Master Data Science: Top Courses By edX

As patients, we care about the privacy of our medical record; but as patients, we also wish to benefit from the analysis of data in medical records. As citizens, we want a fair trial before being punished for a crime; but as citizens, we want to stop terrorists before they attack us. As decisionmakers, we value the advice we get from data-driven algorithms; but as decisionmakers, we also worry about unintended bias. Many data scientists learn the tools of the trade and get down to work right away, without appreciating the possible consequences of their work.

This course focused on ethics specifically related to data science will provide you with the framework to analyze these concerns. This framework is based on ethics, which are shared values that help differentiate right from wrong. Ethics are not law, but they are usually the basis for laws.

What you'll learn

Who owns data
How we value different aspects of privacy
How we get informed consent
What it means to be fair

Programming for Data Science University of Adelaide Logo

There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognized credential in this highly competitive area.

Using practical activities and our innovative ProcessingJS Workspace application you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

You will learn algorithm design as well as fundamental programming concepts such as data selection, iteration, and functional decomposition, data abstraction, and organization. In addition to this, you will learn how to perform simple data visualizations using ProcessingJS and embed your learning using problem-based assignments.

This course will test your knowledge and skills in solving smallscale data science problems working with real-world datasets and develop your understanding of big data in the world around you.

What you'll learn

How to analyze data and perform simple data visualizations using ProcessingJS
Understand and apply introductory programming concepts such as sequencing, iteration, and selection
Equip you to study computer science or other programming languages

Data Science: Productivity Tools Provided by Harvard University (HarvardX)

What You Will Learn

How to use Unix/Linux to manage your file system
How to perform version control with git
How to start a repository on GitHub
How to leverage the many useful features provided by RStudio

Data Science Research Methods: R Edition Provided by Microsoft

What You Will Learn

After completing this course, you will be familiar with the following concepts and techniques:
Data analysis and inference
Data science research design
Experimental data analysis and modeling

Before You Start

Prerequisites

To complete this course successfully, you should have:
Basic knowledge of math
Some programming experience R is preferred.
A willingness to learn through self-paced study.

Course Format

self-paced: course contains assignments without due dates. You can progress through the course at your own speed.

The course ends: Apr 1, 2019

Introduction to Python for Data Science Microsoft Logo

This course is part of the Microsoft Professional Program Certificate in Data Science and Microsoft Professional Program in Artificial Intelligence.

Python is a very powerful programming language used for many different applications. Over time, the huge community around this open source language has created quite a few tools to effectively work with Python. In recent years, a number of tools have been built specifically for data science. As a result, analyzing data with Python has never been easier.

In this practical course, you will start from the very beginning, with basic arithmetic and variables, and learn how to handle data structures, such as Python lists, Numpy arrays, and Pandas DataFrames. Along the way, you�??ll learn about Python functions and control flow. Plus, you�??ll look at the world of data visualizations with Python and create your own stunning visualizations based on real data.

What you'll learn

Explore Python language fundamentals, including basic syntax, variables, and types
Create and manipulate regular Python lists
Use functions and import packages
Build Numpy arrays, and perform interesting calculations
Create and customize plots on real data
Supercharge your scripts with control flow, and get to know the Pandas DataFrame

Source: HOB

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