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Module Title: 
Principles of Data Science
Module Code: 
DSC6131

Module Content

Fundamental principles of data science

Introduction to R/Python (software) for data scientist

Concepts in data exploration and visualization (relationships and causality, reliability and validity, relationships between interval, interval and categorical data with correlation analysis, ...) and basic visualization techniques

Database management systems, and core data mining techniques (association, Classification, Clustering, Prediction, Sequential patterns, Decision trees, ...)

Data collection, cleaning, pre-processing, and storage using various databases;

Numeric and categorical variable analysis and visualization with descriptive statistics

Exploratory data analysis to understand and profile complex data sets; Visual analytics, statistics, and statistical models, causal inference

Supervised and unsupervised modeling, overfitting and its avoidance, evaluation and model analytics

Graph and text data analyzing and visualizing techniques for web and big data

Visualization techniques for interactive quantitative analysis of relationships and information

Reporting the results and presenting the data with visualization techniques

Concepts in machine learning and mining for labeled, unlabelled data to identify relationships, patterns, and trends (predict into the future);

Communicate findings to varied audiences and effective use of data visualizations

Data pipeline

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African Center of Excellence in Data Science(ACE-DS)

Head Office:UR College of Business & Economics

E-mail:   aceds@ur.ac.rw

Phone:(+250) 788484421