Page 51 - SH 2561 INTER

38 | P a g e

DGE-206 Numerical Methods and Discrete Mathematics 3(3-0-6)
Prerequisite : DGE-105 Calculus 1 and DGE-106 Calculus 2
Corequisite : No
Matrix operations, linear algebra, LU degradation, curve modulation, roots of numeric
equations, numerical classification, numerical integration through Runge-Kutta methods for solving
initial conditions of ordinary differential equations, tree connections, dislocation of approximation,
soling linear and non-linear equations, function approximation, derivative approximation and
numerical integration, using of software for numerical computation.

DGE-207 Probability and Statistics for Digital Engineers 3(3-0-6)
Prerequisite : No
Corequisite : No
Basic analysis and presentation of data, probability, statistical classification, sampling,
approximation, statistic inference and hypothesis testing, correlation variance analysis and regression, the
use of statistics in problem solving, statistics methodology, attributes of data, continuous analysis, random
variables, distribution of the probability, distribute of samples, hypothesis testing theory, model Markov, the
analysis of linear regression in engineering, sample approximation and model creation, distribution
sampling.

DGE-208 Artificial Intelligence Techniques 2 : Hardware-Based Approaches 3(2-3-6)
Prerequisite : DGE-201 Digital Signal Processing and DGE-203 Wired and Wireless Communication System
Corequisite : No
Integrated design for software and hardware embedded system. Microcontroller application
development using C, C++, Python, Arduino and MATLAB. Microcontroller bus system for
network communication. Device and service control. Unified Model Language (UML) program.
Real-time embedded system under tight constraints development. Commercial consideration.
Specific application processor. Rapid hardware and software prototype. Design license

DGE-209 Data Analytics 3(2-3-6)
Prerequisite : DGE-202 Artificial Intelligence Techniques 1 : Software-Based Approaches and
DGE-206 Numerical Methods and Discrete Mathematics
Corequisite : No
Data model and database architecture. Conceptual data definition for database relationship design.
Normalization. Database theory. Relational language for database. Database application case study. Data collection and
presentation. Industrial data analysis. Linear distribution analysis. Single factor-none parameter analysis. Application for
design, analysis and interpret data. Data mining. Data warehouse. Statistic for data mining. Database acknowledgement.
Abstract definition. Online analytical processing and multi-dimensional analysis. Data classification concept and classifier
evaluation. unequal problems clustering. Data clustering. Data mining implementation.