For-Data-Science-Beginners

For Data Science Beginners

Set of Notes with links to help those who are Data Science Beginners. Feel free to raise a PR if you need to!

Blogs to Follow:

• Data Science Central
• KDNuggets
• Analytics Vidhya
• Data Science Plus
• R-Bloggers
• What are the best Blogs for Data Scientists to Read - Quora
• Cognitive class
• Simply Statistics
• Edwin Chens blog
• Deepmind Blog
• Dataversity Blog
• Yhat Blog
• Visualization with R
• DataSchool

To Learn:

• ADVICE FOR ASPIRING DATA SCIENTISTS AND OTHER FAQS
• How to get your first job in Data Science? Tomi Mester Medium
• The most comprehensive Data Science learning plan for 2017
• LeaRning Path on R - Step by Step Guide to Learn Data Science on R

• [Python Training

  Python For Data Science

  Learn Python](https://www.analyticsvidhya.com/learning-paths-data-science-business-analytics-business-intelligence-big-data/learning-path-data-science-python/)

• Infographic - Quick Guide to learn Python for Data Science
• Minimalistic Learning Path to Become a Data Scientist
• SQL for Data Analysis (Udacity)
• Recommended Python learning resources - fast.ai
• Here are 450 Ivy League courses you can take online right now for free

Videos:

• Practical Deep Learning Course for Coders

• [Introduction to R for Data Science

  edX](https://www.edx.org/course/introduction-r-data-science-microsoft-dat204x-2)

• [Data Science

  Coursera](https://www.coursera.org/specializations/jhu-data-science)

• Aspiring Data Scientist! Here are 8 free online courses to start

• [Statistics and Data Science

  Stanford](https://www.youtube.com/playlist?list=PLoROMvodv4rO5jY6RA1eFVcLVY2kJU_EL)

Github:

• GitHub - Developer-Y/cs-video-courses: List of Computer Science courses with video lectures.
• GitHub - JanVanRyswyck/awesome-talks: Awesome online talks and screencasts
• GitHub - caesar0301/awesome-public-datasets: A topic-centric list of high-quality open datasets in public domains. By everyone, for everyone!
• GitHub - josephmisiti/awesome-machine-learning: A curated list of awesome Machine Learning frameworks, libraries and software.
• GitHub - ChristosChristofidis/awesome-deep-learning: A curated list of awesome Deep Learning tutorials, projects and communities.
• GitHub - ossu/data-science: Path to a free self-taught education in Data Science!.

Hackathons/Competitions:

• Kaggle: Your Home for Data Science
• DataHack : Biggest Data hackathon platform for Data Scientists
• CrowdANALYTIX:A crowdsourced analytics platform to solve data-driven business problems
• http://www.topcoder.com/active-challenges/data/

Datasets:

• Data worldbank
• Open Government Data (OGD) Platform India
• http://archive.ics.uci.edu/ml/

• [Datasets

  Kaggle](https://www.kaggle.com/datasets)

• [r/datasets

  Reddit](https://www.reddit.com/r/datasets/)

• Data World
• Data Sources - Jo Hardin - Pomona College
• Google Dataset Search
• Gapminder World

Podcasts:

• Artificial Intelligence: AI Podcast - by Lex Fridman
• Partially Derivative
• Data Skeptic
• Linear Digressions
• R-Podcast
• Not so standard deviations
• Dataframed

Libraries:

• Apache Singa
• Amazon Machine Learning
• TensorFlow
• Theano
• Torch

Communities:

• Reddit /r/DataScience
• Reddit r/rstats
• Reddit r/learnmachinelearning

Misc:

• Git for Humans - Alice Bartlett [Video]
• From Data to Viz leads you to the most appropriate graph for your data.

Videos:

• Tetiana Ivanova - How to become a Data Scientist in 6 months a hacker’s approach to career planning
• Beginner guide for Neural Networks and Machine Learning

Newsletter:

• Data Science
• Data Science and R: how do I start?

Math Courses:

• Linear Algebra - Foundations to Frontiers
• Applications of Linear Algebra Part 1

• Applications of Linear Algebra Part 2

• Calculus 1A: Differentiation
• Calculus 1B: Integration
• Calculus 1C: Coordinate Systems & Infinite Series

Statistics Courses:

• Introduction to Probability
• Introduction to Statistics: Probability
• Statistical Reasoning
• Introduction to Statistics: Inference
• Introduction to Statistics: Descriptive Statistics
• MIT OCW Multivariable Calculus

Importance of Portfolio

• My freewheeling conversation on Data Science
• How to Build a Data Science Portfolio

• How to flaunt your Passion for analytics in Data science job interviews?

• The cold start problem: how to build your machine learning portfolio

• Show off your Data Science skills with Kaggle Kernels