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Masters

Practicum Human Computation and Analytics

University of Munich
Munich , Germany
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Tuition Fee
Not Available
Start Date
Not Available
Medium of studying
On campus
Duration
12 weeks
Details
About Program
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Details
Program Details
Degree
Masters
Major
Artificial Intelligence | Data Science | Software Engineering
Area of study
Information and Communication Technologies | Mathematics and Statistics
Education type
On campus
Timing
Full time
Course Language
English
About Program

Program Overview

Practicum "Human Computation and Analytics"

Overview

The practicum "Human Computation and Analytics" aims to apply techniques learned from the lectures and exercises of the course "Human Computation and Analytics". Students will solve problems currently faced in industry and/or research in programming projects, focusing on "Human Computation" and "Visual Analytics".


Organisation

  • Module: This practicum is part of the module "Human Computation and Analytics", restricted to students enrolled in the master degree program Data Science.
  • Type: Master Practicum
  • Time: 2 hours weekly
  • Instructors: Prof. Dr. Andreas Butz, Prof. Dr. François Bry, Yingding Wang
  • Time and Location: Wednesday, 10:00 to 12:00 c.t., Room M 201 (Geschwister-Scholl-Platz 1 (M))
  • Start: 26.04.2017 - 26.07.2017
  • Requirements: Attendees must bring their laptops.

Registration

  • Registration: Mandatory within the UniWorX-System
  • Start: Tuesday, 01.04.2017, 0 a.m.
  • End: Thursday, 26.04.2017, 10 p.m.

Topics

Topic 1: Sentiment Analysis

  • Project Contact: Florian Lachner
  • Data: Facebook Posts RawData
  • Description: Analyze and visualize the focus of UX-related Facebook posts from Amazon US and Amazon India to draw conclusions on similarities and differences between the two countries' posts.

Topic 2: Mental Stress

  • Project Contact: Yingding Wang
  • Data: Fitness wristbands can be borrowed, and participants' own heart rate data can be collected.
  • Description: Integrate Google Calendar with stress measurement to allow fine-grained filtering of heart rate patterns based on activity labels, improving mental stress detection.

Topic 3: Parkinson's Disease

  • Project Contact: Yingding Wang and Dr. Franz M. J. Pfister
  • Data: Patients' video data will be provided by Dr. Franz M. J. Pfister.
  • Description: Develop a web-based HCA platform for distributed labeling of video data by Parkinson's Disease experts, analyzing the quality and reliability of expert opinions.

Exam

  • Attendance: Mandatory, with unexcused absences potentially resulting in disqualification from the final examination.
  • Final Examination:
    • A live demo and presentation of the project outcomes.
    • A written final team report covering all relevant aspects of HCA and the tasks defined in the last 3 lab sessions.
  • Final Presentation Details:
    • Dates: 26.July, 10-12
    • Duration: 20 minutes
  • Team Final Report:
    • Each team submits a single final report.
    • The report elaborates on all relevant aspects of HCA and the tasks defined in the last 3 lab sessions, highlighting individual contributions.

Schedule

Practicum Schedule

Date Topic Slides
1. Introduction (Organisational Matters, Topics, Team Building, Tools) Organisation and Topics, Infrastructure and Technologies, Topic Description of Sentiment Analysis
2. Building Web Clients Tasks of Team Presentation 1
3. Server Framework and Data Storage
4. Team Presentation 1 Team SemAntica, A Team, Team Wind++
5. Preprocessing and Displaying Data with Python3
6. Data Analysis with Python3
7. Visualizing processed data of HCA Systems
8. Team Presentation 2 Tasks of Team Presentation 2
9. Advertising system and solving cold start
10. Team Practices
11. Team Practices
12. Team Practices
13. Team Practices
14. Team Presentation 3 (Live Demo, Final Presentation of the project) Tasks of final Presentation & four deadlines
Submission deadline of team reports and program codes of the projects (No extension)

Online Sources

JavaScript

  • d3js Gallery
  • highcharts demos
  • Chart.js
  • JavaScript Introduction

TypeScript and Angular2

  • TypeScript
  • TypeScript: Quick start
  • Angular2: Quick start
  • Angular2 Git Repo 2.4.x
  • Angular2 Tutorial: Tour of heroes
  • Angular2 highcharts
  • D3 Version 4 Typescript Definition Files
  • D3 with Angular2
  • Tutorial: creating a chart with d3 and typescript part 1
  • Tutorial: creating a chart with d3 and typescript part 2

Java and Play Framework

  • Play 2.5.x documentation
  • Play-jongo git repo
  • Jongo docs

MongoDB

  • Installation Guidance of MongoDB Community Edition
  • MongoDB Manual
  • SQL to MongoDB Mapping Chart

Python3

  • Plotly (Data Visualisation Tool)
  • Plotly for Python3
  • Pymongo 3.4.0
  • scikit-learn
  • TensorFlow
  • Matplotlib for Plotting in Python3

Mobile and Voice Clients

  • Building Your First Android App
  • Voice Client with Alexa

Additional References

  • The Data Visualisation Catalogue (Plot Examples)
  • Human Computation Projects conducted by Luis von Ahn
  • HCA (Lecture + Exercise)

Software and Examples

Supplementary Materials

Templates

  • Presentation template: LaTeX Beamer Slides
  • Presentation template theme: LaTeX Beamer Theme
  • Report template: Springer - Lecture Notes in Computer Science (LNCS)
  • Report template documentation: Springer - Lecture Notes in Computer Science (LNCS)
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