Postgraduate degree in Data Science Analytics
from Centro de Política Pública y Escuela Superior de Economía y Negocios (ESEN)
Post graduate degree in Data Science Analtyics
The Institute for Statistics Education at Statistics.com and the Centro de Politicas Publicas at Escuela Superior de Economía y Negocios (ESEN) are together offering a Post Graduate degree in Analytics for Data Science.
This innovative postgraduate degree in Analytics for Data Science will train business analyts in predictive modeling, forecasting, customer segmentation, data visualization and risk analysis.
The program is taught online in English.
Who is this program for?
This program is aimed at managers, business analysts or data software engineers and other computer professionals who work in positions related to the use of data to support decision-making in any field.
To apply, email firstname.lastname@example.org for application.
For more information: http://www.cpp.esen.edu.sv
Planning my Program
Financial Risk Modeling
This course teaches participants how to model financial events that have uncertainties associated with them. Next three dates:To be scheduled.show more dates >> Learn more and register >>
This course will teach you how to choose an appropriate time series model, fit the model, to conduct diagnostics, and use the model for forecasting. Next three dates:November 23, 2018 to December 21, 2018show more dates >> Learn more and register >>
Interactive Data Visualization
This course covers the principles of the visual display of data, both for presentation and analysis. Next three dates:October 26, 2018 to November 30, 2018show more dates >> Learn more and register >>
Introduction to Social Network Analysis (SNA)
This course will teach a mix of quantitative and qualitative methods for describing, measuring and analyzing social networks. Next three dates:To be scheduled.show more dates >> Learn more and register >>
Optimization - Linear Programming
The course introduces the use of mathematical models for managerial decision making and covers how to formulate linear programming models for decision problems where multiple decisions need to be made in the best possible way while simultaneously satisfying a number of logical conditions (or constraints). You will learn how to use spreadsheet software to implement and solve these linear programming problems. Next three dates:August 17, 2018 to September 14, 2018show more dates >> Learn more and register >>
Predictive Analytics 1 - Machine Learning Tools
This course covers the two core paradigms that account for most business applications of predictive modeling: classification and prediction. The course includes hands-on work with XLMiner, a data-mining add-in for Excel. Next three dates:September 28, 2018 to October 26, 2018May 22, 2020 to June 21, 2020show more dates >> Learn more and register >>
Predictive Analytics 2 - Neural Nets and Regression
This course covers the two core paradigms that account for most business applications of predictive modeling: classification and prediction. The course includes hands-on work with XLMiner, a data-mining add-in for Excel. Next three dates:October 26, 2018 to November 23, 2018show more dates >> Learn more and register >>
Predictive Analytics 3: Dimension Reduction, Clustering and Association Rules
This course covers key unsupervised learning techniques - association rules, principal components analysis, and clustering. The course will include an integration of supervised and unsupervised learning techniques. Next three dates:To be scheduled.show more dates >> Learn more and register >>
In this course you will learn how multiple linear regression models are derived, use software to implement them, learn what assumptions underlie the models, learn how to test whether your data meet those assumptions and what can be done when those assumptions are not met, and develop strategies for building and understanding useful models. Next three dates:October 05, 2018 to November 02, 2018show more dates >> Learn more and register >>
Risk Simulation and Queuing
This course covers modeling technique making decisions in the presence of risk or uncertainty. Specific topics include risk analysis using Monte Carlo simulation for risk simulation, queuing theory for problems involving waiting lines, and decision trees for analyzing problems with multiple discrete decision alternatives.Next three dates:November 16, 2018 to December 14, 2018show more dates >> Learn more and register >>
Tuition and Fees: $5000
The above estimate includes the program registration fee, and individual course fees. It reflects considerable savings that are available if you pay the program cost upon enrollment. You also have the option of paying in monthly installments, or on a course-by-course basis:
- Pay for your program upon enrollment (check or credit card): $5000
- Pay for program upon enrollment via training or purchase order, or if needing quote or invoice: $5500
- Pay in 18 monthly installments: $290/month
- Pay as you go: $7,000
$ 7,000 (10 installments of $700) payable at ESEN
- University graduate level degree or equivalent in any discipline, or finishing degre within six months from the date of filing of the application for admission.
- Knowledge of R programming.
- Statistical inference as part of undergraduate studies.
- English language proficiency at an intermediate or advanced level.
Documentation required for registration
- Copy of University degree and Certification registered by the Ministry of Education or equivalent institution outside of El Salvador.
- Copy of DUI, NIT and a copy of passport.
- Application for admission.
- Acceptance of the rules contained in the Academic Regulations of the Higher School of Economics and Business, RAESEN, and the standards established specifically for graduate courses Public Policy Center.
- Payment of first installment.
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