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Data Analytics is an ever-growing field with untapped opportunity for researchers. Here are some of the data analysis skills I have learned along with their sources.

Google Data Analytics Certification - Grow with Google

Data analysts prepare, process, and analyze data to help inform business decisions. They create visualizations to share their findings with stakeholders and provide recommendations driven by data. In this program, I was introduced to the world of data analytics through hands-on curriculum developed by Google. I developed in-demand data analytics skills using spreadsheets, SQL, Tableau, R, and more. See project here. 

Introduction to Deep Learning & Neural Networks with Keras - IBM

This foundational course was a great opportunity to learn the very basics of Deep Learning, using Keras in particular. What was best in thid course was that I learned all the more "under the hood" aspects of DL and NN, but also had the chance to complete a capstone project where I programmed a simple NN on my own. See project here

Foundational SQL - Datacamp

To be an effective data scientist, one must know how to wrangle and extract data from databases using a language called SQL . This course taught. me syntax in SQL shared by many types of databases, such as PostgreSQL, MySQL, SQL Server, and Oracle. 

Python Programming for Everybody - University of Michigan

To be an effective data scientist, one must know how to wrangle and extract data from databases using a language called SQL . This course taught. me syntax in SQL shared by many types of databases, such as PostgreSQL, MySQL, SQL Server, and Oracle. 

AI for everyone - DeepLearning.AI

AI is not only for engineers! “AI for Everyone” was a course that helped me understand AI technologies and spot opportunities to apply AI to problems in my professional career. 

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