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Thai-Nichi Institute of Technology Student Handbook 2019 International Program
DSA-205 A Practical Approach to Data Science 3(3-0-6)
Prerequisite : DSA-105 Introduction to Data Science
Corequisite : None
Introduction to data science and its application to the business, the life cycle of a
typical data science project. Loading data from various formats, exploring and managing
data. Modeling methods, choosing and evaluating models. Single-variable models, basic
multiple-variable models such as decision trees, nearest neighbor, and Naive Bayes. Linear
and logistic regression. Unsupervised methods, documentation and deployment.

DSA-206 Programming for Data Analysis 3(3-0-6)
Prerequisite : DSA-103 Object-Oriented Programming and
DSA-107 Data Structure and Algorithm
Corequisite : None
A scripting language for statistical data manipulation and analysis, Introduction
to R and RStudio, How to run R, introduction to functions, data types such as scalars,
vectors, arrays, and matrices, Vector operations, vector indexing, filtering, List and its
operations, data frame, factors and tables, R programming structures such as control
statements, arithmetic and boolean operators, functions, and recursion, Math and statistical
functions, Object-oriented programming, Input / Output, Graphics package, Debugging,
Fundamental packages for statistics and data analysis.

DSA-207 Programming for Data Analysis Laboratory 1(0-3-2)
Prerequisite : DSA-103 Object-Oriented Programming and
DSA-107 Data Structure and Algorithm
Corequisite : None
Introduction to programming for data analysis, for example, running Python with
an interactive prompt, command line and IDE, types and operations. Numerics, dynamic
typing, list and dictionaries, tuples and files, expression and statements, functions, modules
and packages, classes and OOP, essential packages for data analysis such as NumPy, Pandas
and Matplotlib.