2024 - 2025 Training Course Schedule
+254 712 260 031
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Welcome to the comprehensive course on Epidemiology and Biostatistics with ODK, R, Python, Stata, SPSS, Excel, NVivo, Power BI, and GIS! This course is designed to provide you with a deep understanding of epidemiological principles, data analysis techniques, and advanced tools used in public health research and practice.
Epidemiology is the study of the distribution and determinants of health-related events in populations. It plays a crucial role in identifying health trends, risk factors, and opportunities for disease prevention and control. Biostatistics, on the other hand, complements epidemiology by providing the tools and methods to analyze and interpret health-related data, enabling evidence-based decision-making.
In this course, we will cover a wide range of topics, from study design and data collection using ODK for field-based research to data analysis and visualization using various software packages, including R, Python, Stata, SPSS, Excel, NVivo, Power BI, and GIS. You will gain hands-on experience in handling diverse datasets, performing statistical analyses, and creating informative visualizations.
Throughout the course, we will focus on the practical application of epidemiological and biostatistical concepts to real-world public health scenarios. You will have the opportunity to work on case studies, research projects, and a capstone project to apply the knowledge and skills acquired during the training.
By the end of this course, you will be equipped with the tools and techniques necessary to conduct epidemiological studies, analyze health-related data, and contribute to evidence-based decision-making in public health and research settings. Whether you are a public health professional, researcher, or student, this course will empower you to make a meaningful impact in the field of epidemiology and biostatistics.
We are excited to embark on this learning journey with you and look forward to exploring the fascinating world of epidemiology and biostatistics together! Let's get started and make a positive difference in public health through data-driven insights and informed decision-making.
The course is carefully designed to provide comprehensive coverage of the topics while ensuring sufficient time for hands-on practice and discussions. The duration of the course may vary, but it is typically structured to be completed over three weeks, allowing participants to gain a deep understanding of the subject matter.
Course Objective: The course aims to achieve the following objectives:
Module 1: Introduction to Epidemiology and Public Health
Module 2: Principles of Disease Transmission and Control
Module 3: Epidemiological Study Designs
Module 4: Data Collection Methods and Tools
Module 5: Data Management and Quality Assurance with ODK
Module 6: Introduction to Data Analysis with Excel
Module 7: Advanced Data Analysis with Excel
Module 8: Data Visualization with Excel
Module 9: Introduction to Biostatistics
Module 10: Descriptive Biostatistics using SPSS
Module 11: Inferential Biostatistics using SPSS
Module 12: Advanced Data Analysis with SPSS
Module 13: Data Visualization with SPSS
Module 14: Introduction to R Programming
Module 15: Data Manipulation with R
Module 16: Data Visualization with R
Module 17: Basic Statistical Analysis with R
Module 18: Advanced Statistical Modeling with R
Module 19: Hypothesis Testing with R
Module 20: Introduction to Python Programming
Module 21: Data Manipulation with Python
Module 22: Data Visualization with Python
Module 23: Basic Statistical Analysis with Python
Module 24: Advanced Statistical Modeling with Python
Module 25: Hypothesis Testing with Python
Module 26: Introduction to Stata for Epidemiology
Module 27: Data Management with Stata
Module 28: Basic Statistical Analysis with Stata
Module 29: Advanced Statistical Modeling with Stata
Module 30: Hypothesis Testing with Stata
Module 31: Introduction to NVivo for Qualitative Data Analysis
Module 32: Data Coding and Analysis using NVivo
Module 33: Data Visualization with Power BI
Module 34: Geographic Information Systems (GIS) in Epidemiology
Module 35: Spatial Data Analysis and Mapping
Module 36: Application of Epidemiology and Biostatistics in Public Health Research
Module 37: Ethical Considerations in Epidemiology and Biostatistics
Module 38: Integration of Tools: R, Python, Stata, SPSS, NVivo, Excel, Power BI, and GIS
Module 39: Handling Large Datasets and Big Data Analytics
Module 40: Capstone Project and Presentation