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# Intro to Data Science

via Udacity

## Overview

The Introduction to Data Science class will survey the foundational topics in data science, namely:

• Data Manipulation
• Data Analysis with Statistics and Machine Learning
• Data Communication with Information Visualization
• Data at Scale -- Working with Big Data

The class will focus on breadth and present the topics briefly instead of focusing on a single topic in depth. This will give you the opportunity to sample and apply the basic techniques of data science.

This course is also a part of our Data Analyst Nanodegree.

Why Take This Course?

You will have an opportunity to work through a data science project end to end, from analyzing a dataset to visualizing and communicating your data analysis.

Through working on the class project, you will be exposed to and understand the skills that are needed to become a data scientist yourself.

## Syllabus

### Lesson 1: Introduction to Data Science

• Introduction to Data Science
• What is a Data Scientist
• Pi-Chaun (Data Scientist @ Google): What is Data Science?
• Gabor (Data Scientist @ Twitter): What is Data Science?
• Problems Solved by Data Science
• Pandas
• Dataframes
• Create a New Dataframe

### Lesson 2: Data Wrangling

• What is Data Wrangling?
• Acquiring Data
• Common Data Formats
• What are Relational Databases?
• Aadhaar Data and Relational Databases
• Introduction to Databases Schemas
• API’s
• Data in JSON Format
• How to Access an API efficiently
• Missing Values
• Easy Imputation
• Impute using Linear Regression
• Tip of the Imputation Iceberg

### Lesson 3: Data Analysis

• Statistical Rigor
• Kurt (Data Scientist @ Twitter) - Why is Stats Useful?
• Introduction to Normal Distribution
• T Test
• Welch T Test
• Non-Parametric Tests
• Non-Normal Data
• Stats vs. Machine Learning
• Different Types of Machine Learning
• Prediction with Regression
• Cost Function
• How to Minimize Cost Function
• Coefficients of Determination

### Lesson 4: Data Visualization

• Effective Information Visualization
• Napoleon's March on Russia
• Don (Principal Data Scientist @ AT&T): Communicating Findings
• Rishiraj (Principal Data Scientist @ AT&T): Communicating Findings Well
• Visual Encodings
• Perception of Visual Cues
• Plotting in Python
• Data Scales
• Visualizing Time Series Data

### Lesson 5: MapReduce

• Big Data and MapReduce
• Basics of MapReduce
• Mapper
• Reducer
• MapReduce with Subway Data

Dave Holtz

## Reviews

4.2 rating, based on 13 reviews

Start your review of Intro to Data Science

• Life is Study
1023

Life is Study completed this course.

Intro to data science is an intermediate level course that assumes basic Python programming skills and knowledge of statistics. The course focuses on gathering, manipulating, analyzing and visualizing data using Python and various Python packages such...
• Lukas Tencer completed this course and found the course difficulty to be medium.

It brings introduction in many areas, but it does not go into depth to any area. For more advanced classes look for other courses on Udacity. Good as introduction.
• Joe Foley is taking this course right now, spending 8 hours a week on it and found the course difficulty to be medium.

I was skeptical when I enrolled in UDACITY's Data Analysis Nano Degree Program but not only have they provided the experience they said they would they have steadily made improvements since I enrolled. How many times in your life have you had that...
• Shahrukh Ahmed completed this course, spending 5 hours a week on it and found the course difficulty to be easy.

Though the course uses interesting examples for teaching concepts in relation to data science, the over reliance of the online grader for practice often makes learning redundant. Big part of learning programming is experimentation which the grader does not allow for.
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