Here's What You'll Learn:

• Introduction to Kobo Toolbox: Overview of mobile data collection, platform setup, basic form creation.
• Form Design: Effective design techniques, skip logic, validation rules, cascading selects.
• Data Management: Deployment, synchronization, export, and permissions management.
• Advanced Features: Multimedia questions, geopoints, external data, and advanced logic.
• Analysis & Visualization: Data cleaning, exporting, creating charts, and using external tools.
• Security & Ethics: Data privacy, security strategies, ethical considerations, compliance.
• Integration with External Tools: APIs, Google Sheets, GIS software, automation.
• Collaborative Projects: Team data collection and real-time monitoring.
• Project Management: Large-scale project handling, budgeting, stakeholder reporting.

Here's What You'll Learn:

Module 1: Foundations of Humanitarian Action

Module 2: Humanity and Impartiality

Module 3: Neutrality and Independence

Module 4: Do No Harm Principle

Module 5: Accountability and Quality Standards

Module 6: Protection of Civilians

Module 7: Humanitarian Access and Security Management

Module 8: Coordination and Partnerships

Module 9: The Humanitarian-Development-Peace Nexus

Module 10: Practical Application and Ethical Dilemmas

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 Customer Relationship Management (CRM) in Banking

Module 2: Understanding the Banking Customer

Module 3: CRM Strategies for Banks

Module 4: CRM Technologies and Systems for Banking

Module 5: Data Management and Analytics in Banking CRM

Module 6: Customer Segmentation and Targeting in Banking

Module 7: Personalization and Customization in Banking CRM

Module 8: Customer Loyalty and Retention Strategies for Banks

Module 9: Measuring CRM Effectiveness in Banking

Module 10: The Future of CRM in Banking

Here's What You'll Learn:

Module 1: Foundations of Robust Research Design

Module 2: Conceptualizing the Research Framework

Module 3: Sampling Strategies and Ethical Practice

Module 4: Introduction to Data Types and Management

Module 5: Implementing Mobile Data Collection Tools

Module 6: Advanced Survey Design for Mobile Platforms

Module 7: Form Programming, Logic, and Deployment

Module 8: Real-Time Data Quality Assurance

Module 9: Introduction to Qualitative Data Analysis and NVIVO

Module 10: NVIVO: Importing, Organizing, and Initial Coding

Module 11: NVIVO: Advanced Thematic Analysis and Node Structures

Module 12: NVIVO: Queries, Visualizations, and Reporting

Module 13: Introduction to Quantitative Analysis and the Stata Environment

Module 14: Stata: Data Management, Cleaning, and Manipulation

Module 15: Stata: Descriptive Statistics and Advanced Data Visualization

Module 16: Stata: Inferential Statistics - Comparison Tests and Power

Module 17: Stata: Regression Analysis (Linear and Logistic Models)

Module 18: Synthesis, Interpretation, and High-Impact Reporting

Here's What You'll Learn:

Module 1: Introduction to Precision Agriculture and Smart Farming

Module 2: Geospatial Technologies in Precision Agriculture

Module 3: Sensors and Data Collection in the Field

Module 4: Data Management and Analysis for Precision Farming

Module 5: Variable Rate Technologies and Prescription Maps

Module 6: Precision Irrigation and Water Management

Module 7: Smart Pest, Disease, and Weed Management

Module 8: Robotics, Automation, and Drones in Agriculture

Module 9: Farm Management Software and Decision Support Systems

Module 10: Economic Benefits and Implementation of Precision Agriculture

Here's What You'll Learn:

Module 1: Foundations of Culture and Communication

Module 2: Cultural Dimensions and Models

Module 3: Verbal Communication Across Cultures

Module 4: Non-Verbal Communication and Cultural Cues

Module 5: Navigating Cultural Differences in Business and Workplaces

Module 6: Building Intercultural Relationships and Trust

Module 7: Managing Conflict in Cross-Cultural Settings

Module 8: Cross-Cultural Negotiation and Decision-Making

Module 9: Adapting Communication Styles for Global Success

Module 10: Developing Intercultural Competence and Continuous Learning

Here's What You'll Learn:

Module 1: Foundations of Public Speaking

Module 2: Conquering Stage Fright and Building Confidence

Module 3: Crafting Your Message and Structuring Your Talk

Module 4: Mastering Vocal Delivery

Module 5: Body Language and Visual Aids

Module 6: Engaging Your Audience

Module 7: Handling Q&A and Impromptu Speaking

Module 8: Advanced Presentation Techniques

Module 9: Storytelling for Impact

Module 10: Creating a Personal Action Plan

Here's What You'll Learn:

Module 1: Introduction to Post-Harvest Management and Food Processing

Module 2: Principles of Post-Harvest Handling and Storage

Module 3: Food Preservation Technologies

Module 4: Food Quality Control and Safety

Module 5: Processing of Grains and Cereals

Module 6: Processing of Fruits and Vegetables

Module 7: Processing of Dairy and Meat Products

Module 8: Packaging and Labeling of Food Products

Module 9: Food Waste Reduction and Value Addition

Module 10: Food Business Development and Regulations

Module 1: Introduction to Climate Change and the Need for Climate Finance

Module 2: Understanding Carbon Markets: Compliance Mechanisms

Module 3: Understanding Carbon Markets: Voluntary Mechanisms

Module 4: International Climate Finance Architecture

Module 5: Project Development and Financing for Climate Action

Module 6: Accessing Climate Finance: Proposal Writing and Requirements

Module 7: Carbon Market Project Development and Implementation

Module 8: Article 6 of the Paris Agreement and New Market Mechanisms

Module 9: Risk Management and Governance in Climate Finance and Carbon Markets

Module 10: The Role of the Private Sector and Future Trends in Climate Finance and Carbon Markets

Here's What You'll Learn:

Module 1: Business Combinations and Consolidated Financial Statements (IFRS 3 & IFRS 10)

Module 2: Financial Instruments - Recognition, Measurement, and Derecognition (IFRS 9)

Module 3: Financial Instruments - Presentation and Disclosures (IAS 32 & IFRS 7)

Module 4: Employee Benefits (IAS 19)

Module 5: Income Taxes (IAS 12)

Module 6: Provisions, Contingent Liabilities, and Contingent Assets (IAS 37)

Module 7: Leases (IFRS 16)

Module 8: Revenue from Contracts with Customers (IFRS 15)

