Here are my favorite Data Science/Data Analytics Resources
Curriculum
1) MIT Open Courseware
A great MOOC (Massive Online Open Courses) to learn about the math and statistical fundamentals of Data Science, such as linear algebra, statistics, probability, etc. From a
great university. This will give you some of the fundamentals of data science. https://ocw.mit.edu
A website that sets up data analytics and data science competitions. It also provides a lot of free data that you can play build your skills on.
3) https://Datasciencemasters.org
A open-source curriculum for learning Data Science. Including foundation in theory and technologies. You can download code and use it to build
project to improve your skills.
4) https://superdatascience.com/pages/machine-learning
I really like like this website, because it teaches you all the fundamentals of machine learning from A to Z.
5) https://Coursera.org
A MOOC (Massive Online Open Courses) that can teach you anything you need to know about Data Science and Machine Learning and Data analytics
Another good MOOC
7) https://EdX.org
Another good MOOC
8) Standford Online (https://online.stanford.edu/)
A lot like MIT Open Courseware. Free and from a renowned university.
Programming
This is my favorite Data Science/Data Analytics platform. Python is very hot right now in regards to Data Science. Anaconda is the best platform to learn and program in Python.
Strongly recommend learning Python and/or R. It looks like you’ve learned SQL, which is the other popular language.
5) Sci-kit Learn (https://scikit-learn.org)
This is my favorite library for data science and deep learning. A lot of great features for classification and anomaly detect and other stuff.
Github is a community source repository for Python, C++, C#, Java, and Javascript. You should create your own GitHub account and start being active on it. There are a lot of tutorials.
You can learn almost any coding language here. C++/Python
There are a lot of good books from Amazon to learn Python.
Datasets
My Favorite Publicly Available Datasets (also see https://rtpopendata.com/2019/02/03/my-favorite-publicly-available-datasets/)
I’ve been working with data for decades, searching for insights, converting it, managing it, and now performing data analytics. We have access to unbelievable treasure troves of public data to analyze. Many of the blogs I write are based on these datasets, as I don’t have access to large computing systems. Here is a list of my favorite publicly available datasets. Enjoy!
PJM Interconnection Data Dictionary for electrical grids, distribution and transmission. https://www.pjm.com/markets-and-operations/data-dictionary.aspx
University of California Irvin (UCI) has a huge machine learning repository to practice techniques. This repository can be accessed at archive.ics.uci.edu/ml/index.php
Amazon Web Services datasets are available to the public. https://aws.amazon.com/datasets/.
Kaggle is a data science competition website that rewards prizes to teams for the best ML models. Datasets are located at https://www.kaggle.com/datasets
University of Michigan Sentiment Data.
The time series data repositories are located at https://fred.stlouisfed.org/categories.
Canadian Institute of Cyber Security. https://www.unb.ca/cic/datasets/nsl.html.
Datasets for “The Elements of Statistical Learning”. https://web.stanford.edu/~hastie/ElemStatLearn/.
Government Open Data Portal. https://data.gov
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