awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
https://github.com/academic/awesome-datascience
Last synced: 5 days ago
JSON representation
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Training Resources
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Colleges
- Master of Data Science @ Illinois Institute of Technology
- Master of Applied Data Science @ The University of Michigan
- Master Data Science and Artificial Intelligence @ Eindhoven University of Technology
- Master's Degree in Data Science and Computer Engineering @ University of Granada
- A list of colleges and universities offering degrees in data science.
- Msc in Data Science @ The University of Edinburgh
- Master of Applied Data Science @ The University of Michigan
- Msc in Data Science @ The University of Edinburgh
- Msc in Data Science @ The University of Edinburgh
- Master Data Science and Artificial Intelligence @ Eindhoven University of Technology
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Free Courses
- Data Scientist with R
- Data Scientist with Python
- Genetic Algorithms OCW Course
- Convex Optimization - Convex Optimization (basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory...)
- Skillcombo - Data Science - 1000+ free online Data Science courses
- Learning from Data - Introduction to machine learning covering basic theory, algorithms and applications
- Kaggle - Learn about Data Science, Machine Learning, Python etc
- ML Observability Fundamentals - Learn how to monitor and root-cause production ML issues.
- Weights & Biases Effective MLOps: Model Development - Free Course and Certification for building an end-to-end machine using W&B
- Python for Data Science by Scaler - This course is designed to empower beginners with the essential skills to excel in today's data-driven world. The comprehensive curriculum will give you a solid foundation in statistics, programming, data visualization, and machine learning.
- MLSys-NYU-2022 - Slides, scripts and materials for the Machine Learning in Finance course at NYU Tandon, 2022.
- LLMOps: Building Real-World Applications With Large Language Models - Learn to build modern software with LLMs using the newest tools and techniques in the field.
- Prompt Engineering for Vision Models - Learn to prompt cutting-edge computer vision models with natural language, coordinate points, bounding boxes, segmentation masks, and even other images in this free course from DeepLearning.AI.
- AI Expert Roadmap - Roadmap to becoming an Artificial Intelligence Expert
- Hands-on Train and Deploy ML - A hands-on course to train and deploy a serverless API that predicts crypto prices.
- Data Science Course By IBM - Free resources and learn what data science is and how it’s used in different industries.
- Python for Machine Learning - Start your journey to machine learning with Python, one of the most powerful programming languages.
- Data Scientist with R
- Data Scientist with Python
- Data Science - Open Source Society University
- Genetic Algorithms OCW Course
- Neural Networks: Zero to Hero - A free video series by Andrej Karpathy covering neural networks from scratch — backpropagation, makemore, GPT, and more.
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Intensive Programs
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MOOC's
- Coursera Introduction to Data Science
- Data Science - 9 Steps Courses, A Specialization on Coursera
- Data Mining - 5 Steps Courses, A Specialization on Coursera
- Machine Learning – 5 Steps Courses, A Specialization on Coursera
- OpenIntro
- CS 171 Visualization
- Process Mining: Data science in Action
- Oxford Deep Learning
- Oxford Machine Learning
- UBC Machine Learning - video
- Coursera Big Data Specialization
- Statistical Thinking for Data Science and Analytics by Edx
- Cognitive Class AI by IBM
- Udacity - Deep Learning
- Keras in Motion
- Microsoft Professional Program for Data Science
- COMP3222/COMP6246 - Machine Learning Technologies
- CS 231 - Convolutional Neural Networks for Visual Recognition
- Coursera Tensorflow in practice
- Coursera Deep Learning Specialization
- 365 Data Science Course
- Coursera Natural Language Processing Specialization
- Coursera GAN Specialization
- Codecademy's Data Science
- Linear Algebra - Linear Algebra course by Gilbert Strang
- A 2020 Vision of Linear Algebra (G. Strang)
- Data Science: Statistics & Machine Learning
- Machine Learning Engineering for Production (MLOps)
- Recommender Systems Specialization from University of Minnesota
- Stanford Artificial Intelligence Professional Program
- Data Scientist with Python
- Programming with Julia
- Scaler Data Science & Machine Learning Program
- Data Scientist with Python
- CS 109 Data Science
- Data Science Specialization
- Python for Data Science Foundation Course
- Data Science Skill Tree
- Data Science for Beginners - Learn with AI tutor
- Machine Learning for Beginners - Learn with AI tutor
- Linear Algebra - Linear Algebra course by Gilbert Strang
- Introduction to Data Science
- Getting Started with Python for Data Science
- Maschinelle Sprachgebrauchsanalyse - Grundlagen der Korpuslinguistik - course material on text-mining / corpus-linguistics *in German* funded by the federal state of North Rhine-Westphalia
- Programmieren für Germanist*innen - course material: programming in python *in German* for digital humanities - funded by the federal state of North Rhine-Westphalia
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Tutorials
- 1000 Data Science Projects
- Machine Learning, Data Science and Deep Learning with Python
- How To Label Data
- Your Guide to Latent Dirichlet Allocation
- Over 1000 Data Science Online Courses at Classpert Online Search Engine
- Python for Data Science: A Beginner’s Guide
- 12 free Data Science projects to practice Python and Pandas
- #tidytuesday
- Data science your way
- PySpark Cheatsheet
- Tutorials of source code from the book Genetic Algorithms with Python by Clinton Sheppard
- Tutorials to get started on signal processing for machine learning
- Minimum Viable Study Plan for Machine Learning Interviews
- Best CV/Resume for Data Science Freshers
- Understand Data Science Course in Java
- Data Analytics Interview Questions (Beginner to Advanced)
- Top 100+ Data Science Interview Questions and Answers
- DataCamp Cheatsheets
- Realtime deployment - series model deployment.
