[PyFeyn] Training Course On Research Design, Mobile Data Collection, Mapping And Data Analysis Using Nvivo And Python

Data-Afrique consultancy workshops at data-afriqueconsultancy.or.ke
Wed Mar 6 17:34:48 GMT 2024
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 Training 
Course On Research Design, Mobile Data Collection, Mapping And Data Analysis 
Using Nvivo And Python 
 
Dates
Fees
Location
Apply
11/03/2024 - 22/03/2024
$3000
Nairobi

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Physical 
      Class

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Online 
      Class
08/04/2024 - 19/04/2024
$3950
Kigali

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Physical 
      Class

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Online 
      Class
13/05/2024 - 24/05/2024
$5500
Dubai

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Physical 
      Class

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Online 
      Class
10/06/2024 - 21/06/2024
$3000
Nairobi

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Physical 
      Class

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Online 
      Class
08/07/2024 - 19/07/2024
$3000
Nairobi

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Physical 
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Online 
      Class
08/07/2024 - 19/07/2024
$3000
Nairobi

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Physical 
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Online 
      Class
12/08/2024 - 23/08/2024
$3000
Nairobi

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Physical 
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Online 
      Class
09/09/2024 - 20/09/2024
$3000
Nairobi

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Physical 
      Class

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Online 
      Class
11/11/2024 - 22/11/2024
$3000
Mombasa

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Physical 
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Online 
      Class
09/12/2024 - 20/12/2024
$3000
Nairobi

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Online 
      Class
14/10/2024 - 25/10/2024
$3950
Kigali

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Our 202 Training Calendar 
 
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Whatapp
 
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 considerations 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
COURSE 
OBJECTIVES
At 
the end of course participants should be able to:
·        
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
DURATION
10 
Days
WHO 
SHOULD ATTEND
The course 
targets 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.
COURSE 
CONTENT
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
·        
Introduction 
to Mobile Data gathering
·        
Benefits 
of Mobile Applications
·        
Data 
and types of Data
·        
Introduction 
to common mobile based data collection platforms
·        
Managing 
devices
·        
Challenges 
of Data Collection
·        
Data 
aggregation, storage and dissemination
·        
Types 
of questions
·        
Data 
types for each question
·        
Types 
of questionnaire or Form logic
·        
Extended 
data types geoid, image and multimedia
Module 
5: Survey Authoring
·        
Design 
forms using a web interface using:
·        
ODK 
Build
·        
Koboforms
·        
PurcForms
·        
Hands-on 
Exercise
Module 
6: Preparing the mobile phone for data collection
·        
Installing 
applications: ODK Collect
·        
Using 
Google play
·        
Manual 
install (.apk files)
·        
Configuring 
the device (Mobile Phones)
 
THE 
END
 
Looking 
forward to your attendance.
 
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