Module 9: Investment Property (IAS 40) and Property, Plant and Equipment (IAS 16)

Module 10: Presentation of Financial Statements (IAS 1) and Accounting Policies, Changes in Accounting Estimates and Errors (IAS 8)

Here's What You'll Learn:

Module 1: Introduction to Aquaculture

Module 2: Site Selection and Pond Construction

Module 3: Fish Species Selection

Module 4: Water Quality Management

Module 5: Fish Nutrition and Feeding

Module 6: Fish Health Management

Module 7: Harvesting and Post-Harvest Handling

Module 8: Farm Management and Economics

Module 9: Sustainable Aquaculture Practices

Module 10: Current Trends and Innovations in Aquaculture in Kenya

Here's What You'll Learn:

Module 1: Foundations of Market Research and the Consumer Landscape

Module 2: Secondary Data and Market Sizing

Module 3: Qualitative Research Methods

Module 4: Fundamentals of Quantitative Research Design

Module 5: Descriptive Statistics and Data Visualization for Insights

Module 6: Hypothesis Testing and Statistical Inference in Market Research

Module 7: Segmentation, Targeting, and Positioning (STP) Analysis

Module 8: Regression and Predictive Modeling

Module 9: Advanced Measurement and Scaling Techniques

Module 10: Reporting, Storytelling, and Actionable Insights

Here's What You'll Learn:

Module 1: Foundations of Interpersonal Skills

Module 2: Active Listening and Empathy

Module 3: Effective Communication Strategies

Module 4: Conflict Resolution and Negotiation

Module 5: Building Rapport and Trust

Module 6: Managing Emotions and Self-Awareness

Module 7: Assertiveness vs. Aggression

Module 8: Giving and Receiving Feedback

Module 9: Collaboration and Teamwork

Module 10: Creating a Personal Interpersonal Development Plan

Here’s What You’ll Learn:

Module 1: Introduction to the Banking Industry

Module 2: Core Banking Products and Services

Module 3: Account Opening and Customer Onboarding

Module 4: Deposit Operations and Management

Module 5: Lending Operations and Credit Management

Module 6: Payment Systems and Transactions

Module 7: Treasury Functions and Foreign Exchange

Module 8: Compliance and Regulatory Framework in Banking

Module 9: Customer Service and Relationship Management in Banking

Module 10: Risk Management in Banking Operations

Here's What You'll Learn:

Module 1: Understanding Climate Change and the Energy Landscape

Module 2: Solar Photovoltaic (PV) Technology

Module 3: Wind Energy Systems

Module 4: Hydropower and Geothermal Energy

Module 5: Bioenergy and Waste-to-Energy Technologies

Module 6: Energy Storage Solutions

Module 7: Grid Integration and Smart Grids

Module 8: Energy Efficiency and Conservation

Module 9: Climate Change Mitigation Policies and Strategies

Module 10: Project Development and Financing for Renewable Energy

Here's What You'll Learn:

Module 1: SurveyCTO Fundamentals and Server Setup

Module 2: Designing Forms with the Online Form Designer

Module 3: Advanced Form Logic and Validation (XPath Functions)

Module 4: Working with External Datasets and Pre-loading Data

Module 5: Data Collection using SurveyCTO Collect and Web Forms

Module 6: Real-Time Data Monitoring and Quality Control

Module 7: Data Management, Export, and Synchronization

Module 8: Introduction to Geospatial Data Collection and Mapping

Module 9: Advanced Features: Case Management and Audit Trails

Module 10: Data Security, Privacy, and Best Practices

Here's What You'll Learn:

Module 1: Foundations of High-Performing Teams

Module 2: Effective Team Communication

Module 3: Building Trust and Psychological Safety

Module 4: Conflict Resolution and Negotiation

Module 5: Defining Roles and Responsibilities

Module 6: Collaborative Problem-Solving and Decision-Making

Module 7: Leveraging Diversity for Innovation

Module 8: Giving and Receiving Constructive Feedback

Module 9: Building a Collaborative Culture

Module 10: Creating a Teamwork Action Plan

Here's What You'll Learn:

Module 1: Foundational Data Concepts and Stata Interface

Module 2: Advanced Quantitative Data Manipulation in Stata

Module 3: Descriptive Statistics and Data Visualization in Stata

Module 4: Inferential Statistical Analysis using Stata

Module 5: Introduction to Qualitative Data Analysis and NVivo

Module 6: Preparing and Importing Qualitative Data into NVivo

Module 7: Systematic Coding and Node Management in NVivo

Module 8: Exploring Themes and Patterns with NVivo Queries

Module 9: Integrating Quantitative and Qualitative Findings (Mixed Methods)

Module 10: Reporting, Dissemination, and Ethical Data Practices

Here's What You'll Learn:

Module 1: Introduction to Permaculture Ethics and Principles

Module 2: Understanding Natural Systems and Ecological Literacy

Module 3: Permaculture Design Process and Tools

Module 4: Water Management and Earthworks

Module 5: Soil Building and Fertility Strategies

Module 6: Guilds, Stacking, and Forest Gardens

Module 7: Integrated Animal Systems in Permaculture

Module 8: Appropriate Technology and Renewable Energy

Module 9: Designing for Social and Economic Permaculture

Module 10: Developing Your Permaculture Design Project

Here's What You'll Learn:

Module 1: Introduction to Urban Agriculture and Food Security

Module 2: Principles of Urban Permaculture and Ecological Design

Module 3: Urban Farming Techniques and Technologies

Module 4: Soil Health and Nutrient Management in Urban Settings

Module 5: Water Management and Irrigation for Urban Farms

Module 6: Pest and Disease Management in Urban Agriculture

Module 7: Policy, Planning, and Governance for Urban Agriculture

Module 8: Economic Models and Value Chains in Urban Agriculture

Module 9: Community Engagement and Social Aspects of Urban Agriculture

Module 10: Developing an Urban Agriculture Project Plan

Here's What You'll Learn:

Module 1: Introduction to Data Warehousing

Module 2: Dimensional Modeling

Module 3: ETL Concepts and Architecture

Module 4: Data Extraction Techniques

Module 5: Data Transformation Processes

Module 6: Data Loading Strategies

Module 7: ETL Tool Selection and Best Practices

Module 8: Data Quality Management in Data Warehousing

Module 9: Performance Tuning of ETL Processes

Module 10: Data Warehouse Implementation and Business Intelligence

Here's What You'll Learn:

