Computer and IT Information Technology Statistics

Course on Big Data Analytics for Policy Planners at ITEC, Ministry of External Affairs, Delhi [Sept 9-27]: Registrations Open

By: Jasmeet | 03 Sep 2019 7:44 PM

Indian Technical and Economic Cooperation Programme (ITEC) is a bilateral assistance program run by the Government of India. It is a demand-driven, response-oriented program that focuses on addressing the needs of developing countries through innovative technological cooperation between India and the partnering nation.

Along with its corollary the Special Commonwealth Assistance for Africa Programme, ITEC covers 158 countries across Asia, Africa, Latin America, Central, and Eastern Europe, and several Pacific and Caribbean nations. Since its inception, the program has spent over US$ 2 billion and benefited thousands of students and professionals from around the globe and annual expenditure on the program has averaged US$ 100 million per annum in recent years.

ITEC is conducting a course on Big data analytics for policy planners from September 9 to 27, 2019.

Course Prerequisite

Adequate knowledge of the following topics at the undergraduate level. Knowledge of the R software, at least at the basic level, will be necessary.

Probability, Common distributions, Estimation, Tests of Hypothesis, Analysis of Variance (ANOVA), Simple linear regression


Bachelor’s Degree in Statistics ( or in related subjects with adequate knowledge of statistics at the undergraduate level).

  • Introduction to the usual decision-making process and the need for data-driven decisions. Concept of supervised and unsupervised learning.
  • Least squares estimation of the regression coefficients, Test of significance of regression coefficients, prediction of new observations, etc. Inclusion of qualitative regressors.
  • Model fitting, interpretation of the coefficients in a logistic regression model, Odds ratio in logistic regression, Classification using logistic regression.
  • An overview of classification, Linear and quadratic discriminant function, Classification for normal populations. K-nearest neighbor classifier, Naïve Bayes classifier.
  • Overview of support vector classifier, Support vector machine,  SVM for regression, Relationship to logistic regression

To apply online, click here.


Email ID:

For further details, click here.

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