Introduction to Database and Data Mining

About Course

Overview

Databases and other collections of data are everywhere. Retailers use data about customers and their purchases to make decisions that increase profits. Researchers analyze data about the human genome to find treatments for diseases. Policymakers analyze socioeconomic data to gain insights that guide their decisions. Online music and video services perform data mining to deliver customized recommendations. How does all this work? CS 105 explores the ways in which collections of data are organized, stored, and analyzed. Topics include relational databases and the SQL query language, the writing of simple programs to process data, data visualization and the graphical display of data, and data-mining techniques for discovering patterns in data. Applications from a variety of domains (including business, the arts, the life sciences, and the social sciences) are used to illustrate the course’s key concepts.

By, Prof. David G. Sullivan, Boston University, Fall 2017

Course Content

Fundementals Facts about Data

Fundemental Facts About Data

06:20

The Relation Model

Keys- Candidate Keys and Primary Keys

Capturing Relationships Using Foreign Keys

Constraints and Null Values

SQL: Simple SELECT Commands

SQL: Pattern Matching; Comparisons Involving NULL

SQL: Removing Duplicates; Aggregate Functions

Subqueries in SQL

SQL: Queries Involving Subgroups

SQL: Data Types; Creating Tables and Inserting Rows

SQL: Cartesian Product; Joins

SQL: Joins Revisited

SQL: Outer Joins

SQL: Other Commands

Getting Started with Python (Using Spyder)

Getting Started with Python (using IDLE)

Python Building Blocks

Python: Built-In Functions and User Input

Python: A First Look at Lists; the range() Function

for Loops in Python

Writing Your Own Functions (Using Spyder)

Writing Your Own Functions (Using IDLE)

Cumulative Computations

Making Decisions: Conditional Execution

Working with Strings and Lists

Using Objects; Splitting and Joining Strings

Accessing a Database from Python

Working with Text Files; File Writing

Reading from a Text File

Data Mining Fundamentals

Evaluating a Model Learned in Data Mining

Classification Learning Using 1R

Classification Learning: Learning a Decision Tree

About Course

Overview

What Will You Learn?

Course Content

Fundementals Facts about Data

Fundemental Facts About Data

The Relation Model

The Relason Model

Keys- Candidate Keys and Primary Keys

Keys- Candidate Keys and Primary Keys

Capturing Relationships Using Foreign Keys

Capturing Relationships Using Foreign Keys

Constraints and Null Values

Constraints and Null Values

SQL: Simple SELECT Commands

SQL: Simple SELECT Commands

SQL: Pattern Matching; Comparisons Involving NULL

SQL: Pattern Matching; Comparisons Involving NULL

SQL: Removing Duplicates; Aggregate Functions

SQL: Removing Duplicates; Aggregate Functions

Subqueries in SQL

Subqueries in SQL

SQL: Queries Involving Subgroups

SQL: Queries Involving Subgroups

SQL: Data Types; Creating Tables and Inserting Rows

SQL: Data Types; Creating Tables and Inserting Rows

SQL: Cartesian Product; Joins

SQL: Cartesian Product; Joins

SQL: Joins Revisited

SQL: Joins Revisited

SQL: Outer Joins

SQL: Outer Joins

SQL: Other Commands

SQL: Other Commands

Getting Started with Python (Using Spyder)

Getting Started with Python (Using Spyder)

Getting Started with Python (using IDLE)

Getting Started with Python (using IDLE)

Python Building Blocks

Python Building Blocks

Python: Built-In Functions and User Input

Python: Built-In Functions and User Input

Python: A First Look at Lists; the range() Function

Python: A First Look at Lists; the range() Function

for Loops in Python

for Loops in Python

Writing Your Own Functions (Using Spyder)

Writing Your Own Functions (Using Spyder)

Writing Your Own Functions (Using IDLE)

Writing Your Own Functions (Using IDLE)

Cumulative Computations

Cumulative Computations

Making Decisions: Conditional Execution

Making Decisions: Conditional Execution

Working with Strings and Lists

Working with Strings and Lists

Using Objects; Splitting and Joining Strings

Using Objects; Splitting and Joining Strings

Accessing a Database from Python

Accessing a Database from Python

Working with Text Files; File Writing

Working with Text Files; File Writing

Reading from a Text File

Reading from a Text File

Data Mining Fundamentals

Data Mining FundamentalsDraft Lesson

Evaluating a Model Learned in Data Mining

Evaluating a Model Learned in Data Mining

Classification Learning Using 1R

Classification Learning Using 1R

Classification Learning: Learning a Decision Tree

Classification Learning: Learning a Decision Tree