Module 1: Foundations of Quality Management and Variation

Module 2: Fundamentals of Control Charts

Module 3: Control Charts for Variable Data (I-MR, X̄-R)

Module 4: Control Charts for Variable Data (X̄-S and Advanced Techniques)

Module 5: Control Charts for Attribute Data (p and np Charts)

Module 6: Control Charts for Attribute Data (c and u Charts)

Module 7: Process Capability Analysis (Cₚ, Cₚₖ)

Module 8: Advanced Process Monitoring: Cusum and EWMA Charts

Module 9: Pre-Control and Short Run SPC Methods

Module 10: SPC Implementation, Management, and Reporting

Here's What You'll Learn:

Module 1: Foundations of Data Protection and the 3-2-1 Rule

Module 2: Backup Strategies and Implementation Methods

Module 3: Storage Technologies for Backup and Recovery

Module 4: Disaster Recovery Planning (DRP) and Business Continuity

Module 5: Data Recovery Procedures and Testing

Module 6: Data Archiving, Retention, and Compliance

Module 7: Cloud-Based Backup and Recovery Solutions

Module 8: Security and Encryption in Backup Processes

Module 9: Backup System Management and Monitoring

Module 10: Advanced Recovery Scenarios and Automation

Here's What You'll Learn:

Module 1: Introduction to Markets and Food Security

Module 2: Value Chain Analysis for Market Access

Module 3: Market Information Systems and Price Analysis

Module 4: Agricultural Marketing Strategies and Best Practices

Module 5: Post-Harvest Handling and Quality Standards for Market Access

Module 6: Financing and Risk Management in Agricultural Trade

Module 7: Trade Policies, Agreements, and Food Security

Module 8: Global Food Trade Dynamics and Trends

Module 9: Overcoming Market Access Barriers

Module 10: Designing Market-Oriented Food Security Interventions

Here's What You'll Learn:

Module 1: Foundations of Psychological Measurement and Scaling

Module 2: Classical Test Theory (CTT) and Reliability

Module 3: Validity in Measurement

Module 4: Item Analysis and Scale Development

Module 5: Introduction to Factor Analysis for Scale Validation

Module 6: Item Response Theory (IRT) Fundamentals

Module 7: Differential Item Functioning (DIF) and Measurement Bias

Module 8: Standard Setting and Score Interpretation

Module 9: Specialized Measurement Models and Techniques

Module 10: Practical Implementation and Psychometric Reporting

Here's What You'll Learn:

Module 1: Introduction to Sustainable Agriculture and Its Principles

Module 2: Soil Health and Fertility Management for Sustainability

Module 3: Sustainable Water Use and Irrigation

Module 4: Integrated Pest and Disease Management (IPM) in Sustainable Systems

Module 5: Crop Diversification and Rotation

Module 6: Agroforestry and Permaculture Design

Module 7: Organic Farming Principles and Practices

Module 8: Sustainable Livestock Integration

Module 9: Farm Energy Efficiency and Renewable Resources

Module 10: Economic Viability and Certification in Sustainable Agriculture

Here's What You'll Learn:

Module 1: Foundations of Environmental Data and R Setup

Module 2: Data Acquisition and Preprocessing with R

Module 3: Geospatial Analysis of Environmental Data

Module 4: Time Series Modeling for Environmental Monitoring

Module 5: Statistical Analysis and Modeling in R

Module 6: Advanced Machine Learning for Environmental Prediction

Module 7: Introduction to Power BI for Environmental Reporting

Module 8: Data Modeling and Advanced DAX for Metrics

Module 9: Creating Interactive Environmental Dashboards

Module 10: Environmental Data Governance and Stakeholder Communication

Here's What You'll Learn:

Module 1: Introduction to Predictive Modeling with R
Module 2: Linear Regression
Module 3: Logistic Regression
Module 4: Decision Trees
Module 5: Random Forests
Module 6: Support Vector Machines
Module 7: Clustering Techniques
Module 8: Time Series Analysis
Module 9: Ensemble Methods
Module 10: Model Deployment

Here's What You'll Learn:

Module 1: Foundations of Survey Research and Total Survey Error

Module 2: Survey Design Process and Questionnaire Development

Module 3: Crafting Effective Survey Questions and Response Formats

Module 4: Sampling Methods and Coverage Error

Module 5: Modes of Data Collection and Administration

Module 6: Measurement Error: Validity and Reliability

Module 7: Pre-testing, Cognitive Interviews, and Pilot Studies

Module 8: Data Processing, Cleaning, and Ethical Considerations

Module 9: Non-response and Weighting Adjustments

Module 10: Survey Data Analysis and Reporting Findings

Here's What You'll Learn:

Module 1: Foundations of Fraud Risk and Power BI Setup

Module 2: Data Modeling and ETL for Fraud Scenarios

Module 3: Core DAX for Financial Risk and Anomaly Metrics

Module 4: Visualization of Fraud Patterns and Red Flags

Module 5: Analytical Techniques for Transactional Fraud Detection

Module 6: Vendor, Procurement, and Accounts Payable Fraud Analysis

Module 7: Employee and Expense Report Fraud Analytics

Module 8: Advanced Analytics and AI Visuals for Predictive Fraud

Module 9: Reporting Governance and Secure Dashboard Deployment

Module 10: Integrated Fraud Detection Dashboard Capstone

Here's What You'll Learn:

Module 1: Introduction to Food Systems and Nutrition

Module 2: Environmental Sustainability of Food Systems

Module 3: Social Equity and Economic Viability in Food Systems

Module 4: Sustainable Food Production Systems

Module 5: Sustainable Food Processing and Supply Chains

Module 6: Promoting Sustainable and Healthy Diets

Module 7: Policy and Governance for Sustainable Food Systems

Module 8: Climate Change and Food Systems Resilience

Module 9: Measurement and Assessment of Sustainable Food Systems

Module 10: Designing Sustainable Food Systems Interventions

Here's What You'll Learn:

Module 1: Introduction to Time Series Data and Components

Module 2: Data Preparation and Visualization in SPSS

Module 3: Smoothing and Classical Decomposition Methods

Module 4: Introduction to Exponential Smoothing Models

Module 5: Advanced Exponential Smoothing: Holt-Winters Models

Module 6: Stationarity, Autocorrelation, and Partial Autocorrelation

Module 7: ARIMA Model Identification and Specification

Module 8: ARIMA Model Estimation and Diagnostic Checking

Module 9: Advanced Forecasting Techniques and Model Comparison

Module 10: Integrating Time Series with Regression and Reporting

Here's What You'll Learn:

