COURSE INTRODUCTION
In recent years, the growing use of data science has dramatically improved decision-making processes across various sectors. There is an increasing amount of data being gathered through initiatives like baseline surveys, demographic health surveys, socio-economic surveys, food security surveys, and employee/customer satisfaction assessments. These efforts aim to gather data that is crucial for informed decision-making.
It is important for organizations to go beyond just generating insights from data. They must focus on systematically enhancing human judgment in real-world scenarios. How can organizations harness the power of data science to drive real-world development outcomes? This hands-on training, which spans 10 days, aims to address these important considerations. By the end of the course, participants will gain practical skills in producing accurate, actionable, and cost-effective data reports for decision-making.
The course will cover the use of SurveyCTO, GIS, NVIVO, and Python.
COURSE DURATION
2 Weeks
LEARNING OBJECTIVES
Understand key statistical terms and concepts.
Design and implement effective and universally accepted surveys.
Convert data into various formats using appropriate software.
Utilize mobile data collection tools like SurveyCTO.
Use GIS software to plot and display survey data on maps.
Analyze qualitative data using NVIVO.
Use Python for data science and machine learning tasks.
Explore Spark for big data analysis.
Learn to implement machine learning algorithms.
Work with Numpy for numerical data processing.
Utilize Pandas for data analysis and Matplotlib for plotting.
Create interactive dynamic visualizations.
Learn advanced machine learning techniques like K-Means Clustering, Logistic Regression, Random Forest, and Support Vector Machines.
Implement Natural Language Processing (NLP) and Spam Filters.
Gain insights into Neural Networks.
Write comprehensive reports from survey data.
Formulate strategies to enhance data use for better decision-making.
WHO SHOULD ATTEND?
This course is designed for professionals from diverse fields such as Agriculture, Economics, Nutrition, Food Security, Public Health, Education, and more. It is ideal for individuals who already have basic knowledge of statistics and wish to deepen their understanding of statistical modeling and its real-world applications.
COURSE MODULES
Module 1: Introduction to Statistical Concepts
Basic statistical concepts.
Descriptive statistics.
Inferential statistics.
Module 2: Research Design
The role and purpose of research design.
Types of research designs.
The research process and methodology.
Exercise: Develop a research design based on a selected project.
Module 3: Survey Planning, Implementation, and Completion
Overview of survey types.
Survey process and design.
Sampling methods and sample size determination.
Planning and conducting surveys.
Post-survey tasks.
Module 4:
Introduction to SurveyCTO
Introduction and key features of SurveyCTO.
Advantages over other platforms like ODK and KoBoToolbox.
Case studies on SurveyCTO applications.
Module 5:
SurveyCTO Server Setup
SurveyCTO components and server setup.
Data aggregation, storage, and dissemination.
Module 6:
SurveyCTO Collect App Setup
Installing and configuring the SurveyCTO Collect app.
Exploring the app interface.
Module 7:
SurveyCTO Online Form Builder
Creating forms using SurveyCTO’s form builder.
Using various input types and logic to design dynamic forms.
Module 8:
Building Forms with XLSForms
Introduction to XLSForm design.
Handling constraints, skip logic, and other form features.
Module 9:
Collecting Data with SurveyCTO
Managing forms and submitting data from the SurveyCTO Collect app.
Collecting GPS data and sending it to the SurveyCTO server.
Module 10
: Data Monitoring and Management
Monitoring submissions and form progress using SurveyCTO Data Explorer.
Exporting and managing data for analysis.
Module 11:
Visualizing Geographic Data Using GIS
Exporting GPS coordinates for mapping.
Using QGIS for mapping survey data.
Module 12:
Qualitative Research and NVIVO
Understanding qualitative data and analysis.
Introduction to NVIVO for qualitative data analysis.
Managing NVIVO projects, nodes, and coding.
Conducting thematic and content analysis using NVIVO.
Module 13:
Introduction to Python for Data Science
Setting up Python and Jupyter notebooks.
Working with libraries like Numpy, Pandas, Matplotlib, and Seaborn.
Introduction to machine learning and data visualization techniques.
Module 14:
Advanced Data Science Techniques
Learning about big data analysis with Spark.
Implementing machine learning algorithms.
Working with K-Means Clustering, Decision Trees, and Random Forest.
Module 15:
Report Writing and Data Dissemination
Writing clear and comprehensive reports from survey data.
Strategies for communicating results to decision-makers.
COURSE DETAILS
Duration: 2 Weeks
Location: Stepsure Training And Research Institute (can also be customized for in-house or online training).
Fee: The course fee includes training, materials, two coffee breaks, lunch, and a completion certificate.
Contact Info:
Email: info@stepsureresearchinstitute.org
Phone: +254 723 482 495
Website: www.stepsureresearchinstitute.org
