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 17:38:28 UTC 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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Online
Class
08/04/2024 - 19/04/2024
$3950
Kigali
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Physical
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Online
Class
13/05/2024 - 24/05/2024
$5500
Dubai
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Online
Class
10/06/2024 - 21/06/2024
$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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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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Online
Class
09/09/2024 - 20/09/2024
$3000
Nairobi
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Physical
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Online
Class
11/11/2024 - 22/11/2024
$3000
Mombasa
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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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Online
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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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