Module 1: Introduction to Early Warning Systems and Food Security

Module 2: Understanding Food Security Information Systems

Module 3: Data Collection and Indicators for Early Warning

Module 4: Climate and Environmental Monitoring for Food Security

Module 5: Market and Economic Analysis for Food Security

Module 6: Conflict, Displacement, and Food Security Linkages

Module 7: Information Analysis and Interpretation for Early Warning

Module 8: Communication and Dissemination of Early Warning Information

Module 9: Linking Early Warning to Early Action

Module 10: Developing and Strengthening Early Warning Systems

Here's What You'll Learn:

Module 1: Python Fundamentals for Biomedical Data

Module 2: Data Wrangling with Pandas and NumPy

Module 3: Biostatistics and Inferential Analysis

Module 4: Clinical Data Processing and EHR Analysis

Module 5: Introduction to Genomics and Bioinformatics Data

Module 6: Statistical Modeling for Healthcare Outcomes

Module 7: Machine Learning for Diagnostics and Prognostics

Module 8: Survival Analysis and Time-to-Event Modeling

Module 9: Data Visualization with Matplotlib and Seaborn

Module 10: Geospatial and Epidemiology Data Analysis

Module 11: Power BI Desktop Fundamentals and Data Loading

Module 12: Data Transformation with Power Query (M Language)

Module 13: Designing Robust Data Models in Power BI

Module 14: Introduction to DAX (Data Analysis Expressions)

Module 15: Advanced Power BI Visualizations for Healthcare

Module 16: Creating Interactive Dashboards for Healthcare Performance

Module 17: Integrating Python Scripts and Models into Power BI

Module 18: Ethical AI, Data Governance, and Deployment

Here's What You'll Learn:

Module 1: Foundations of Research Ethics

Module 2: Informed Consent and Participant Protection

Module 3: Privacy, Confidentiality, and Data Security

Module 4: Data Management and Sharing

Module 5: Authorship and Intellectual Property

Module 6: Peer Review Ethics

Module 7: Research Misconduct

Module 8: Conflict of Interest in Research

Module 9: Responsible Use of Animals in Research

Module 10: Responsible Conduct in Collaborative Research and Emerging Areas

Here's What You'll Learn:

Module 1: Foundations of Sampling and Statistical Inference

Module 2: Simple Random Sampling (SRS) and Estimation

Module 3: Systematic and Cluster Sampling Techniques

Module 4: Stratified Random Sampling

Module 5: Complex Survey Designs: Multi-Stage and Multi-Phase

Module 6: Probability Proportional to Size (PPS) Sampling

Module 7: Non-Probability Sampling Methods and Limitations

Module 8: Sample Size Determination and Power Analysis

Module 9: Bias, Non-response, and Weighting Adjustments

Module 10: Designing a Comprehensive Sampling Plan

Here’s What You’ll Learn:

Module 1: Introduction to Payroll Management and Kenyan Statutory Deductions

Module 2: Understanding the Legal and Regulatory Framework for Payroll in Kenya

Module 3: Setting Up and Managing Employee Records for Payroll in Kenya

Module 4: Calculating Gross Pay and Allowances in Kenya

Module 5: Calculating and Remitting Pay As You Earn (PAYE) in Kenya

Module 6: Calculating and Remitting National Social Security Fund (NSSF) Contributions in Kenya

Module 7: Calculating and Remitting National Hospital Insurance Fund (NHIF) Contributions in Kenya

Module 8: Other Statutory and Voluntary Deductions in Kenya

Module 9: Payroll Processing, Reporting, and Record Keeping in Kenya

Module 10: Best Practices and Emerging Trends in Payroll Management in Kenya

Here's What You'll Learn:

Module 1: Introduction to Agricultural Marketing and Value Chains

Module 2: Market Analysis and Demand Assessment

Module 3: Post-Harvest Management and Quality Control

Module 4: Value Addition and Product Development

Module 5: Market Channels and Distribution Strategies

Module 6: Pricing Strategies and Market Information Systems

Module 7: Contract Farming and Producer Organizations

Module 8: Digital Marketing and E-commerce in Agriculture

Module 9: Food Safety Standards and Certifications

Module 10: Financing Agricultural Value Chains and Risk Management

Here's What You'll Learn:

Module 1: Principles of Clear and Effective Scientific Writing

Module 2: Structuring Different Types of Scientific Manuscripts

Module 3: Writing Compelling Introductions and Methods

Module 4: Presenting Results Effectively

Module 5: Writing Insightful Discussions and Conclusions

Module 6: Journal Selection and the Submission Process

Module 7: Navigating Peer Review and Responding to Reviewers

Module 8: Ethical Considerations in Scientific Publication

Module 9: Writing Impactful Abstracts and Cover Letters

Module 10: Enhancing Publication Impact and Visibility

Here’s What You’ll Learn:

Module 1: Foundations of Forensic Accounting

Module 2: Fraud Schemes and Typologies

Module 3: The Fraud Investigation Process

Module 4: Gathering and Analyzing Evidence

Module 5: Interviewing and Interrogation Techniques

Module 6: Digital Forensics and Cybercrime

Module 7: Reporting and Communicating Findings

Module 8: Legal Aspects of Fraud Examination

Module 9: Prevention and Internal Controls

Module 10: Capstone Project: Mock Fraud Investigation

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: Foundations of Corporate Finance

Module 2: The Time Value of Money

Module 3: Sources of Long-Term Finance

Module 4: Sources of Short-Term Finance

Module 5: Introduction to Capital Structure

Module 6: Theories of Capital Structure

Module 7: Cost of Capital

Module 8: Working Capital Management

Module 9: Capital Budgeting and Investment Decisions

Module 10: Capstone Project: Developing a Capital Structure Plan

Here's What You'll Learn:

