We run multiple on – demand trainings focused on strategy, data analysis and policy formulation. In addition to those mentioned below, we can create training and capacity building solutions tailored to your organizational needs.

Evidence Based Policy Making

Summary:

This course will enable participants to:

• Adopt a structured approach to problem-solving using theory and evidence
• Deepen their understanding of theory of change and indicator development
• Examine impact of programs using data-driven experimental and non-experimental evaluation methods
• Understand data collection processes, sampling design and data collection methods

Syllabus Outline:

• Introduction to Policy Design
• Theory of Change
• Theory of Logic
• Intervention design
• Survey Design
• Descriptive Evidence  
• Impact Evaluations
• Cost Benefit Analysis

Introduction to Data Analysis and Visualization

Summary:

This course is for understanding fundamentals of data analysis and visualization. It is designed for students and professionals who want to upgrade their data skills to be able to effectively understand, transform and analyze data according to their needs/scope of work. It will teach powerful functions and tools in Excel and Tableau that will assist in day to day work as well as aid in handling and solving complex data problems. You will learn how to interpret and visualize data creatively to provide relevant insights.

By the end of this course you will be able to manage sophisticated spreadsheets, develop professional dashboards and conduct analysis using complex calculations requiring advanced excel features. This course is a gateway to better productivity at work and a better employability portfolio as Excel still remains one of the top demanded skills that is required by employers.

Course Outline:

• Sorting and Organizing Data
• Adjusting Worksheets and Layout
• Determine the inputs you need to meet your end goals in terms of revenue or investments using Goal Seek and Data Table.
• Crash Course on Statistics
• Understanding Descriptive Statistics
• Excel Functions: IF, Sum, Count, Average, SumIF,CountIF, AverageIF etc
• Data Munging with Pivot Tables
• Forecasting & Sensitivity Analysis using Excel
• Data Visualization, Graphs and Maps
• Dashboards with Tableau

Data Analysis on STATA for Policy Makers

Summary:

Stata is one of the top tools used by economists and social scientists for quantitative program evaluation and data management. This course is for researchers and professionals who want to learn to conduct data management, analysis and visualizations using this statistical software. The training will enhance the participant’s knowledge and skills to analyze data in a fast, accurate and easier manner and will also teach them how to interpret and present the results. Participants will be given a refresher of basic principles of statistics and econometric models (such as regression analysis) and will learn how to conduct these using STATA.

By the end of this course you will learn data cleaning, data management, regression analysis, hypothesis testing and data visualizations. This course will benefit people working in the private sector, government institutions, research institutions and NGOs.

Syllabus Outline:

• Installing STATA
• Understanding different STATA windows.
• Importing Files on STATA
• Cleaning Data
• Merging Data Sets
• Basic STATA Functions
• Descriptive Stats on STATA
• Regression Analysis on STATA
• Exporting Results
• Graphs

Data Analytics and Visualization on Tableau

Objective:

Tableau is a powerful tool for business analytics, visualizations and data dash-boarding. Its ability to accommodate multifarious data types, including spatial and textual data makes it an ideal tool to draw insights from data sources at lightning fast speeds.

This course is a gentle introduction to Tableau for students and professionals who work on large data sets to solve complex business problems. Having gone through this course, attendees can start using Tableau in a professional setting with ease and it covers the content required as prerequisite to appear for Tableau Certified Associate Exam.

Outline:

• Installing Tableau
• Understanding different Tableau windows.
• Connecting data in Tableau
• Connecting Spatial Files in Tableau
• Basic Tableau functions
• Creating a Map in Tableau
• Making a Dashboard in Tableau
• Making a storyboard in Tableau for Presentation.

Business Analytics with R

Duration: 1 day (8 Hours)

Summary:

Business analytics is a set of data analysis and modeling techniques for understanding business situations and improving business decisions. This course provides an introduction to business analytics concepts, methods and tools with concrete examples from industry applications. We do so with the help of R programming language which is a free, powerful scripting language designed with descriptive and predictive analytics in mind. In the first part of the course, we will focus on data analysis concepts and understanding data with a refresher on basic probability and statistics.

In the second part, we will do an overview of the R scripting language, its syntax and semantics, followed by a quick dive into its practical applications and explore case studies with business implications.

The final part of the course will introduce the basic principles and techniques predictive modeling in R with examples of textual, spatial and temporal data followed by creating visualizations to display your analysis the form of charts, graphs and reports for managerial decision making.

Syllabus Outline:

Probability & Statistics Refresher

• Measures of Central Tendency
• Measures of spread & variability
• Measures of Association

Shape & Distribution of Statistical graphs

• Histograms
• Scatterplots
• The Box Plot

Introduction to R

• Introduction to the R interface
• Data variables & Basic Operations
• Loading Data & Reading Data
• Summary Stats
• Predictive Modeling & Statistical Analysis in R
• Introducing classification through a practical example
• Simple Linear Regression
• Discussion on model selection
• Data Visualization, Results Extraction & Reporting
• Creating reproducible reports with R Markdown
• Introduction to R graphical packages