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 SurveyCTO, 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 SurveyCTO

·         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.

TOPICS TO BE COVERED

Module1: Basic statistical terms and concepts

·         Introduction to statistical concepts

·         Descriptive Statistics

·         Inferential statistics

Module 2:Research Design

·         The role and purpose of research design

·         Types of research designs

·         The research process

·         Which method to choose?

·         Exercise: Identify a project of choice and developing a research design

Module 3: Survey Planning, Implementation and Completion

·         Types of surveys

·         The survey process

·         Survey design

·         Methods of survey sampling

·         Determining the Sample size

·         Planning a survey

·         Conducting the survey

·         After the survey

·         Exercise: Planning for a survey based on the research design selected

Module 4:Introduction to SurveyCTO

·         Introduction and Key Concepts

·         Overview of ODK and Kobotolbox

·         Advantages of SurveyCTO

·         Key Features of SurveyCTO

·         Case studies on use of SurveyCTO

Module 5:SurveyCTO  Server

·         Components of SurveyCTO

·         Data aggregation, storage, and dissemination

·         Setting up a SurveyCTO server

·         Managing users & user roles

Module 6:Setting Up SurveyCTO  Collect App

·         Installing SurveyCTO collect from google play store

·         Configuring SurveyCTO collect app

·         SurveyCTO   Collect Application  Interface

Module 7:SurveyCTO Online Form builder

·         Creating a form

·         Input types

·         Adding question to Form

·         Form logics

·         Import  and export forms

Module 8:Building Forms using XLSForms

·         Introduction to xlsform designer

·         Components of XlSForm

·         Question types

·         Handling constraints and required options

·         Form skip logic

·         Form Operators and Functions

·         Grouping Questions

·         Settings Worksheet

·         Importing xlsforms to surveyCTO server

Module 9:Using SurveyCTO  Collect

·         Managing forms in SurveyCTO Collect

·         Collecting GPS data

·         Submitting data to  SurveyCTO Server

Module 10:Monitoring Data with SurveyCTO Data Explorer

·         Monitoring Submission statistics

·         Monitoring Form submissions and dataset

·         Reviewing and correcting incoming data

·         Summarize data submitted for individual fields

·         Summarize the empirical relationships between field

Module 11:Data Management

·         Exporting &Exporting data from SurveyCTO as CSV via SurveyCTO Sync

·         Importing SurveyCTO – CSV file into statistical applications

·         Downloading data directly from SurveyCTO

Module 12:Visualizing Geographic Data

·         Exporting GPS Coordinates to Google maps and Google Earth

·         Exporting GPS data for Mapping/Visualizing

 

Module 13: GIS mapping of survey data using QGIS

·         Introduction to GIS for Researchers and data scientists

·         Importing survey data into a GIS

·         Mapping of survey data using QGIS

·         Exercise: QGIS mapping exercise.

Module 14:Understanding Qualitative Research

·         Qualitative Data

·         Types of Qualitative Data

·         Sources of Qualitative data

·         Qualitative vs Quantitative

·         NVivo key terms

·         The NVivo Workspace

Module 15:Preliminaries of Qualitative data Analysis

·         What is qualitative data analysis

·         Approaches in Qualitative data analysis; deductive and inductive approach

·         Points of focus in analysis of text data

·         Principles of Qualitative data analysis

·         Process of Qualitative data analysis

Module 16:Introduction to NVIVO

·         NVIVO Key terms

·         NVIVO interface

·         NVIVO workspace

·         Use of NVIVO ribbons

Module 17:NVIVO Projects

·         Creating new projects

·         Creating a new project

·         Opening and Saving project

·         Working with Qualitative data files

·         Importing Documents

·         Merging and exporting projects

·         Managing projects

·         Working with different data sources

Module 18:Nodes in NVIVO

·         Theme codes

·         Case nodes

·         Relationships nodes

·         Node matrices

·         Type of Nodes,

·         Creating nodes

·         Browsing Nodes

·         Creating Memos

·         Memos, annotations and links

·         Creating a linked memo

Module 19:Classes and summaries

·         Source classifications

·         Case classifications

·         Node classifications

·         Creating Attributes within NVivo

·         Importing Attributes from a Spreadsheet

·         Getting Results; Coding Query and Matrix Query

Module 20: Coding

·         Data-driven vs theory-driven coding

·         Analytic coding

·         Descriptive coding

·         Thematic coding

·         Tree coding

Module 21:Thematic Analytics in NVIVO

·         Organize, store and retrieve data

·         Cluster sources based on the words they contain

·         Text searches and word counts through word frequency queries.

