680509427/): Step-by-step instructions and sample code for pytest.

- `Book` [**Python Crash Course (2nd Edition)**](https://learning.oreilly.com/library/view/python-crash-course/9781492071266/): Python fundamentals.

- `Course` [**Effective Python**](https://learning.oreilly.com/videos/effective-python/9780134175249/): Lessons to writing programs the Pythonic way.

- `Course` [**Python Fundamentals**](https://learning.oreilly.com/videos/python-fundamentals/9780135917411/): Code-oriented presentation of Python.

- `Framework` [**Miniconda**](https://docs.conda.io/en/latest/miniconda.html): A small, bootstrap version of Anaconda.

- `Resource` [**Python Morsels**](https://www.pythonmorsels.com): Learn to write better Python code.

- `Resource` [**Real Python**](https://realpython.com): Online Python tutorials, video courses, news, and more.



## SQL

- `App` [**TablePlus**](https://tableplus.com/): Modern, native, and friendly GUI tool for relational databases.

- `Book` [**SQL Pocket Guide (4th Edition)**](https://learning.oreilly.com/library/view/sql-pocket-guide/9781492090397/): Popular SQL pocket guide.

- `Book` [**Learning SQL (3rd Edition)**](https://learning.oreilly.com/library/view/learning-sql-3rd/9781492057604/): Learn SQL fundamentals.

- `Resource` [**PostgreSQL Exercises**](https://pgexercises.com): Provides a series of questions and explanations.



## Statistics

- `Book` [**OpenIntro Statistics**](https://www.openintro.org/book/os/): Comprehensive statistics textbook with real-world examples.

- `Book` [**Practical Statistics for Data Scientists (2nd Edition)**](https://learning.oreilly.com/library/view/practical-statistics-for/9781492072935/): Statistical methods for data science.

- `Course` [**A/B Testing, A Data Science Perspective**](https://learning.oreilly.com/videos/a-b-testing-a/9781491934777/): Guide to designing and executing A/B tests.

- `Resource` [**Khan Academy**](https://www.khanacademy.org/): Short video lessons including statistics, probablity, algebra, and more.



## Web Scraping

- `Book` [**Web Scraping with Python (2nd Edition)**](https://learning.oreilly.com/library/view/web-scraping-with/9781491985564/): Web scraping handbook.

- `Event` [**Advanced Web Scraping**](https://learning.oreilly.com/live-events/advanced-web-scraping/0636920376163/0636920412489/): Learn about scheduling and Selenium.

- `Library` [**Selenium**](https://www.selenium.dev): Web browser automation.

- `Library` [**Scrapy**](https://scrapy.org): Framework for extracting data from websites.



## Workflow Engineering

- `Book` [**The Phoenix Project**](https://itrevolution.com/product/the-phoenix-project/): A novel about IT and DevOps.

- `Book` [**Workflow Modeling**](https://www.amazon.com/Workflow-Modeling-Improvement-Application-Development/dp/1596931922): Tools for process improvement and application development.