Module 1: Fundamentals of Climate Science and Modeling

Module 2: Types and Scales of Climate Models

Module 3: Climate Data Sources and Downscaling Techniques

Module 4: Understanding Climate Scenarios and Emissions Pathways

Module 5: Impact Modeling and Sectoral Applications

Module 6: Uncertainty and Limitations in Climate Projections

Module 7: Communicating Climate Model Outputs

Module 8: Integrating Climate Scenarios into Decision-Making

Module 9: Practical Application of Climate Modeling Tools

Module 10: Developing Custom Climate Scenarios for Planning

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: Introduction to CRM Data Analytics
• Module 2: Data Visualization with PowerBI
• Module 3: Advanced Analytics Techniques
• Module 4: Marketing Performance Measurement
• Module 5: Customer Segmentation and Targeting
• Module 6: Data-Driven Decision Making
• Module 7: CRM Data Integration
• Module 8: PowerBI Best Practices
• Module 9: Case Studies and Real-Life Applications
• Module 10: Future Trends in CRM Data Analytics

Here's What You'll Learn:

Module 1: Foundational Data Ecosystems in Oil and Gas

Module 2: Python Fundamentals for Data Ingestion and Wrangling

Module 3: Specialized Data Handling (Time-Series, Well Logs, Seismic)

Module 4: Data Quality, Cleaning, and Feature Engineering with Pandas

Module 5: Automated Reporting and Scripting with Python

Module 6: PowerBI Architecture and Advanced Data Modeling

Module 7: Mastering Data Analysis Expressions (DAX)

Module 8: Geospatial and Visual Analytics for Petroleum Data

Module 9: Designing Interactive and Actionable Business Dashboards

Module 10: Deployment, Security, and Governance

Here's What You'll Learn:

Module 1: Introduction to Climate Change and Policy in Kenya

Module 2: Understanding Kenya's Climate Change Act and Policy Frameworks

Module 3: Institutions and Governance Structures for Climate Action in Kenya

Module 4: Kenya's Nationally Determined Contributions (NDCs) and International Commitments

Module 5: Climate Finance Landscape in Kenya

Module 6: Sectoral Climate Policies and Strategies in Kenya

Module 7: Mainstreaming Climate Change into Development Planning

Module 8: Community-Based Adaptation and Local Climate Action in Kenya

Module 9: Monitoring, Reporting, and Verification (MRV) for Climate Action in Kenya

Module 10: Advocating for Effective Climate Policy and Governance in Kenya

Here's What You'll Learn:

Module 1: Understanding Climate Change and Disaster Risk

Module 2: The Disaster Risk Reduction Framework

Module 3: Vulnerability and Risk Assessment

Module 4: Climate Change Adaptation Strategies

Module 5: Ecosystem-Based Disaster Risk Reduction (Eco-DRR)

Module 6: Early Warning Systems and Communication for DRR

Module 7: Climate-Resilient Infrastructure and Planning

Module 8: Financing Climate Change Adaptation and DRR

Module 9: Governance and Policy for Climate and Disaster Resilience

Module 10: Integrating Climate Change and DRR for Resilient Development

Here's What You'll Learn:

Module 1: Introduction to Food Policy and Governance

Module 2: The Policy Cycle and Food Security

Module 3: National Food Security Strategies and Plans

Module 4: Role of Different Actors in Food Governance

Module 5: Legal and Regulatory Frameworks for Food Security

Module 6: Land, Water, and Natural Resource Governance

Module 7: Trade, Markets, and Food Policy

Module 8: Climate Change, Disasters, and Food Governance

Module 9: Monitoring, Evaluation, and Accountability in Food Policy

Module 10: Designing and Advocating for Effective Food Policies

Here's What You'll Learn:

Module 1: Foundations of Multivariate Analysis and Data Screening in SPSS

Module 2: Multiple Linear Regression and Model Building in SPSS

Module 3: Binary Logistic Regression Analysis in SPSS

Module 4: Multivariate Analysis of Variance (MANOVA) in SPSS

Module 5: Discriminant Function Analysis (DFA) using SPSS

Module 6: Exploratory Factor Analysis (EFA) and Dimensionality Reduction in SPSS

Module 7: Cluster Analysis and Market Segmentation in SPSS

Module 8: Introduction to Survival Analysis (Cox Regression) in SPSS

Module 9: Repeated Measures ANOVA and Mixed Models in SPSS

Module 10: Advanced Reporting, Interpretation, and Presentation of Results

Here's What You'll Learn:

Module 1: Foundations of Research Project Management

Module 2: Research Project Planning and Scheduling

Module 3: Budgeting and Financial Management

Module 4: Team Leadership and Human Resource Management

Module 5: Data Management and Quality Control

Module 6: Monitoring, Evaluation and Reporting

Module 7: Ethics, Compliance and Risk Management

Module 8: Communication and Stakeholder Engagement

Module 9: Agile and Adaptive Research Approaches

Module 10: Project Closure and Dissemination

Here's What You'll Learn:

Module 1: Foundations of Emotional Intelligence

Module 2: Self-Awareness: The First Pillar

Module 3: Self-Regulation: Managing Your Emotions

Module 4: Social Awareness: Empathy and Perspective

Module 5: Relationship Management: The Art of Connection

Module 6: Emotional Intelligence in the Workplace

Module 7: Conflict Resolution and Difficult Conversations

Module 8: Leadership and Emotional Intelligence

Module 9: Building Emotional Resilience

Module 10: Creating Your Personal EQ Action Plan

Here's What You'll Learn:

Module 1: Introduction to Medical Data Analysis & R Setup

Module 2: R Fundamentals and Data Import for Healthcare Data

Module 3: Data Wrangling in R using the tidyverse

Module 4: Descriptive Statistics and Data Summarization in Medical Context

Module 5: Basic Biostatistics in R (Hypothesis Testing)

Module 6: Introduction to Regression Models in Medical Research

Module 7: Survival Analysis Fundamentals and Implementation in R

Module 8: Data Visualization for Medical Research using ggplot2

Module 9: Introduction to Power BI for Data Integration

Module 10: Connecting, Importing, and Transforming Medical Data in Power BI

Module 11: Data Modeling and Relationships in Power BI

Module 12: Introduction to DAX for Advanced Calculations

Module 13: Creating Interactive Dashboards in Power BI

Module 14: Visualization Best Practices for Medical Reporting

Module 15: Incorporating R Visuals and Scripts into Power BI

Module 16: Ethics, Data Governance, and Reproducible Research

Module 17: Advanced Power BI: Security and Distribution

Module 18: Capstone Project: End-to-End Medical Analytics Workflow

Module 1: Foundations of Statistics and Data Types

Module 2: Descriptive Statistics and Data Visualization

Module 3: Probability and Theoretical Distributions

Module 4: Sampling Methods and Statistical Estimation

Module 5: Principles of Hypothesis Testing

Module 6: Comparative Analysis: t-Tests and ANOVA

Module 7: Introduction to Correlation and Simple Linear Regression

Module 8: Non-Parametric Statistical Methods

Module 9: Fundamentals of Time Series and Index Numbers

Module 10: Statistical Software Application and Reporting

Here’s What You’ll Learn:

