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Data Science for Beginners

Created by Ermin Dedic, Last Updated 19-Jan-2021, Language:English

Data Science for Beginners

A data science intro course. Data Science concepts, methodology, illustration of machine learning via chatbot, and more!

Created by Ermin Dedic, Last Updated 19-Jan-2021, Language:English

What Will I Get ?

  • Explanation of key concepts in data science: big data, data mining, libraries, datasets, API's
  • Programming languages and which ones to learn
  • Data Science Methodology, expressed via Healthcare Insurance Company Case Study
  • Experience The Power of Machine Learning and Natural Language Processing via Chatbot Example
  • GitHub; how to use it for collaboration and version control.

Requirements

  • A computer installed with Windows/Linux /OS X.
  • Minimum of 8GB RAM
  • Internet connection
  • No programming or data science experience required. This is for total beginners.

Description

Welcome! If you see Data Science as a potential career in your future, this is the perfect course to get started with.

Our course does not require any previous Data Science experience. The goal of 'Data Science for Beginners' is to get you acquainted with Data Science methodology, data science concepts, programming languages, give you a peek into how machine learning works, and finally show you a data science tool like GitHub, which lets you collaborate with your colleagues.

Now, while this is a beginner course,  it does not mean that it is an easy course. For example in the Data Science methodology section, many different concepts are introduced. But please keep in mind that a. you will get concrete examples of what each concept means when it is brought up. b. most importantly, you are not meant to understand all the concepts fully. 

Beyond this, you will get to build a simple chatbot. This hands-on activity will illustrate in a more interactive way how machine learning works and how you can provide a machine learning service such as this in your future career.

Course Content

Ermin Dedic

All Things Data.

I have a passion for anything data, whether it is applying statistical methods to data more generally, or utilizing a data-driven approach in the Healthcare or Finance/Banking industries.

I studied Psychology for 6-years, including 2 years of Graduate school, where I was training to be a Child/School Psychologist. I had an opportunity to experience a blend of course work and clinical work but also recognize some of the problems facing the mental health system and graduate school system. 

While I did ultimately decide to voluntarily leave the Grad program, it is via academics that I fell in love with statistics and statistical software like SPSS/SAS.

It was my Graduate school experience that solidified my interest in teaching, and where I received a lot of great feedback on my teaching and teaching style.