All Courses

Here's What You'll Learn:

Module 1: Introduction to Spatial Analysis and QGIS

Module 2: Vector Data Geoprocessing

Module 3: Raster Data Analysis

Module 4: Working with Attribute Data and Joins

Module 5: Advanced Vector Geoprocessing Tools

Module 6: DEM and Terrain Analysis

Module 7: Network Analysis

Module 8: Geostatistics and Interpolation

Module 9: Advanced Spatial Analysis Techniques

Module 10: Automating Geoprocessing with Graphical Modeler and Python

Here's What You'll Learn:

Module 1: Foundations of HR Metrics and Strategic Analytics

Module 2: Power BI Desktop: Setup, Data Connection, and Interface

Module 3: Data Transformation and Cleaning using Power Query Editor

Module 4: Mastering DAX for HR Calculations and Business Logic

Module 5: Designing Interactive Workforce and Engagement Dashboards

Module 6: Analytics for Recruitment, Talent Acquisition, and Efficiency

Module 7: Learning & Development (L&D) and Performance Analytics

Module 8: Compensation, Equity, and Total Rewards Analysis

Module 9: Advanced Data Visualization and Storytelling in Power BI

Module 10: Report Sharing, Governance, and Introduction to Predictive HR Analytics

Here's What You'll Learn:

Module 1: Introduction to Epidemiological Modeling and R

Module 2: Fundamentals of Deterministic Compartmental Models

Module 3: Implementing SIR/SEIR Models in R

Module 4: Parameter Estimation and Model Calibration

Module 5: Modeling the Impact of Vaccination

Module 6: Advanced Model Structures and Dynamics

Module 7: Stochastic Modeling and Outbreak Simulation

Module 8: Policy Analysis and Economic Evaluation

Module 9: Global Sensitivity and Uncertainty Analysis

Module 10: Case Studies and Advanced Modeling in R

Here's What You'll Learn:

Module 1: Foundations of Marketing Analytics

Module 2: Introduction to R for Data Analysis

Module 3: Data Preparation and Visualization in R

Module 4: Descriptive Marketing Analytics

Module 5: Customer Segmentation and Clustering (R)

Module 6: Predictive Modeling for Marketing (R)

Module 7: Introduction to Tableau for Visualization

Module 8: Connecting Data and Building Dashboards in Tableau

Module 9: Marketing Mix Modeling (R)

Module 10: Web and Social Media Analytics (R)

Module 11: A/B Testing and Experimentation Analysis (R)

Module 12: Customer Lifetime Value (CLV) Analysis (R)

Module 13: Visualizing Campaign Performance in Tableau

Module 14: Advanced Dashboarding Techniques in Tableau

Module 15: Reporting and Storytelling with Data

Module 16: Market Basket Analysis and Recommendation Systems (R)

Module 17: Geospatial Marketing Analysis

Module 18: Course Capstone Project and Next Steps

Here's What You'll Learn:

• Module 1: Introduction to PowerBI
• Module 2: Data Modeling
• Module 3: DAX Functions and Expressions
• Module 4: Creating Reports
• Module 5: Dashboards and Sharing
• Module 6: Advanced Data Visualization Techniques
• Module 7: Data Insights and Analytics
• Module 8: PowerBI Service
• Module 9: Best Practices for Data Visualization
• Module 10: Case Study and Final Project

Here's What You'll Learn:

Module 1: Introduction to Survey Data and SPSS

Module 2: Data Preparation and Management in SPSS

Module 3: Descriptive Statistics for Survey Data

Module 4: Visualizing Survey Data

Module 5: Hypothesis Testing Fundamentals

Module 6: Comparing Means (T-tests and ANOVA)

Module 7: Analyzing Relationships Between Categorical Variables (Chi-Square)

Module 8: Correlation and Regression Analysis

Module 9: Reliability and Factor Analysis

Module 10: Advanced Topics and Reporting Survey Findings

Here's What You'll Learn:

Module 1: STATA Programming and Data Management Fundamentals

Module 2: Advanced Data Reshaping and Cleaning Techniques

Module 3: Mastering Linear Regression Diagnostics and Extensions

Module 4: Generalized Linear Models (GLM) and Non-Linear Regression

Module 5: Time Series Analysis and Forecasting in STATA

Module 6: Panel Data Econometrics: Fixed and Random Effects

Module 7: Instrumental Variables (IV) and Treatment Effects Modeling

Module 8: Survival Analysis and Event History Modeling

Module 9: Survey Data Analysis and Weighting Methods

Module 10: Automation, Custom Reports, and Reproducible Research

Here's What You'll Learn:

