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7-optimizing-queries/README.md
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7-optimizing-queries/README.md
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## Optimizing Queries and Data Comparisons
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This challenge will take what we already know about SQL and Python and add the necessary tools to optimize how we make queries and compare data.
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#### Setup
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In create_db.py, initialize and create a new database "schedules.db" and give it the necessary tables to hold the following:
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Students have a name, and a major.
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Classes have a title, and a field of study.
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Major and field of study are the same, ie. Economics is a major and a field of study.
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Students have many classes.
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Classes have many students.
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Write a seed_db() function that takes the existing data in create db and randomly fills the database with it.
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#### Query
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Write a function shared_classes() in Python that takes two student names. It should return the classes they take together, if any. How you want to do this is open ended.
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What is the Big O time complexity of your algorithm for loading the students and comparing their classes? Write it down, and benchmark your code.
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#### First Optimization - the Index
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Read [how indexes work](http://www.programmerinterview.com/index.php/database-sql/what-is-an-index/) here. What type of data structure does sqlite3 use to hold indexes?
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Now, add an index to one or more of your tables on columns you think would be appropriate.
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Benchmark again - what is your speed now?
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#### Second Optimization - use a Set
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Are you comparing the data returned from the DB in Python? If so, you probably aren't using the right data type. We haven't covered Sets yet - read about them [here](https://docs.python.org/3.4/library/stdtypes.html#set)
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A set is very similar to a dictionary, only it does not store values. Only keys. The syntax is like so:
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```
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{'Programming', 'Calculus', 'Literature'}
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```
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Use sets to store the returned class data about both students and use set's built in methods to find the intersection if it exists.
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The Big O complexity of this operation is `O(len(x) * len(y))`. If you did the most simple comparison with arrays, it was probably `O(len(x) * len(y)**2)`.
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Read about sets. Why is this? Here's a [list](https://wiki.python.org/moin/TimeComplexity) of all Python datatype method's time complexity.
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#### Third Optimization - a better (longer!) Query
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Instead of doing all your comparisons on the Python side, can we pull the information straight out of the database with a more advanced query?
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Before you write the query to replace your original answers- let's write a new function that takes a Major and number of students, and returns classes where that number of students or more in that class have that major.
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Now, write your enhanced query to find the intersect without any Python data parsing.
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Benchmark this function against your first two.
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Sandbox!! You will want to get familiar with the following SQL commands: GROUP BY, HAVING, IN.
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124
7-optimizing-queries/classes.py
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7-optimizing-queries/classes.py
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def classes():
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return ['Pharmacology for AT',
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'Human Nutrition',
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'Comp Networks & Security',
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'Principles of Counseling',
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'Intro to Human Com',
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'Mass Comm',
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'Public Relations',
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'Com Relations in Orgs',
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'Survey of Com Research',
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'Technology and Society',
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'Intro Comps & Office',
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'Intro to Microsoft Excel',
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'Intro to Microsoft Acces',
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'Computer Science II',
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'Computer Science II Lab',
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'Logic for Comp Scientist',
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'Comp NW Culture: Music',
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'Comp NW Social Systems',
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'Economic Life',
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'Principle Microeconomics',
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'The Global Economy',
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'Exceptionalities',
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'Continuation Prep Math',
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'Internship I',
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'Engineering Fundamentals',
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'Acad. Writing & Reading',
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'Research Writing',
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'Business Writing',
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'British Texts',
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'Post-Colonial Texts',
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'Technical Writing',
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'Intro to Poetry Writing',
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'Intro to Food Science',
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'Farm Business Management',
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'Food Plant San and HACCP',
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'Food Microbiology',
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'Food Chem and Analysis',
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'Food Laws and Regulation',
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'West. Civ. to 1500',
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'West & World since 1500',
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'Tech Based Ventures',
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'I&E Seminar Series',
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'Illustration',
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'E-Commerce Advertising',
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'Psychology of Sport',
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'Human Resources Mgt',
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'Internship in IS',
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'Principles of Marketing',
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'Music Listening',
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'Music in Western Culture',
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'Patho Across Lifespan',
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'Found of Research & EBP',
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'Transition Role Prof Nur',
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'Nur Role for Unlicensed',
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'Nursing',
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'Ldrship & Mngmt',
