Program Details & Curriculum
Everything you need to know before enrolling. Explore each program below.
Data Analytics (Excel + Power BI)
This program takes you from spreadsheet fundamentals to building interactive dashboards in Power BI. You will work with datasets from health, finance, agriculture, logistics, and NGO contexts, building a portfolio of real projects along the way.
Who is this for?
Program officers, M&E Assistants, Administrative staff, Recent Graduates, and anyone looking to transition into a Data Analytics role. No prior experience required.
What You Will Learn:
- Data cleaning, transformation, and validation in Excel
- Pivot tables, advanced formulas (INDEX MATCH, XLOOKUP, array formulas)
- Building interactive dashboards in Power BI
- DAX measures and calculated columns
- Data modelling and relationships
- Storytelling with data and report design
- Capstone project with real sector datasets
Week by Week Curriculum
- Introduction to Data Analytics and Excel Foundations
- Data Cleaning, Formatting, and Validation
- Pivot Tables and Advanced Excel Functions
- Dashboard Design in Excel
- Introduction to Power BI and Data Import
- Data Modelling, Relationships, and DAX Basics
- Building Interactive Reports and Visuals
- Advanced DAX and Calculated Measures
- Storytelling, Design Best Practices, and Publishing
- Capstone Project Presentation and Portfolio Review
Delivery Format
- Live virtual sessions (2 sessions per week, 2 hours each)
- Recorded session replays for review
- Weekly assignments using datasets from health, government, NGO, finance, agriculture, HR, logistics, academia, and private sector contexts
- Dedicated WhatsApp group for peer support and instructor Q&A
- Portfolio ready capstone project
SQL for Data Analysis
Learn to query, filter, join, and aggregate data directly from databases. This program covers everything from basic SELECT statements to complex analytical queries used across health information systems, financial databases, logistics platforms, and research datasets.
Who is this for?
Aspiring data analysts, M&E Officers, IT support staff, Researchers, and Professionals who work with databases or want to add SQL to their Analytics toolkit.
What You Will Learn:
- Database concepts and relational data structures
- SELECT, WHERE, ORDER BY, and filtering
- Aggregate functions (COUNT, SUM, AVG, GROUP BY)
- JOINs (INNER, LEFT, RIGHT, FULL)
- Subqueries and Common Table Expressions (CTEs)
- Window functions and ranking
- Data extraction for reporting and BI tools
- Writing efficient queries for large datasets
Week by Week Curriculum
- Introduction to Databases and SQL Syntax
- Filtering, Sorting, and Basic Queries
- Aggregate Functions and GROUP BY
- JOINs and Multi Table Queries
- Subqueries and Nested Queries
- CTEs and Window Functions
- Data Extraction and Reporting Queries
- Capstone: End to End Database Analysis Project
Data Science (R or Python)
A rigorous program covering statistical analysis, data wrangling, machine learning, and predictive modelling. You will choose either R or Python as your primary language and work on projects spanning public health surveillance, agricultural yield prediction, financial forecasting, and programme evaluation.
Who is this for?
Working professionals with basic analytics skills who want to move into data science, researchers, epidemiologists, economists, and anyone aiming to build predictive models and conduct advanced statistical analysis.
What You Will Learn:
- Programming fundamentals in R or Python
- Data wrangling and transformation (dplyr/tidyverse or pandas)
- Exploratory data analysis and visualization
- Statistical inference and hypothesis testing
- Regression analysis (linear and logistic)
- Machine learning (classification, clustering, decision trees)
- Model evaluation and validation
- Reproducible research and reporting (R Markdown / Jupyter)
Week by Week Curriculum
- Programming Foundations (R or Python)
- Data Import, Cleaning, and Transformation
- Exploratory Data Analysis and Visualization
- Descriptive Statistics and Probability
- Statistical Inference and Hypothesis Testing
- Linear Regression and Predictive Modelling
- Logistic Regression and Classification
- Machine Learning: Trees, Forests, and Clustering
- Model Evaluation, Tuning, and Cross Validation
- Time Series and Trend Analysis
- Reproducible Reporting and Deployment
- Capstone Project Presentation
MERL Professional Program
A comprehensive program on Monitoring, Evaluation, Research, and Learning. Designed for development professionals, this program covers logical frameworks, indicator development, evaluation design, data quality assurance, and adaptive management across government, health, NGO, and private sector contexts.
Who is this for?
M&E officers, programme managers, development practitioners, researchers, government planning officers, and NGO staff involved in programme design, reporting, or accountability.
What You Will Learn
- Results frameworks and theories of change
- Indicator development and target setting
- Data collection methods and tools (KoboToolbox, ODK)
- Data quality assurance and audit processes
- Programme evaluation design (process, outcome, impact)
- Quantitative and qualitative analysis for M&E
- Reporting, dashboards, and data use for decision making
- Adaptive management and learning systems
Week by Week Curriculum
- Foundations of M&E and Programme Theory
- Logical Frameworks and Results Chains
- Indicator Development and Performance Tracking
- Data Collection Methods and Digital Tools
- Data Quality Assurance and Verification
- Quantitative Analysis for M&E
- Qualitative Methods and Mixed Approaches
- Evaluation Design and Methodology
- M&E Reporting, Visualization, and Dashboards
- Data Use, Learning Agendas, and Adaptive Management
- Research Ethics and Knowledge Management
- Capstone: M&E System Design Project
GIS Professional Program
Build practical skills in geospatial analysis, mapping, and spatial data management. This program covers QGIS, coordinate systems, spatial joins, remote sensing basics, and interactive map creation for health programme planning, agricultural mapping, logistics routing, urban planning, and environmental monitoring.
Who is this for?
Public health planners, agricultural extension officers, urban planners, logistics coordinators, environmental researchers, and development professionals who work with location based data.
What You Will Learn
- GIS concepts, coordinate systems, and spatial data types
- Working with QGIS (data import, styling, layers)
- Georeferencing and digitization
- Spatial joins, buffers, and overlay analysis
- Thematic mapping and cartographic design
- Remote sensing fundamentals
- Interactive web maps and dashboards
- Spatial analysis for programme planning and assessment
Week by Week Curriculum
- Introduction to GIS and Spatial Thinking
- QGIS Setup, Interface, and Data Import
- Coordinate Systems and Projections
- Vector Data: Editing, Styling, and Attributes
- Spatial Queries, Joins, and Geoprocessing
- Raster Data and Remote Sensing Basics
- Thematic Mapping and Cartographic Design
- Interactive Maps and Web Publishing
- Spatial Analysis for Programme Planning
- Capstone: Sector Specific GIS Project
Frequently Asked Questions
Common questions about our training programs.
Not sure which program is right for you?
Book a free 15 minute call and we will help you choose the best fit for your goals.