Module 1: Foundations and the Research Lifecycle

Module 2: Crafting Compelling Introductions and Literature Reviews

Module 3: Methodological Rigor and Reporting Standards

Module 4: Presenting Results and Discussion/Conclusion

Module 5: Effective Academic Style and Language

Module 6: Ethics, Integrity, and Authorship

Module 7: Selecting the Right Journal and Targeting Audience

Module 8: Manuscript Submission and the Peer Review Process

Module 9: Revising and Responding to Reviewer Comments

Module 10: Maximizing Visibility and Impact

Here's What You'll Learn:

Module 1: Introduction to GIS and Public Health in Humanitarian Contexts

Module 2: Geospatial Data Collection and Management for Health Emergencies

Module 3: Core QGIS Functionalities for Public Health Analysis

Module 4: Spatial Epidemiology and Advanced Disease Mapping

Module 5: Environmental Health Risk Assessment and Mapping

Module 6: Healthcare Access, Resource Allocation, and Service Delivery Optimization

Module 7: Population Mapping, Vulnerability, and Displacement Analysis

Module 8: Introduction to Epi Info for Epidemiological Data Management

Module 9: Advanced Epi Info Data Analysis and Survey Design

Module 10: Integrating Epi Info and Other Health Data with QGIS

Module 11: Geocoding and Address Matching for Public Health Data

Module 12: Network Analysis for Health Logistics and Access

Module 13: Time Series and Spatio-Temporal Analysis for Outbreaks

Module 14: Automated Mapping and Reporting with QGIS

Module 15: Introduction to Remote Sensing for Public Health

Module 16: Data Quality, Ethics, and Privacy in Humanitarian GIS

Module 17: Web-Based GIS for Public Health Information Sharing

Module 18: Applied Project: End-to-End GIS for Public Health in Crisis

Here's What You'll Learn:

Module 1: Foundations of Literature Review and Research Questions

Module 2: Developing Comprehensive Search Strategies

Module 3: Database Selection and Search Execution

Module 4: Reference Management and Screening Tools

Module 5: Critical Appraisal and Risk of Bias Assessment

Module 6: Data Extraction and Coding for Synthesis

Module 7: Narrative Synthesis and Thematic Grouping

Module 8: Introduction to Meta-Analysis Principles

Module 9: Reporting Standards and Dissemination

Module 10: Writing, Reviewing, and Utilizing the Review

Here's What You'll Learn:

Module 1: Introduction to Genomics and Bioinformatics

Module 2: R Programming Fundamentals for Bioinformatics

Module 3: Working with Genomic Data Formats in R

Module 4: Quality Control and Pre-processing of Genomic Data

Module 5: Differential Expression Analysis (RNA-Seq)

Module 6: Introduction to Variant Calling and Annotation

Module 7: Population Genetics and GWAS (Conceptual)

Module 8: Introduction to Epigenomic Data Analysis

Module 9: Pathway and Network Analysis

Module 10: Introduction to Data Visualization with Tableau

Module 11: Connecting Genomic Data to Tableau

Module 12: Building Basic Visualizations in Tableau

Module 13: Advanced Visualizations for Genomic Data in Tableau

Module 14: Creating Interactive Dashboards in Tableau

Module 15: Statistical Plotting and Interpretation in R

Module 16: Best Practices for Reproducible Genomic Analysis

Module 17: Case Studies in Genomic Data Analysis

Module 18: Project Work and Presentation

Here's What You'll Learn:

Module 1: Foundations of Outbreak Data and R Environment Setup

Module 2: Data Import, Cleaning, and Tidy Data Principles in R

Module 3: Descriptive Epidemiology and Measures in R

Module 4: Advanced Visualization for Outbreaks using ggplot2

Module 5: Introduction to Spatial Epidemiology and Mapping in R

Module 6: Time Series Analysis and Epidemic Curves using R

Module 7: Advanced Epidemiological Modeling with R

Module 8: Introduction to Power BI for Data Connection

Module 9: Data Transformation and M-Query in Power BI

Module 10: Data Modeling and Relationships in Power BI

Module 11: DAX Fundamentals for Public Health Metrics

Module 12: Creating Interactive Outbreak Dashboards in Power BI

Module 13: Geospatial Mapping and Visualization in Power BI

Module 14: Integrating R Visuals into Power BI

Module 15: Forecasting and Predictive Analytics in R

Module 16: Ethics, Data Security, and Confidentiality

Module 17: Automating Refresh and Dashboard Publication

Module 18: Final Capstone Project: End-to-End Analytics