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.

Program Content

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.

Admission process

To apply, email postgrados.cpp@esen.edu.sv for application.
For more information:  http://www.cpp.esen.edu.sv

 

Planning my Program

Course ListView printable list of courses with first available start date.

 
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In this certificate program, there are '10' required courses + you choose '0' electives

 
 

FULL PROGRAM LIST

  • Financial Risk Modeling
    This course teaches participants how to model financial events that have uncertainties associated with them. Next three dates:
    June 14, 2019 to July 12, 2019June 12, 2020 to July 10, 2020
    show more dates >> Learn more and register >>
  • Forecasting Analytics
    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:
    March 22, 2019 to April 19, 2019July 26, 2019 to August 23, 2019November 22, 2019 to December 20, 2019March 20, 2020 to April 17, 2020July 24, 2020 to August 21, 2020November 20, 2020 to December 18, 2020
    show 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:
    February 08, 2019 to March 08, 2019June 28, 2019 to July 26, 2019October 25, 2019 to November 22, 2019February 07, 2020 to March 06, 2020June 26, 2020 to July 24, 2020October 23, 2020 to November 20, 2020February 05, 2021 to March 05, 2021
    show more dates >> Learn more and register >>
  • Introduction to Network Analysis
    This course will teach a mix of quantitative and qualitative methods for describing, measuring and analyzing social networks. Next three dates:
    February 22, 2019 to March 22, 2019August 09, 2019 to September 06, 2019February 21, 2020 to March 20, 2020
    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:
    January 04, 2019 to February 01, 2019August 16, 2019 to September 13, 2019January 03, 2020 to January 31, 2020August 14, 2020 to September 11, 2020
    show 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:
    December 14, 2018 to January 11, 2019January 18, 2019 to February 15, 2019May 10, 2019 to June 07, 2019September 27, 2019 to October 25, 2019January 17, 2020 to February 14, 2020May 22, 2020 to June 19, 2020September 25, 2020 to October 23, 2020January 15, 2021 to February 12, 2021
    show 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:
    February 22, 2019 to March 22, 2019July 12, 2019 to August 09, 2019November 15, 2019 to December 13, 2019February 21, 2020 to March 20, 2020June 26, 2020 to July 24, 2020October 23, 2020 to November 20, 2020
    show 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:
    January 04, 2019 to February 01, 2019April 12, 2019 to May 10, 2019September 06, 2019 to October 04, 2019January 03, 2020 to January 31, 2020April 10, 2020 to May 08, 2020July 31, 2020 to August 28, 2020
    show more dates >> Learn more and register >>
  • Regression Analysis
    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:
    January 18, 2019 to February 15, 2019May 10, 2019 to June 07, 2019October 04, 2019 to November 01, 2019January 17, 2020 to February 14, 2020May 08, 2020 to June 05, 2020October 02, 2020 to October 30, 2020
    show 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:
    May 03, 2019 to May 31, 2019November 15, 2019 to December 13, 2019May 01, 2020 to May 29, 2020November 13, 2020 to December 11, 2020
    show 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 to pay on a course-by-course basis:

    • Pay for your program upon enrollment:  $5000
    • Pay as you go: $
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      6,970

     

    Detailed Fees Description

    Investment

    $ 7,000 (10 installments of $700) payable at ESEN

    Requirements

    • 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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