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: 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: 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

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

Module 1: Introduction to Livestock Management and Health

Module 2: Animal Anatomy, Physiology, and Nutrition

Module 3: Livestock Breeding Systems and Genetic Improvement

Module 4: Common Livestock Diseases in Kenya

Module 5: Livestock Disease Prevention and Biosecurity

Module 6: Livestock Feeding and Ration Formulation

Module 7: Reproductive Management in Livestock

Module 8: Housing and Handling of Livestock

Module 9: Livestock Production Economics and Marketing

Module 10: Modern Technologies in Livestock Management

Module 1: Geospatial Data Foundations and Python for GIS

Module 2: Advanced Remote Sensing Data Pre-processing

Module 3: Feature Engineering for Geospatial Data

Module 4: Fundamentals of Traditional Machine Learning

Module 5: Supervised Classification: Model Selection and Training

Module 6: Unsupervised Clustering and Segmentation

Module 7: Introduction to Deep Learning and Neural Networks

Module 8: Convolutional Neural Networks (CNNs) for Imagery

Module 9: Semantic Segmentation for Land Cover Mapping

Module 10: Object Detection in High-Resolution Imagery

Module 11: Time-Series Analysis and Change Detection

Module 12: Model Evaluation and Spatial Accuracy Assessment

Module 13: Advanced Vector Data Machine Learning

Module 14: Integrating Lidar Data with Deep Learning

Module 15: Cloud Computing for Machine Learning Remote Sensing

Module 16: Operationalizing and Deploying Geospatial Models

Module 17: Geospatial Ethics and Bias in Satellite Imagery

Module 18: Capstone Project: End-to-End Geospatial AI Solution

Here's What You'll Learn:

Module 1: Fundamentals of Climate Change and Risk

Module 2: Principles of Climate Risk Assessment

Module 3: Data Collection and Analysis for Vulnerability

Module 4: Assessing Exposure and Sensitivity

Module 5: Evaluating Adaptive Capacity

Module 6: Integrated Climate Risk and Vulnerability Mapping

Module 7: Sectoral Climate Risk Assessment

Module 8: Communicating Climate Risk and Engaging Stakeholders

Module 9: Mainstreaming Climate Risk into Planning

Module 10: Tools and Technologies for Climate Risk Analysis

Here’s What You’ll Learn:

Module 1: Foundations of AI in the Hospitality Industry

Module 2: AI-Driven Revenue Management and Dynamic Pricing

Module 3: Hyper-Personalization and the Modern Guest Journey

Module 4: NLP and AI Chatbots for Guest Support

Module 5: Predictive Analytics for Occupancy and Staffing

Module 6: Computer Vision and IoT for Smart Hotel Operations

Module 7: AI in Food and Beverage (F&B) Optimization

Module 8: Sentiment Analysis and Reputation Management

Module 9: Hyper-Targeted Marketing and Loyalty AI

Module 10: AI Ethics, Privacy, and Human-AI Synergy

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

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: 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: The AI-Driven Retail Revolution

Module 2: Data Engineering for Customer Insights

Module 3: Building Sophisticated Recommendation Engines

Module 4: Predictive Analytics for Demand Forecasting

Module 5: Dynamic Pricing and Markdown Optimization

Module 6: Computer Vision in Physical Retail

Module 7: Conversational AI and Virtual Shopping Assistants

Module 8: Hyper-Personalization in Digital Marketing

Module 9: Supply Chain and Inventory Intelligence

Module 10: AI Ethics, Privacy, and Future Trends

Here's What You'll Learn:

Module 1: Introduction to AI and Precision Agriculture

Module 2: Data Acquisition: IoT Sensors and Farm Telemetry

Module 3: Computer Vision for Crop Health Monitoring

Module 4: Machine Learning for Yield Prediction and Forecasting

Module 5: AI-Driven Irrigation and Nutrient Management

Module 6: Drone Technology and Aerial Image Analytics

Module 7: Satellite Remote Sensing and GIS Integration

Module 8: Autonomous Farm Machinery and Robotics

Module 9: Climate Adaptation and Predictive Weather Modeling

Module 10: AI Ethics, Data Governance, and Sustainability