This course is Free to Audit and good for understanding more about the ethics behind data science. In this course, you will get to know about the framework to analyze ethical considerations regarding the privacy and control of consumer information and big data. This course will cover the following questions- Who owns data, How do we value privacy, How to receive informed consent, and What it means to be fair.

Every day, thousands of people are moving towards the data science stream because of the allure of the field and great earning opportunities. Some might come from a specialized background, while others simply participate because of interest. To get a data science job you don't particularly need any degrees or certificates, however, having one will increase your chances of getting hired. The first thing you need to have is an appealing portfolio that includes your skills, knowledge, and ability to create solid data science projects. Along with this, you can also add some certificates to show that you have put effort, time, and money to enhance your skills and become a more qualified data scientist.

In this article, I identify extraordinary unmet learner needs and address them with a free offering: my business-oriented machine learning course series, which is designed to fulfill those needs – three vendor-neutral courses that deliver material critical for both techies and business leaders. If you or members of your team would benefit from taking the course series, see how to access it for free here. Your team needs it, your boss demands it, and your career loves it. But today's number-crunching craze tends to, tragically, overlook one key point: Of all the ingredients that are key to success with machine learning, the one that's most often missing isn't about technology or data. Many business leaders do know that machine learning can't succeed in optimizing operations without a proven management process guiding the project – but data scientists tend to focus on one thing and one thing only: hands-on practice with analytics.

My new course series on Coursera, Machine Learning for Everyone (free access), is for any learner who wishes to participate in the business deployment of machine learning, no matter whether you'll play a role on the business side or the technical side. This end-to-end, three-course series is accessible to business-level learners and yet vital to techies as well. It covers both the state-of-the-art techniques and the business-side best practices. Among machine learning courses, the three in this series are somewhat unusual. They're not hands-on, and yet they do delve into the machine learning algorithms themselves, as well as other technical topics.

This repository contains my personal notes and summaries on DeepLearning.ai I've enjoyed every little bit of the course hope you enjoy my notes too. This is by far the best course series on deep learning that I've taken. If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech.