How can I become a data scientist?

This needs a considerable amount of thought. Presently almost all programs being offered by universities are post graduate (Master’s) level or certificate courses which presume prerequisites such as fundamentals of computer science, network engineering, programming, and mathematics. ‘Data Science’ is generally considered to be a combination of the following disciplines: 1. Computer Science 2. Statistics … Continue reading How can I become a data scientist?

4 Problems – Cognitive Biases

This is a gist of an interesting article on some of the problems which are an outcome of a certain cognitive bias [Source: https://betterhumans.coach.me/cognitive-bias-cheat-sheet-55a472476b18#.nk7k8geaa] Four problems that biases help us address: Information overload, lack of meaning, the need to act fast, and how to know what needs to be remembered for later. Problem 1: Too much information. … Continue reading 4 Problems – Cognitive Biases

Great Advice for Data Scientists by Director of Data Science at LinkedIn

Yael Garten, Director of Data Science at LinkedIn, shared the following list of behaviors and qualities that distinguishes exceptional data scientists from the average performers. 1. Request context and envision the answer before you start the work. Average data scientists do what they’re asked and begin building prematurely when often the real question to answer or data product to build is still not understood. … Continue reading Great Advice for Data Scientists by Director of Data Science at LinkedIn

4 Kinds of Survey Error: Sampling, Measurement, Coverage and Non-Response

1. Sampling Error.   Sampling error is essentially the degree to which a survey statistic differs from its “true” value due to the fact that the survey was conducted among only one of many possible survey samples.  It is a degree of uncertainty that we are willing to live with.  Even most non-researchers have a … Continue reading 4 Kinds of Survey Error: Sampling, Measurement, Coverage and Non-Response

Business Intelligence vs Business Analysis vs Machine Learning

Imagine that you are running a fruit store. You start by hiring someone to keep track of the stock level, profit and loss, top-selling fruits, and churn out reports. That’s Business Intelligence (BI), where you care about an accurate account of what happened and what’s going on in your business. You then hire someone to take a look at the reports and work … Continue reading Business Intelligence vs Business Analysis vs Machine Learning