Information Package

Master's of Technology and Knowledge Management with Thesis

TKM521

DATA ANALYTICS

Course Code
TKM521
Semester
-
Theory+Practice
3 + 0
ECTS
10
Course TypeElective Course
Course LevelMaster's Degree With Thesis
Year of Study-
Semester-
ECTS10
Name of Lecturer(s)
Learning Outcomes

At the end of this course, the students;

  1. Know a wide range of data analytics techniques (descriptive analytics, inferential analytics, and predictive analytics).
  2. Master different data analysis problems encountered in applications with heavy data use.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsData Science
Course DescriptionData Analytics is the science of analyzing data to convert information to useful knowledge. This knowledge could help us to make better decisions. This course aims to present you with a wide range of data analytic techniques (descriptive, inferential, predictive, and prescriptive analytics).
Course Contents
WEEK TOPICS
1st Week Basic Definitions: Data, Information, Value of Data, Data Analysis
2nd Week Inferential Data Analysis
3rd Week Descriptive Data Analysis
4th Week Survival Analysis
5th Week Social Network Data Analysis
6th Week Data Analysis Processes
7th Week Data Analysis Processes
8th Week Mid-term Examination
9th Week Ethical and Legal Issues
10th Week Social Network Modeling
11th Week Terabyte Scaled Image Analysis Applications
12th Week Big Data Analysis Between Web Sites
13th Week Case Study Presentations
14th Week Case Study Presentations
Recommended or Required ReadingInferential Data Analysis: Hypothesis Testing and Decision-Making, Tyrone Pretorius.
Descriptive Data Analysis and Statistics. Klaus Krickeberg, Van Trong PhamThi My Hanh Pham, Springer.
Planned Learning Activities and Teaching Methods
  • Lecture
  • Discussion
  • Problem Solving
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 25
Assignment 3 30
Total(%) 55
Contribution of In-term Studies to Overall Grade(%) 55
Contribution of Final Examination to Overall Grade(%) 45
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 3 3
Preparation for Quiz
Individual or group work 14 7 98
Preparation for Final exam 1 50 50
Course hours 14 3 42
Preparation for Midterm exam 1 45 45
Laboratory (including preparation)
Final exam 1 3 3
Homework 3 15 45
Total Work Load286
Total Work Load / 30 (h)9.53
ECTS Credit of the Course10
Language of InstructionTurkish
Work Placement(s)No
LO1 LO2
K1 X
K2 X
K3 X X
K4 X
K5 X X
K6 X
K7 X
K8 X X
K9 X
K10 X
K11 X
K12 X
K13 X