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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Foscore Development Center |Training Courses | Monitoring and Evaluation|Data Analysis|Market Research |M&E Consultancy |ICT Services |Mobile Data Collection | ODK Course | KoboToolBox | GIS and Environment |Agricultural Services |Business Analytics specializing in short courses in GIS, Monitoring and Evaluation (M&E), Data Management, Data Analysis, Research, Social Development, Community Development, Finance Management, Finance Analysis, Humanitarian and Agriculture, Mobile data Collection, Mobile data Collection training, Mobile data Collection training Nairobi, Mobile data Collection training Kenya, ODK, ODK training, ODK training Nairobi, ODK training Kenya, Open Data Kit, Open Data Kit training, Open Data Kit Training, capacity building, consultancy and talent development solutions for individuals and organisations, through our highly customised courses and experienced consultants, in a wide array of disciplines
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