·         Examine themes and structure in your content

Module 22:Queries using NVIVO

·         Queries for textual analysis

·         Queries for exploring coding

Module 23: Building on the Analysis

·         Content Analysis; Descriptive, interpretative

·         Narrative Analysis

·         Discourse Analysis

·         Grounded Theory

Module 24: Qualitative Analysis Results Interpretation

·         Comparing analysis results with research questions

·         Summarizing finding under major categories

·         Drawing conclusions and lessons learned

Module 25: Visualizing NVIVO project

·         Display data in charts

·         Creating models and graphs to visualize connections

·         Tree maps and cluster analysis diagrams

·         Display your data in charts

·         Create models and graphs to visualize connections

·         Create reports and extracts

Module 26: Triangulating results and Sources

·         Triangulating with quantitative data

·         Using different participatory techniques to measure the same indicator

·         Comparing analysis from different data sources

·         Checking the consistency on respondent on similar topic

Module 27: Report Writing

·         Qualitative report format

·         Reporting qualitative research

·         Reporting content

·         Interpretation

Module 28: Introduction to Phython

·         Course Intro

·         Setup

·         Installation Setup and Overview

·         IDEs and Course Resources

·         iPython/Jupyter Notebook Overview

Module 29:Learning Numpy

·         Intro to numpy

·         Creating arrays

·         Using arrays and scalars

·         Indexing Arrays

·         Array Transposition

·         Universal Array Function

·         Array Processing

·         Array Input and Output

Module 30: Intro to Pandas

·         DataFrames

·         Index objects

·         Reindex

·         Drop Entry

·         Selecting Entries

·         Data Alignment

·         Rank and Sort

·         Summary Statistics

·         Missing Data

·         Index Hierarchy

Module 31: Working with Data

·         Reading and Writing Text Files

·         JSON with Python

·         HTML with Python

·         Microsoft Excel files with Python

·         Merge and Merge on Index

·         Concatenate and Combining DataFrames

·         Reshaping, Pivoting and Duplicates in Data Frames

·         Mapping,Replace,Rename Index,Binning,Outliers and Permutation

·         GroupBy on DataFrames

·         GroupBy on Dict and Series

·         Splitting Applying and Combining

·         Cross Tabulation

Module 32:Big Data and Spark with Python

·         Welcome to the Big Data Section!

·         Big Data Overview

·         Spark Overview

·         Local Spark Set-Up

·         AWS Account Set-Up

·         Quick Note on AWS Security

·         EC2 Instance Set-Up

·         SSH with Mac or Linux

·         PySpark Setup

·         Lambda Expressions Review

·         Introduction to Spark and Python

·         RDD Transformations and Actions

Module 33: Data Visualization

·         Installing Seaborn

·         Histograms

·         Kernel Density Estimate Plots

·         Combining Plot Styles

·         Box and Violin Plots

·         Regression Plots

·         Heatmaps and Clustered Matrices

Module 34: Data Analysis

·         Linear Regression

·         Support Vector

·         Decision Trees and Random Forests

·         Natural Language Processing

·         Discrete Uniform Distribution

·         Continuous Uniform Distribution

·         Binomial Distribution

·         Poisson Distribution

·         Normal Distribution

·         Sampling Techniques

·         T-Distribution

·         Hypothesis Testing and Confidence Intervals

·         Chi Square Test and Distribution

Module 35: Report writing for surveys, data dissemination, demand and use

·         Writing a report from survey data

·         Communication and dissemination strategy

·         Context of Decision Making

·         Improving data use in decision making

·         Culture Change and Change Management

·         Preparing a report for the survey, a communication and dissemination plan and a demand and use strategy.

·         Presentations and joint action planning

 

General Notes

·         All our courses can be Tailor-made to participants' needs

·         The participant must be conversant in English

·         Presentations are well-guided, practical exercises, web-based tutorials, and group work. Our facilitators are experts with more than 10 years of experience.

·         Upon completion of training the participant will be issued with a Foscore development center certificate (FDC-K)

·         Training will be done at the Foscore development center (FDC-K) centers. We also offer inhouse and online training on the client schedule

·         Course duration is flexible and the contents can be modified to fit any number of days.

·         The course fee for onsite training includes facilitation training materials, 2 coffee breaks, a buffet lunch, and a Certificate of successful completion of Training. Participants will be responsible for their own travel expenses and arrangements, airport transfers, visa application dinners, health/accident insurance, and other personal expenses.

·         Accommodation, pickup, freight booking, and Visa processing arrangement, are done on request, at discounted prices.

·         Tablet and Laptops are provided to participants on request as an add-on cost to the training fee.

·         One-year free Consultation and Coaching provided after the course.

·         Register as a group of more than two and enjoy a discount of (10% to 50%)

·         Payment should be done before commence of the training or as agreed by the parties, to the FOSCORE DEVELOPMENT CENTER account, so as to enable us to prepare better for you.

·         For any inquiries reach us at training@fdc-k.org or +254712260031

 

·         Website:www.fdc-k.org

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