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Data Science Spring 2020 - Section 5

Department of Management Information Systems, Temple University

Data Science

MIS 0855.005 ■ Spring 2020 ■ Sezgin Ayabakan
  • About
    • Syllabus
    • Instructor
    • Course details
    • Course materials
    • Grading
    • Getting Tableau
  • Announcements
  • Schedule
  • Assignments
    • Assignment 1
    • Assignment 2
    • Assignment 3 (Final Project)
    • Extra Credit Assignment
  • In-class Exercises (ICEs)
  • Readings
    • Readings Module 1
    • Readings Module 2
    • Readings Module 3
    • Readings Module 4

About

We are all drowning in data, and so is your future employer. Data pours in from sources as diverse as social media, customer loyalty programs, weather stations, smartphones, and credit card purchases. How can you make sense of it all? Those that can turn raw data into insight will be tomorrow’s decision-makers; those that can solve problems and communicate using data will be tomorrow’s leaders. This course will teach you how to harness the power of data by mastering the ways it is stored, organized, and analyzed to enable better decisions. You will get hands-on experience by solving problems using a variety of powerful, computer-based data tools virtually every organization uses. You will also learn to make more impactful and persuasive presentations by learning the key principles of presenting data visually.

Learning Outcomes

  • Describe how advances in technology enable the field of data science
  • Locate sources of data relevant to their field of study
  • Identify and correct problems with data sets to facilitate analysis
  • Combine data sets from different sources
  • Assess the quality of a data source
  • Convey meaningful insights from a data analysis through visualizations
  • Analyze a data set using pivot tables
  • Determine meaning in textual data using text mining
  • Identify when advanced analytics techniques are appropriate

Course Schedule

Section 001:

  • Day: Tue, Thu
  • Time: 12:30 – 1:50pm
  • Classroom: Alter 607

Pre-requisite: none

 

Primary Sidebar

Instructor

Sezgin Ayabakan, PhD
ayabakan@temple.edu
Office Hours: Tuesdays and Thursdays 3:30 - 4:30pm
Office: Speakman 201B

ITA Info

Section 001
ITA: Taylor Trench
Email: trench@temple.edu
Office Hour: Wednesdays 11:30am - 12:30pm
Office Loc: Speakman 201
Section 005
ITA: Oviya Soundararajan
Email: oviya.soundararajan@temple.edu
Office Hour: Mondays 11:00am - 12:00pm
Office Loc: Speakman 201

RECENT ANNOUNCEMENTS

Exam 3 Info and Study Guide and Review Session

EXAM 3 INFORMATION: This is very important. Do not confuse your Exam 3 … [More...] about Exam 3 Info and Study Guide and Review Session

ICE 13.1 Simple Predictive Analytics

Here are the files you will need: Guideline Dataset Driver … [More...] about ICE 13.1 Simple Predictive Analytics

ICE 12.2 Sentiment Analysis

Here is the guideline: Sentiment Analysis Using Excel Here is the file for … [More...] about ICE 12.2 Sentiment Analysis

ICE 12.1 Manually Determining the Sentiment of Text Data

Here is the ICE details: ICE 12.1 Manually Determining the Sentiment of … [More...] about ICE 12.1 Manually Determining the Sentiment of Text Data

ICE 11.2 Working with Pivot Tables in Tableau

Here is the guideline: ICE 11.2 Working with Pivot Tables in Tableau Here … [More...] about ICE 11.2 Working with Pivot Tables in Tableau

ICE 11.1 Creating a Database

Here is the guideline: ICE 11.1 Creating a Database This is not graded … [More...] about ICE 11.1 Creating a Database

[More Announcements...]

Great Data Sites

  • FiveThirtyEight
  • Philly Open Data
  • Data Gov
  • Guardian Data Blog
  • Flowing Data
  • Financial Times Data Blog
  • Our World in Data
  • Pew Research Data
  • Reddit / Data is Beautiful

COURSE INFO

Section 001
Class Days: T/TH
Class Time: 12:30 - 1:50pm
Location: Alter 607
Section 005
Class Days: T/TH
Class Time: 2 - 3:20pm
Location: Alter 607

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