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'Colab Impv Pat Hlth Outc',
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'Honors Project Seminar',
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'Professional Devel II',
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'Professional Devel IV',
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'Integ Office Software',
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'Admin Office Management',
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'Self as Leader',
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'Leading Change',
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'Political Life',
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'International Politics',
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'Cyber Crime',
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'Topics Criminal Justice',
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'Intro to Psychology Lab',
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'Psych of Disabilities',
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'Childhood & Adolescence',
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'Psychology Men and Women',
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'Forensic Psychology',
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'Honors Pharmacology Res',
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'Drug & Alcohol Abuse',
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'Rehab Internship',
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'Educational Interpreting',
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'SLI Senior Capstone',
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'Intro to Sociology',
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'Grow/Change Urb Society',
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'Womens Studies',
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'Ethics in Engineering',
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'Adv Ergon',
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'Lean Proc Impr Engr',
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'Comp Networks & Security Lab',
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'Host Computer Security',
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'Information Security',
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'Adv. Comp. Networks',
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'CNL Theory and Practice',
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'Techniques of Counseling',
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'Stats Res for Counseling',
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'Group Background &Theory',
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'Asses & Eval in Counsel',
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'Marriage',
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'Coun Life-Span Develop',
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'Pro Orient Eth & Leg Iss',
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'Multicultural Counseling',
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'Prin & Prac of Schl Coun',
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'Human Sexuality Counsel',
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'Clin Assess in Cnl Prac',
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'Diagnosis Clin Cnl Prac',
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'Comp Sys & Structures',
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'Functional & Logic Prog.',
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'Information Retrieval',
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'Eco Applica Internet II',
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'Read & Lit II: Int Spec',
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'Teach in the Amer Ed Sys',
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'Action Research: Science',
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'Diagnosis and Assessment',
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'Pract I: Intervention',
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'Literacy Inquiry Project',
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'Ldrshp Schl Improvement',
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'Analysis of Teaching',
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'Tchr Ldr Masters Exit',
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'Data Driven Decisions',
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'Advanced Ed Measurement',
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'Bldg-Level Leadership',
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'Bldg Budget',
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'Principal Practicum',
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'Adv Tchr Ldr Seminar',
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'Pol & Soc Contexts',
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'Organizational Behavior',
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'Superintendent Practicum']
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11
7-optimizing-queries/create_db.py
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7-optimizing-queries/create_db.py
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import sqlite3
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import classes
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import majors
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import random
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from faker import Faker
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def create():
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pass
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def seed():
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pass
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7-optimizing-queries/intersect.py
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7-optimizing-queries/intersect.py
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7-optimizing-queries/majors.py
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7-optimizing-queries/majors.py
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def majors():
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return ['Biology',
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'Chemistry',
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'Mathematics',
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'Political Science',
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'Psychology',
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'Social Sciences',
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'Social Work',
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'Sociology',
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'Speech Pathology',
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'Accounting',
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'Finance' ,
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'Management',
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'Management Information Systems',
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'Marketing',
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'Family & Consumer Sciences',
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'Child & Family Studies',
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'Dietetics',
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'Retail Merchandising',
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'Art',
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'Ceramics',
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'Drawing',
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'Graphic Design',
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'Painting',
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'Photography',
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'Printmaking',
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'Sculpture',
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'New Media',
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'Mass Communication',
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'Music',
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'Composition',
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'Instrumental Performance',
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'Organ Performance',
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'Piano Pedagogy',
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'Piano Performance',
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'Vocal Performance',
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'Theatre',
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'Acting',
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'Directing',
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'Design and Technology',
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'Musical Theater']
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