ISOM352/ISOM599:
Applied Data Analytics with Coding

Computer systems

Database systems (mySQL)

ER Model

Data warehousing

Data Definition Language

Data Modification Language

SQL in mySQL

SQL in Excel

SQL in Python

Take home (due in 48 hours)

Class time used to discuss FAQs for first half of course and mid-term

Coding basics

Python basics I (IDE, variables, data types, console I/O)

Python basics II (conditions, loops, lists, strings, dictionaries, files - csv, json, excel)

Data Frames

Import/Export

Functions

Aggregation Functions

Data Slicing

Missing Data

Combining Data

Data visualization in Python (low level) - matplotlib

Data visualization in Python (high level) - seaborn

Data visualization in Python (high level and interactive) - plotly

text mining - nltk

statistical models - statmodels

machine learning - sklearn (clustering, classification)

10-15 minute group presentation of insights extracted from data using SQL and/or Python

Datasets from Kaggle or an online channel will be selected and provided