Data science and data modeling are fast emerging as crucial capabilities that every enterprise and every technologist must possess these days. As the process of actually constructing models becomes democratized, the general view is shifting toward using the right data and using the data right. In this course, Representing, Processing, and Preparing Data, you will gain the ability to correctly represent information from your domain as numeric data, and get it into a form where the full capabilities of models can be leveraged. First, you will learn how outliers and missing data can be dealt with in a theoretically sound manner. Next, you will discover how to use spreadsheets, programming languages and relational databases to work with your data. You will see the different types of data that you may deal with in the real world and how you can collect and integrate data to a common destination to eliminate silos. Finally, you will round out the course by working with visualization tools that allow every member of an enterprise to work with data and extract meaningful insights. When you are finished with this course, you will have the skills and knowledge to use the right data sources, cope with data quality issues and choose the right technologies to extract insights from your enterprise data.
Author Name: Janani Ravi
Author Description:
Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing … more

Table of Contents

• Course Overview
  1min
• Understanding Data Cleaning and Preparation Techniques
  22mins
• Preparing Data for Analysis Using Spreadsheets and Python
  39mins
• Collecting Data to Extract Insights
  30mins
• Loading and Processing Data Using Relational Databases
  33mins
• Representing Insights Obtained from Data
  35mins