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3621434 Short Introduction to Algorithmic Data Analysis, 3 Cp 
Code 3621434  Validity 01.01.1950 -
Name Short Introduction to Algorithmic Data Analysis  Abbreviation LJAD 
Credits3 Cp  Date of expiry  
TypeIntermediate Studies Subject0530 Computer Science 
ClassStudy Unit  Hours  
Study right   Grading0-5 
Recommended scheduling 
   
Organisation Computer Science (J,K) 

Description
Learning outcomes 

Student understands: what kind of problems can be solved using algorithmic data analysis; principles and prerequisites of the most common data analysis methods; prerequisites and goals of data mining and machine learning; the workflow of algorithmic data analysis

Student knows how to choose the correct approach (descriptive vs. predictive) and to choose the correct method from the most common ones. Student can use the common data analysis methods, and knows how to analyse the results.

 
Content 

Different phases of data analysis. Basic concepts in descriptive and predictive data analysis. Basics of mining of association rules and frequent itemsets. Most important clustering algorithms. Basics of graph analysis. Decision trees and naïve Bayes classifier. Detecting and analysing anomalies. Privacy and fairness in data-analysis.      

 
Modes of study 

Lectures 20 h, exam 4 h, exercise sessions 10 h, independent study 54 h. The course can also be completed by taking a literature exam on the general exam day on following literature: Tan, Steinbach, Karpatne & Kumar: Introduction to Data Mining 2nd ed. Pearson Education, Harlow, 2020, chapters 1–6.4, 9, and 10.

 
Teaching methods 

classroom teaching, studying online, exercise sessions

 
Study materials 

Exam books, supplementary materials, materials handed out during contact teaching.                

 
Evaluation criteria 

In total 40 % of the weekly assignments must be marked completed with compulsory attendance for the marked assignments; further marked assignments provide extra points for the exam (max. 10 points, extra points require that the exam is passed). Exam 0–5.

 
Prerequisites 

Introductory course in statistics (or similar skills

 
Time 

The 2nd or 3rd year spring of BSc studies

 
Offering data 

This course is only intended for minor subject students

 
Further information 

This course will be taught in Finnish

 


Letter (J, K) in front of the name of the course/exam indicates the campus on which teaching or exam takes place: J = Joensuu, K = Kuopio.

Present and future teaching
Functions Name Type Cp Teacher Timetable
Registration not started (KUOPIO): Short Introduction to Algorithmic Data Analysis  Lecture and exercise course  Pauli Miettinen  21.03.22 -21.06.22
Registration not started (JOENSUU): Short Introduction to Algorithmic Data Analysis  Lecture and exercise course  Pauli Miettinen  21.03.22 -21.06.22

Future exams
No exams