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NITA AccreditedIntermediatePhysical + Virtual10 daysTODA909

Training on Data Analytics & Visualization with AI Tools

Learn how to use AI tools for data analytics and visualization to improve reporting, insights, and decision-making across organizations.

Next intake

20 Jul 2026 · Nakuru

View all dates

Duration

10 days

Live instruction

Delivery

Physical + Virtual

Cohort based

Level

Intermediate

Working professionals

Certification

NITA reimbursable

For Kenyan cohorts

Language

English

All materials

Overview

About this programme

This intensive training equips professionals with practical skills to analyze, visualize, and communicate data insights using AI-powered tools. Participants will learn how to clean and prepare data, apply analytics techniques, generate insights with AI assistance, and create clear, impactful visualizations for decision-making. The course emphasizes hands-on learning, ethical data use, and real-world applications across business, government, and development sectors.

Duration

10 Days

Who Should Attend

  • Data analysts and aspiring analysts

  • Monitoring, Evaluation, and Learning (MEL) professionals

  • Business intelligence and reporting officers

  • Policy, planning, and strategy professionals

  • Finance, HR, operations, and program staff

  • Managers and decision-makers working with data

Learning outcomes

What you'll walk away with

By the end of this course, participants will be able to:

  • Understand core data analytics concepts and workflows

  • Use AI tools to clean, analyze, and interpret data

  • Apply descriptive, diagnostic, and basic predictive analytics

  • Design effective charts, dashboards, and visual stories

  • Communicate insights clearly to technical and non-technical audiences

  • Apply ethical and responsible data analytics practices

Course modules

What we cover, module by module

Module 1: Foundations of Data Analytics & AI

  • Role of data analytics in decision-making
  • Types of analytics: descriptive, diagnostic, predictive, prescriptive
  • Introduction to AI-assisted analytics
  • Data ethics and governance basics
  • Case Study:Using analytics to improve organizational performance

Module 2: Data Collection, Quality & Preparation

  • Data sources and data types
  • Data quality, bias, and integrity
  • Data cleaning and preparation concepts
  • Using AI tools for data preparation
  • Practical Session:Cleaning and preparing a sample dataset with AI assistance

Module 3: Exploratory Data Analysis (EDA) with AI

  • Understanding data distributions and patterns
  • Using AI to summarize and explore datasets
  • Identifying trends, outliers, and correlations
  • Asking the right analytical questions
  • Practical Session:Exploratory analysis using AI-driven insights

Module 4: Data Analysis Techniques for Business & Programs

  • Descriptive and diagnostic analysis
  • Trend analysis and comparative analysis
  • Basic forecasting and scenario analysis (conceptual)
  • Interpreting AI-generated insights
  • Case Study:Analyzing operational or program performance data

Module 5: Data Visualization Principles

  • Principles of effective data visualization
  • Choosing the right chart for the message
  • Avoiding common visualization mistakes
  • Accessibility and inclusive visualization design
  • Practical Session:Designing effective charts and visuals

Module 6: Visualization Tools & Dashboards with AI

  • Overview of visualization and BI tools
  • AI-assisted chart creation and dashboard design
  • Designing interactive dashboards
  • Automating reports and visual updates
  • Practical Session:Building a dashboard using AI-enabled tools

Module 7: Data Storytelling & Communication

  • Structuring data-driven narratives
  • Presenting insights to decision-makers
  • Visual storytelling techniques
  • Using AI to draft insights and summaries
  • Practical Session:Creating a data story from analysis results

Module 8: Sector Applications & Use Cases

  • Business and finance analytics
  • M&E, policy, and development analytics
  • HR, operations, and service delivery analytics
  • Custom sector examples
  • Case Study:Applying analytics and visualization in a sector context

Module 9: Advanced Topics & Responsible AI Analytics

  • Introduction to predictive analytics with AI
  • Bias, fairness, and transparency in analytics
  • Data privacy and compliance
  • Quality assurance and validation of AI outputs
  • Practical Session:Reviewing analytics outputs for accuracy and bias

Module 10: Capstone Project & Action Planning

  • Group capstone: end-to-end data analysis and visualization project
  • Presentations and peer feedback
  • Building analytics roadmaps for organizations
  • Course evaluation and next steps
Impact

Where the change lands

Personal Impact

  • Strong data literacy and analytical confidence

  • Practical skills in AI-assisted data analysis

  • Improved ability to design clear, insightful visualizations

  • Enhanced storytelling and presentation of data insights

Organizational Impact

  • Better evidence-based decision-making

  • Improved quality and speed of reporting

  • Increased adoption of AI-enabled analytics

  • Stronger data governance and ethical data use

Dates and locations

Upcoming intakes

Every intake is limited to a small cohort. Booking closes when a date fills or three weeks before the start, whichever comes first.

Full calendar
FAQs

Common questions.

Still not sure? Send us a note and a facilitator will get back to you within a business day.

No. The course focuses on practical, AI-assisted analytics.

Course finder

Find the right course for you

Prefer to talk it through? Send us an enquiry and a facilitator will scope a fit within a business day.

For corporate teams

Training 10+ professionals?

We deliver Training on Data Analytics & Visualization with AI Tools in-house at your offices, at a venue we arrange, or fully virtual. Customise the curriculum against your KPIs, and get a bespoke price for the cohort size you need.