Intro to Data ScienceUdacity
What you'll learn on the course
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.
- 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
- Create a New Dataframe
- What is Data Wrangling?
- Acquiring Data
- Common Data Formats
- What are Relational Databases?
- Aadhaar Data
- Aadhaar Data and Relational Databases
- Introduction to Databases Schemas
- Data in JSON Format
- How to Access an API efficiently
- Missing Values
- Easy Imputation
- Impute using Linear Regression
- Tip of the Imputation Iceberg
- 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
- 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
- Big Data and MapReduce
- Basics of MapReduce
- MapReduce with Aadhaar Data
- MapReduce with Subway Data