Module 1: Introduction to Taxation Principles and the Kenyan Tax System

Module 2: Income Tax in Kenya: Individuals and Corporations

Module 3: Value Added Tax (VAT) in Kenya: Principles and Application

Module 4: Excise Duty in Kenya: Scope and Administration

Module 5: Customs Duty and Import/Export Taxes in Kenya

Module 6: Tax Administration and Procedures in Kenya: KRA and Taxpayer Obligations

Module 7: Tax Planning and Compliance in Kenya

Module 8: Tax Offences, Penalties, and Dispute Resolution in Kenya

Module 9: Emerging Issues and Trends in Kenyan Taxation

Module 10: Practical Application and Case Studies in Kenyan Taxation

Here's What You'll Learn:

Module 1: Foundations of Industrial Data and Python Environment Setup

Module 2: Python Fundamentals for Industrial Data Processing (Pandas)

Module 3: Time Series Analysis of Sensor Data (Resampling and Filtering)

Module 4: Advanced Data Preprocessing and Feature Engineering

Module 5: Descriptive and Exploratory Data Analysis in Python

Module 6: Statistical Process Control (SPC) and Anomaly Detection

Module 7: Predictive Maintenance: Classification Models in Python

Module 8: Regression Models for Process Optimization

Module 9: Introduction to Power BI for Data Connection

Module 10: Data Transformation and M-Query for Industrial Data

Module 11: Data Modeling for Manufacturing and IoT Datasets

Module 12: DAX Fundamentals for Calculating Operational Metrics

Module 13: Creating Interactive Performance Dashboards in Power BI

Module 14: Integrating Python Visuals and Scripts into Power BI

Module 15: Root Cause Analysis and Drill-Through Reporting

Module 16: Data Security and Governance in Industrial Analytics

Module 17: Automating Data Pipelines and Dashboard Deployment

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

Here's What You'll Learn:

Module 1: Foundations of Corporate Finance

Module 2: Capital Budgeting Techniques

Module 3: Cost of Capital

Module 4: Financial Statement Analysis

Module 5: Business Valuation: Discounted Cash Flow (DCF) Method

Module 6: Business Valuation: Multiples-Based Valuation

Module 7: Mergers and Acquisitions (M&A)

Module 8: Capital Structure Decisions

Module 9: Dividend Policy

Module 10: Risk Management and Financial Planning

Here's What You'll Learn:

Module 1: Introduction to Epidemiological Data Science

Module 2: Python Fundamentals for Public Health Data

Module 3: Epidemiological Data Acquisition and Cleaning

Module 4: Visualization and Exploratory Data Analysis (EDA)

Module 5: Classic Compartmental Modeling (SIR/SEIR)

Module 6: Time Series Forecasting for Incidence Rates

Module 7: Machine Learning for Outbreak Prediction

Module 8: Geospatial Epidemiology and Spatial Analysis

Module 9: Model Validation, Uncertainty, and Interpretation

Module 10: Communicating Forecasts and Policy Integration

Here's What You'll Learn:

Module 1: Foundations and Principles of Epidemiology

Module 2: Measures of Disease Occurrence and Association

Module 3: Study Design: Observational Studies (Cross-Sectional and Case-Control)

Module 4: Study Design: Cohort and Intervention Studies (Trials)

Module 5: Addressing Bias, Confounding, and Effect Modification

Module 6: Public Health Surveillance and Outbreak Investigation

Module 7: Introduction to Regression Modeling in Epidemiology

Module 8: Causal Inference and Advanced Analytical Techniques

Module 9: Validity, Reliability, and Survey Instrument Design

Module 10: Ethical Issues, Communication, and Proposal Development

Here's What You'll Learn:

Module 1: Introduction to Epidemic Preparedness

Module 2: Data Management with R

Module 3: Descriptive Statistics in R

Module 4: Inferential Statistics in R

Module 5: Data Visualization with R

Module 6: Introduction to Tableau

Module 7: Advanced Tableau Visualizations

Module 8: Integrating R and Tableau

Module 9: Time Series Analysis in R

Module 10: Geospatial Analysis in Tableau

Module 11: Machine Learning Basics with R

Module 12: Predictive Modeling in R

Module 13: Advanced Analytics with R

Module 14: Tableau Server and Online

Module 15: Data Storytelling with Tableau

Module 16: Real-world Case Studies

Module 17: Best Practices in Data Analysis

Module 18: Course Wrap-up and Review

Here's What You'll Learn:

Module 1: Introduction to Gender and Food Security

Module 2: Gendered Roles and Responsibilities in Food Systems

Module 3: Gender and Access to Productive Resources

Module 4: Gender, Food Consumption, and Nutrition

Module 5: Women's Empowerment and Food Security Outcomes

Module 6: Gender Analysis in Food Security Programming

Module 7: Gender-Responsive Food Security Policies and Governance

Module 8: Gender, Climate Change, and Food Security

Module 9: Monitoring, Evaluation, and Learning for Gender-Transformative Food Security

Module 10: Designing Gender-Transformative Food Security Interventions

Here's What You'll Learn:

Module 1: Foundational Concepts in Programme Evaluation

Module 2: Logic Models, Theory of Change, and Evaluation Questions

Module 3: Choosing the Right Impact Evaluation Design and Counterfactuals

Module 4: Data Collection, Quality Assurance, and Introduction to Statistical Software

Module 5: Non-Experimental Methods: Propensity Score Matching (PSM)

Module 6: Quasi-Experimental Methods: Difference-in-Differences (DiD)

Module 7: Experimental Methods: Randomized Control Trials (RCTs)

Module 8: Advanced Data Analysis: Regression Analysis and Treatment Heterogeneity

Module 9: Integrating Qualitative Data and Mixed-Methods Evaluation

Module 10: Reporting, Dissemination, and Utilization of Evaluation Findings

Here's What You'll Learn:

