Study Plan - Data Science

When you finish all units of your education program, you will receive a Diploma and a Professional License, as well as a bachelor’s degree endorsed by SACSCOC that is recognized worldwide.

Accredited and Consolidated Institution.
Registered in Group 3 of the Institutional Improvement Program.

First Term

Matter Code
Course List
Sequence
Hours With Teacher
Hours Independent
Credits (Units)
LEX0113
FOREIGN LANGUAGE I
48
48
6
DIG0013
DIGITAL CULTURE
48
48
6
GENERAL STUDIES ELECTIVE IN MATH
48
48
6
MAT1013
COLLEGE MATH
48
48
6
LIS1013
ALGORITHMS AND PROGRAMMING
64
32
6
MAT1053
ANALYTICAL GEOMETRY
48
48
6
Total
304
272
36

Hours With Teacher : Horas Docente
Hours Independent: Horas independiente

Second Term

Matter Code
Course List
Sequence
Hours With Teacher
Hours Independent
Credits (Units)
MAT1023
CALCULUS I
MAT1013
64
32
6
MAT1043
ADVANCED ALGEBRA
0
0
6
GENERAL STUDIES ELECTIVE IN SOCIAL SCIENCES
0
0
6
LEX0123
FOREIGN LANGUAGE II
LEX0113
48
0
6
ESP0013
ACADEMIC REASONING
DIG0013
48
48
6
LIS1023
OBJECT-ORIENTED PROGRAMMING
LIS1013
64
32
6
GENERAL STUDIES ELECTIVE IN ARTS
0
0
6
Total
224
112
42

Hours With Teacher : Horas Docente
Hours Independent: Horas independiente

Third Term

Matter Code
Course List
Sequence
Hours With Teacher
Hours Independent
Credits (Units)
LDS2013
DATA REPRESENTATION
LIS1023
0
0
6
LDS2023
DISCRETE ANALYSIS I
MAT1043
0
0
6
LEX0133
FOREIGN LANGUAGE III
LEX0123
0
0
6
ESP0023
ACADEMIC WRITING
ESP0013
0
0
6
MAT2013
CALCULUS II
MAT1023
64
32
6
LAT2013
MATRIX THEORY
0
0
6
LAT2023
STOCHASTIC MODELS I
0
0
6
Total
64
32
42

Hours With Teacher : Horas Docente
Hours Independent: Horas independiente

Fourth Term

Matter Code
Course List
Sequence
Hours With Teacher
Hours Independent
Credits (Units)
MAT2023
MATHEMATICAL ANALYSIS I
MAT1023
0
0
6
LAT2053
STOCHASTIC MODELS II
LAT2023
0
0
6
LIS2033
DATABASES
LIS1023
0
0
6
LIS2043
DISCRETE MATH
MAT1023
0
0
6
LDS2033
DISCRETE ANALYSIS II
LDS2023
0
0
6
GENERAL STUDIES ELECTIVE IN HUMANITIES
0
0
6
GENERAL STUDIES ELECTIVE IN NATURAL SCIENCES
0
0
6
Total
0
0
42

Hours With Teacher : Horas Docente
Hours Independent: Horas independiente

Fifth Term

Matter Code
Course List
Sequence
Hours With Teacher
Hours Independent
Credits (Units)
LFA3123
NUMERICAL ANALYSIS
MAT1033
0
0
6
LDS3013
PROFESSIONAL PRACTICES I
0
0
6
MAT3013
MATHEMATICAL ANALYSIS II
MAT2023
0
0
6
LAT3013
INFERENCE METHODS I
LAT2023
0
0
6
LAT3023
STOCHASTIC MODELS III
LAT2053
0
0
6
Total
0
0
30

Hours With Teacher : Horas Docente
Hours Independent: Horas independiente

Sixth Term

Matter Code
Course List
Sequence
Hours With Teacher
Hours Independent
Credits (Units)
LAT3053
MATH PROGRAMMING
LAT2013
0
0
6
LAT3063
INFERENCE METHODS II
LAT3013
0
0
6
LEC3043
ECONOMETRICS
MAT1023
0
0
6
LDS3023
PATTERN RECOGNITION
LAT3013
0
0
6
LDS3033
SELECT TOPICS
0
0
6
LDS3043
COMPUTER INTELLIGENCE
MAT3023
0
0
6
Total
0
0
36

Hours With Teacher : Horas Docente
Hours Independent: Horas independiente

Seventh Term

Matter Code
Course List
Sequence
Hours With Teacher
Hours Independent
Credits (Units)
LDS4013
DATA MINING
LAT3013
0
0
6
LDS4023
TOPOLOGICAL DATA ANALYSIS
LDS3023
0
0
6
LDS4033
CONCURRENT PROGRAMMING
0
0
6
LDS4043
PERSPECTIVES OF THE DISCIPLINE
0
0
6
LDS4053
PROFESSIONAL PRACTICES II
LDS3013
0
96
6
LEC3103
TIME SERIES ECONOMETRICS
LEC3043
0
0
6
Total
0
96
36

Hours With Teacher : Horas Docente
Hours Independent: Horas independiente

Eighth Term

Matter Code
Course List
Sequence
Hours With Teacher
Hours Independent
Credits (Units)
LAT4053
ADVANCED OPTIMIZATION
LAT3053
0
0
6
LIS4093
CLOUD COMPUTING AND BIG DATA
LIS4053
0
0
6
LDS4063
DATA VISUALIZATION
LDS4013
0
0
6
LDS4073
DATA SECURITY
LDS4033
0
0
6
LDS4083
VANGUARD TOPICS
0
0
6
LDS4093
STATISTICAL LEARNING
LDS3043
48
48
6
Total
48
48
36

Hours With Teacher : Horas Docente
Hours Independent: Horas independiente

Total Study Plan Credits
Hours With Teacher 640
Hours Independent 560
Credits (Units) 300

Objective

Train highly qualified professionals in the analysis and management of large volumes of data, with a solid foundation in statistical analysis, mathematical models, programming and advanced data science techniques such as artificial intelligence, neural networks, machine learning and data visualization. All of this in a physical and virtual learning environment, seeking to develop critical, creative and innovative experts capable of facing contemporary technological and social challenges, contributing to the equitable development and scientific advancement of globalized society.

Graduate profile

The Data Science’s teaching learning process is based on competencies. This focus includes knowledge, skills and attitudes, thus training ethical professionals who can respond to data science needs and requirements in a globalized world.

  • Master Data Science methodologies with statistical analysis and information management to create solutions that benefit society.
  • Apply probability tools to relate random phenomena with contextual variables, proposing effective solutions and showing an attitude of service.
  • Interpret results of statistical and mathematical techniques responsibly, using technological and digital tools to make informed decisions.
  • Select appropriate computer tools according to the needs of the project, identifying patterns and ensuring honest and specific solutions.
  • Design databases with models, query and optimization languages, using ethical tools to establish analysis strategies.
  • Effectively manage learning through digital resources, optimizing your professional development process.

Explore everything that studying Data Science has to offer.

Recommended Computer Specifications

These specifications are provided as a general guideline, reflecting the average requirements of the academic software currently in use at the institution. Please note that the university is not responsible for any individual decisions made regarding computer equipment.