- 1000 Data Science Projects
- DataDriven - SQL, Python, and Data Modeling Interview Questions
- TutorialSearch - Free cross-platform search engine indexing 50,000+ tutorials from Udemy, Skillshare, Pluralsight, and other major learning platforms across 45+ categories.
- StepByStepML - Interactive calculator that visualizes the step-by-step manual math behind machine learning algorithms for exam prep.
- How to Build Optimal AI Agents That Actually Work - A developer handbook on designing and building effective AI agents.
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What is Data Science?
- What is Data Science @ Quora
- What is Data Science @ O'reilly
- The sexiest job of 21st century
- Wikipedia
- How to Become a Data Scientist
- a very short history of #datascience - -computer science. The term “Data Science” has emerged only recently to specifically designate a new profession that is expected to make sense of the vast stores of big data. But making sense of data has a long history and has been discussed by scientists, statisticians, librarians, computer scientists and others for years. The following timeline traces the evolution of the term “Data Science” and its use, attempts to define it, and related terms._ |
- Software Development Resources for Data Scientists - ready code and tools._|
- Data Scientist Roadmap - driven world where approx 328.77 million terabytes of data are generated daily. And this number is only increasing day by day, which in turn increases the demand for skilled data scientists who can utilize this data to drive business growth._|
- Navigating Your Path to Becoming a Data Scientist - demand careers today. With businesses increasingly relying on data to make decisions, the need for skilled data scientists has grown rapidly. Whether it’s tech companies, healthcare organizations, or even government institutions, data scientists play a crucial role in turning raw data into valuable insights. But how do you become a data scientist, especially if you’re just starting out? _|
- Data Science For Beginners - week, 20-lesson curriculum all about Data Science. |
- Software Development Resources for Data Scientists - ready code and tools._|
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Where do I Start?
- Scikit-Learn - purpose data science package which implements the most popular algorithms - it also includes rich documentation, tutorials, and examples of the models it implements. Even if you prefer to write your own implementations, Scikit-Learn is a valuable reference to the nuts-and-bolts behind many of the common algorithms you'll find. With [Pandas](https://pandas.pydata.org/), one can collect and analyze their data into a convenient table format. [Numpy](https://numpy.org/) provides very fast tooling for mathematical operations, with a focus on vectors and matrices. [Seaborn](https://seaborn.pydata.org/), itself based on the [Matplotlib](https://matplotlib.org/) package, is a quick way to generate beautiful visualizations of your data, with many good defaults available out of the box, as well as a gallery showing how to produce many common visualizations of your data.
Programming Languages
Categories
Sub Categories
Miscellaneous Tools
136
Bloggers
123
Deep Learning Packages
90
Books
84
Datasets
80
Comparison
76
Twitter Accounts
73
Comics
50
MOOC's
45
YouTube Videos & Channels
42
Facebook Accounts
41
Journals, Publications and Magazines
41
General Machine Learning Packages
38
Podcasts
33
Algorithms
28
Tutorials
24
Free Courses
22
Colleges
20
Infographics
15
Presentations
11
Data Science Competitions
6
Tools
4
Research & Knowledge Retrieval
4
Newsletters
4
Telegram Channels
3
Intensive Programs
2
Workflow
2
Hobby
1
Mailing lists
1
GitHub Groups
1
Slack Communities
1
Disaster
1
Frameworks
1
Keywords
machine-learning
86
python
59
deep-learning
58
data-science
50
pytorch
26
tensorflow
21
scikit-learn
13
keras
13
ml
12
data-analysis
12
neural-network
11
reinforcement-learning
11
artificial-intelligence
10
mlops
10
ai
9
data-visualization
9
numpy
8
computer-vision
8
hyperparameter-optimization
7
object-detection
7
awesome-list
7
gradient-boosting
7
neural-networks
7
llm
6
data-mining
6
jupyter
6
pandas
6
r
6
jupyter-notebook
6
data
5
pipeline
5
workflow
5
image-processing
5
big-data
5
spark
5
nlp
5
explainable-ai
5
explainable-ml
5
awesome
5
dataset
5
cli
4
classifier
4
gpu
4
data-engineering
4
node-embedding
4
feature-engineering
4
random-forest
4
network-embedding
4
graph-embedding
4
machine-learning-algorithms
4