Module 1: Introduction to Statistics and Inference

Module 2: Probability Distributions and Estimation

Module 3: Fundamentals of Hypothesis Testing

Module 4: One-Sample Hypothesis Tests

Module 5: Two-Sample Hypothesis Tests

Module 6: Analysis of Variance (ANOVA)

Module 7: Non-Parametric Tests

Module 8: Chi-Square Tests and Association

Module 9: Simple Linear Regression

Module 10: Advanced Topics and Model Selection

Here's What You'll Learn:

Module 1: Foundations of Renewable Energy and Data  

Module 2: Python Environment Setup and Fundamentals  

Module 3: Data Acquisition and Cleaning for Energy Datasets  

Module 4: Exploratory Data Analysis (EDA) of Solar PV Data  

Module 5: Wind Energy Resource Assessment and Data Preparation  

Module 6: Advanced Time Series Analysis for Energy Data  

Module 7: Introduction to Machine Learning for Renewables  

Module 8: Predictive Modeling for Energy Output Forecasting  

Module 9: Power BI Desktop and Data Modeling Fundamentals  

Module 10: Creating Interactive Solar PV Dashboards in Power BI  

Module 11: Advanced DAX and Calculated Measures  

Module 12: Geospatial Analytics of Renewable Assets  

Module 13: Predictive Maintenance Analytics for Wind Turbines  

Module 14: Financial Modeling and Levelized Cost of Energy (LCOE)  

Module 15: Grid Impact Analysis and Load Profile Modeling  

Module 16: Optimization and Scenario Analysis in Renewable Projects  

Module 17: Capstone Project: End-to-End Analytics Workflow  

Module 18: Communicating Insights and Data Storytelling

Module 1: Overview of Petroleum Exploration and Production Agreements
Module 2: Key Legal and Regulatory Frameworks
Module 3: Fiscal Regimes in Petroleum Contracts
Module 4: Key Commercial Terms and Negotiations
Module 5: Risk Allocation and Liability
Module 6: Environmental Considerations and Sustainability
Module 7: Local Content and Socio-Economic Impact
Module 8: Joint Operating Agreements (JOAs)
Module 9: Production Sharing Contracts (PSCs) in Detail
Module 10: Contract Management and Dispute Resolution

Here's What You'll Learn:

Module 1: Fundamentals of Food Safety and Quality

Module 2: Good Manufacturing Practices (GMP) and Good Hygiene Practices (GHP)

Module 3: Hazard Analysis and Critical Control Points (HACCP) System

Module 4: Food Safety Management Systems (FSMS) and ISO 22000

Module 5: Food Microbiology and Contaminants

Module 6: Food Allergens and Labeling Requirements

Module 7: Traceability and Recall Procedures

Module 8: Food Safety Auditing and Regulatory Compliance

Module 9: Quality Assurance Tools and Techniques

Module 10: Developing and Implementing a Food Safety and Quality Plan

Here's What You'll Learn:

Module 1: Introduction to Food Security Concepts

Module 2: The Four Pillars of Food Security

Module 3: Measuring and Monitoring Food Insecurity

Module 4: Drivers of Food Insecurity

Module 5: Food Systems Approach to Food Security

Module 6: Policies and Governance for Food Security

Module 7: Climate Change and Food Security

Module 8: Emergency Food Security and Humanitarian Response

Module 9: Sustainable Food Production Systems

Module 10: Developing Food Security Interventions and Strategies

Here's What You'll Learn:

Module 1: Understanding Climate Change and Its Impacts

Module 2: Principles of Effective Climate Communication

Module 3: Audience Analysis and Segmentation for Climate Action

Module 4: Crafting Compelling Climate Messages

Module 5: Communication Channels and Tools for Climate Awareness

Module 6: Engaging Stakeholders and Building Partnerships

Module 7: Addressing Misinformation and Climate Denial

Module 8: Storytelling and Narrative Building for Climate Change

Module 9: Measuring the Impact of Climate Communication

Module 10: Developing a Climate Communication Strategy

Here's What You'll Learn:

Module 1: Fundamentals of Data and the Data Lifecycle

Module 2: Data Collection Methods and Tools

Module 3: Data Collection Planning and Ethics

Module 4: Introduction to Data Cleaning

Module 5: Handling Missing Data

Module 6: Dealing with Inconsistent and Erroneous Data

Module 7: Data Validation and Quality Assurance

Module 8: Automating Data Cleaning Workflows

Module 9: Introduction to Data Visualization

Module 10: Project-Based Application: End-to-End Data Pipeline

Here's What You'll Learn:

Module 1: Foundations of Effective Communication

Module 2: Mastering Verbal Communication

Module 3: Non-Verbal and Listening Skills

Module 4: Communicating with Confidence and Assertiveness

Module 5: Interpersonal Communication and Emotional Intelligence

Module 6: Business Writing and Digital Communication

Module 7: Delivering Powerful Presentations

Module 8: Conflict Resolution and Difficult Conversations

Module 9: Cross-Cultural Communication

Module 10: Building and Maintaining Professional Relationships

Here's What You'll Learn:

Module 1: Introduction to R and RStudio

Module 2: Data Wrangling with dplyr and tidyr

Module 3: Exploratory Data Analysis and Visualization

Module 4: Descriptive Statistics and Data Summarization

Module 5: Hypothesis Testing and t-Tests

Module 6: ANOVA and Chi-Squared Tests

Module 7: Linear Regression Analysis

Module 8: Multiple Regression and Model Diagnostics

Module 9: Introduction to Time Series Analysis

Module 10: Building an End-to-End Statistical Project

Here's What You'll Learn:

Module 1: Introduction to Mixed-Methods Philosophy and Rationale

Module 2: Core Mixed-Methods Designs (Typology)

Module 3: Convergent Parallel Design (Triangulation)

Module 4: Explanatory Sequential Design (QUAN  QUAL)

Module 5: Exploratory Sequential Design (QUAL  QUAN)

Module 6: Sampling in Mixed-Methods Research

Module 7: Data Integration and Mixing Strategies

Module 8: Validity and Rigor in Mixed-Methods

Module 9: Analysis of Mixed-Methods Data

Module 10: Writing and Disseminating Mixed-Methods Findings

Here's What You'll Learn:

Module 1: Introduction to Research and the Research Process

Module 2: Formulating Research Questions and Hypotheses

Module 3: Quantitative Research Designs

Module 4: Qualitative Research Designs

Module 5: Mixed Methods Research

Module 6: Sampling Techniques

Module 7: Data Collection Methods

Module 8: Basics of Data Analysis (Quantitative)

