Research Design,ODK Mobile Data Collection,GIS Mapping,Data Analysis using NVIVO and PYTHON Course

Research Design,ODK Mobile Data Collection,GIS Mapping,Data Analysis using NVIVO and PYTHON Course on 10th to 21st October 2022

Course calendar

INTRODUCTION

New developments in data science offer a tremendous opportunity to improve decision-making. In the development world, there has been an increase in the number of data gathering initiative such as baseline surveys, Socio-Economic Surveys, Demographic and Health Surveys, Nutrition Surveys, Food Security Surveys, Program Evaluation Surveys, Employees, customers and vendor satisfaction surveys, and opinion polls among others, all intended to provide data for decision making.

It is essential that these efforts go beyond merely generating new insights from data but also to systematically enhance individual human judgment in real development contexts. How can organizations better manage the process of converting the potential of data science to real development outcomes This ten days hands-on course is tailored to put all these important consideration into perspective. It is envisioned that upon completion, the participants will be empowered with the necessary skills to produce accurate and cost effective data and reports that are useful and friendly for decision making.

It will be conducted using ODK, GIS, NVIVO and PYTHON

DURATION

2 Weeks

LEARNING OBJECTIVES

·         Understand and appropriately use statistical terms and concepts

·         Design and Implement universally acceptable Surveys

·         Convert data into various formats using appropriate software

·         Use mobile data gathering tools such as Open Data Kit (ODK)

·         Use GIS software to plot and display data on basic maps

·         Qualitative data analysis using NVIVO

·         Python for Data Science and Machine

·         Spark for Big Data Analysis

·         Implement Machine Learning Algorithms

·         Numbly for Numerical Data

·         Pandas for Data Analysis

·         Matplotlib for Python Plotting

·         Seaborn for statistical plots

·         interactive dynamic visualizations

·         SciKit-Learn for Machine Learning Tasks

·         K-Means Clustering, Logistic Regression and Linear Regression

·         Random Forest and Decision Trees

·         Natural Language Processing and Spam Filters

·         Neural Networks

·         Support Vector Machines

·         Write reports from survey data

·         Put strategies to improve data demand and use in decision making

WHO SHOULD ATTEND?

This is a general course targeting participants with elementary knowledge of Statistics from Agriculture, Economics, Food Security and Livelihoods, Nutrition, Education, Medical or public health professionals among others who already have some statistical knowledge, but wish to be conversant with the concepts and applications of statistical modeling.

INTRODUCTION

New developments in data science offer a tremendous opportunity to improve decision-making. In the development world, there has been an increase in the number of data gathering initiative such as baseline surveys, Socio-Economic Surveys, Demographic and Health Surveys, Nutrition Surveys, Food Security Surveys, Program Evaluation Surveys, Employees, customers and vendor satisfaction surveys, and opinion polls among others, all intended to provide data for decision making.

It is essential that these efforts go beyond merely generating new insights from data but also to systematically enhance individual human judgment in real development contexts. How can organizations better manage the process of converting the potential of data science to real development outcomes This ten days hands-on course is tailored to put all these important consideration into perspective. It is envisioned that upon completion, the participants will be empowered with the necessary skills to produce accurate and cost effective data and reports that are useful and friendly for decision making.

It will be conducted using ODK, GIS, NVIVO and PYTHON

DURATION

2 Weeks

LEARNING OBJECTIVES

·         Understand and appropriately use statistical terms and concepts

·         Design and Implement universally acceptable Surveys

·         Convert data into various formats using appropriate software

·         Use mobile data gathering tools such as Open Data Kit (ODK)

·         Use GIS software to plot and display data on basic maps

·         Qualitative data analysis using NVIVO

·         Python for Data Science and Machine

·         Spark for Big Data Analysis

·         Implement Machine Learning Algorithms

·         Numbly for Numerical Data

·         Pandas for Data Analysis

·         Matplotlib for Python Plotting

·         Seaborn for statistical plots

·         interactive dynamic visualizations

·         SciKit-Learn for Machine Learning Tasks

·         K-Means Clustering, Logistic Regression and Linear Regression

·         Random Forest and Decision Trees

·         Natural Language Processing and Spam Filters

·         Neural Networks

·         Support Vector Machines

·         Write reports from survey data

·         Put strategies to improve data demand and use in decision making

WHO SHOULD ATTEND?

This is a general course targeting participants with elementary knowledge of Statistics from Agriculture, Economics, Food Security and Livelihoods, Nutrition, Education, Medical or public health professionals among others who already have some statistical knowledge, but wish to be conversant with the concepts and applications of statistical modeling.