Module 9: Basics of Data Analysis (Qualitative)

Module 10: Research Ethics and Writing Research Proposals/Reports

Here's What You'll Learn:

Module 1: Foundations of Metadata and Data Governance

Module 2: Metadata Architecture, Models, and Standards

Module 3: Data Cataloging Principles and Tool Selection

Module 4: Automated Metadata Capture and Data Discovery

Module 5: Implementing Data Quality and Data Stewardship

Module 6: Business Glossary, Taxonomy, and Data Definitions

Module 7: Understanding and Mapping Data Lineage

Module 8: Technical Metadata and Integration with Data Sources

Module 9: Operationalizing the Data Catalog and Search

Module 10: Metadata Management Strategy and Roadmap

Here’s What You’ll Learn:

Module 1: Foundations of Credit and Lending

Module 2: Understanding Financial Statements for Credit Analysis

Module 3: Ratio Analysis and Financial Performance Evaluation

Module 4: Assessing Borrower Character and Repayment Capacity

Module 5: Collateral Evaluation and Security Documentation

Module 6: Loan Structuring and Pricing

Module 7: Credit Risk Assessment and Grading

Module 8: Loan Documentation and Legal Aspects of Lending

Module 9: Loan Monitoring and Problem Loan Management

Module 10: Regulatory and Compliance in Lending

Here's What You'll Learn:

Module 1: Foundations and Philosophical Paradigms in Qualitative Research

Module 2: Qualitative Research Design, Ethics, and Planning

Module 3: In-Depth Interviewing and Elicitation Techniques

Module 4: Focus Group Discussions (FGDs) and Group Dynamics

Module 5: Ethnography, Observation, and Fieldwork Methods

Module 6: Purposeful Sampling Strategies and Participant Selection

Module 7: Data Transcription, Memoing, and Software Preparation

Module 8: Thematic Analysis (TA) in Practice

Module 9: Advanced Qualitative Analysis Methodologies

Module 10: Ensuring Trustworthiness and Reporting Findings

Module 1: Introduction to Public Sector Accounting and IPSAS

Module 2: Core IPSAS Standards - Presentation of Financial Statements

Module 3: Core IPSAS Standards - Assets

Module 4: Core IPSAS Standards - Liabilities and Equity

Module 5: Core IPSAS Standards - Financial Instruments

Module 6: Specific Public Sector Issues under IPSAS

Module 7: Transition to IPSAS Accrual Accounting

Module 8: Budgeting and Financial Reporting under IPSAS

Module 9: Current Developments and Interpretations of IPSAS

Module 10: Practical Application and Case Studies in the Kenyan Public 

Here's What You'll Learn:

Module 1: Understanding Post-Harvest Loss and Food Waste

Module 2: Causes and Hotspots of Post-Harvest Loss

Module 3: Post-Harvest Technologies for Cereals and Grains

Module 4: Post-Harvest Technologies for Fruits, Vegetables, and Perishables

Module 5: Food Processing and Value Addition for Waste Reduction

Module 6: Sustainable Packaging and Cold Chain Management

Module 7: Addressing Food Waste at Retail and Consumer Levels

Module 8: Policy, Governance, and Legal Frameworks for PHL/FW Reduction

Module 9: Measurement, Monitoring, and Reporting of PHL/FW

Module 10: Designing and Implementing PHL/FW Reduction Programs

Here's What You'll Learn:

Module 1: Introduction to Clinical Research and Study Designs

Module 2: Ethical Considerations and Regulatory Frameworks in Clinical Research

Module 3: Principles of Clinical Trial Design

Module 4: Data Management in Clinical Research Using Stata

Module 5: Descriptive Statistics and Graphical Methods for Clinical Data in Stata

Module 6: Hypothesis Testing for Comparing Groups in Clinical Research Using Stata

Module 7: Linear Regression Analysis for Clinical Data Using Stata

Module 8: Logistic Regression Analysis for Clinical Data Using Stata

Module 9: Survival Analysis for Time-to-Event Data Using Stata

Module 10: Analysis of Correlated Data in Clinical Research Using Stata

Module 11: Handling Missing Data in Clinical Research Using Stata

Module 12: Interpreting Statistical Output and Drawing Conclusions in Clinical Research

Module 13: Meta-Analysis: Principles and Application in Stata

Module 14: Statistical Programming in Stata for Clinical Research: Introduction to Do-Files

Module 15: Advanced Regression Techniques in Clinical Research Using Stata

Module 16: Causal Inference in Clinical Research: Introduction to Potential Outcomes Framework

Module 17: Analysis of Clustered and Multilevel Data in Clinical Research Using Stata

Module 18: Reporting Statistical Results in Clinical Research Manuscripts and Presentations

Here's What You'll Learn:

Module 1: Fundamentals of Experimentation and Key Terminology

Module 2: Simple Comparative Experiments and Hypothesis Testing

Module 3: Introduction to Factorial Designs

Module 4: The 2ᵏ Factorial Design: Screening for Effects

Module 5: Blocking and Confounding in Factorial Designs

Module 6: Fractional Factorial Designs

Module 7: Response Surface Methodology (RSM)

Module 8: Analysis of Covariance (ANCOVA) in Experimental Design

Module 9: Robust Parameter Design and Taguchi Methods

Module 10: Case Studies and Industrial Applications of DOE

Here's What You'll Learn:

• Survey Data Basics: Overview, SPSS introduction, data import, descriptive statistics.
• Data Cleaning: Handling missing data, transformation, validation, data file management.
• Descriptive Statistics & Visualization: Measures of central tendency and dispersion, frequency distributions, data visualization.
• Inferential Statistics: Hypothesis testing, t-tests, ANOVA, Chi-square tests, non-parametric tests.
• Correlation & Regression: Correlation analysis, simple and multiple linear regression, assumptions.
• Advanced Techniques: Factor analysis, cluster analysis, discriminant analysis, logistic regression.
• Data Interpretation & Presentation: Interpreting results, creating tables and figures, writing reports, presentations.
• Survey Weighting: Introduction, applying weights, adjusting for bias, analyzing weighted data.
• Data Quality Assessment: Assessing quality, handling outliers, reliability and validity, ethical considerations.
• Reporting & Dissemination: Writing reports, communicating results, using visuals, ethical reporting.