Certificate in Data Analytics with AI

The Certificate in Data Analytics with AI is a practical, hands-on program designed to help you turn raw data into clear business decisions. Over three months, you will learn how to combine statistics, AI tools, and modern analytics software to solve real organizational problems.

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Program Highlights

  • Program : Certificate in Data Analytics with AI
  • Duration : 3 Months
  • Contact Hours : 60+ hours (6 hours/week)
  • Format :Blended (In-person/Online with hands-on labs)
  • Level :Beginner to Intermediate
  • Center : All centers (Accra, Kumasi, Tema)

Program Overview

The Certificate in Data Analytics with AI is a practical, hands-on program designed to help you turn raw data into clear business decisions. Over three months, you will learn how to combine statistics, AI tools, and modern analytics software to solve real organizational problems.

You start with the foundations of AI and statistics so you understand how data behaves and how insights are validated. You then move into advanced Excel for data cleaning, modeling, automation, and dashboard development. From there, you build professional-grade reports and interactive dashboards using Power BI and Tableau.

Every module focuses on application. You work with real datasets, build live dashboards, and complete guided lab exercises each week. You will apply statistical concepts like correlation and hypothesis testing to real business cases. You will use AI tools to assist in analysis, reporting, data interpretation and dashboard development.

By the end of the course, you will confidently clean messy data, perform advanced analysis, automate reports, and present insights through interactive visual dashboards. You graduate with practical skills that employers demand and businesses value.

Tools You'll Master

  • Microsoft Excel - Advanced analytics, Power Query, Power Pivot, VBA automation
  • Microsoft Power BI Desktop - Data modeling, DAX, interactive dashboards
  • Tableau Public - Professional data visualizations and storytelling
  • AI Tools for Data Analysis - AI-powered analytics and insights generation

Learning Outcomes

Upon completion of this program, you will be able to:

  • Explain core AI concepts and apply prompt engineering for data analysis tasks
  • Apply statistical methods such as hypothesis testing, correlation, and probability distributions to real datasets
  • Clean, transform, and prepare raw data using Power Query and structured data techniques
  • Build advanced analytical models in Excel using Pivot Tables, Power Pivot, Solver, and financial forecasting tools
  • Automate repetitive reporting tasks using VBA
  • Design interactive dashboards in Excel for business decision-making
  • Connect, model, and transform data in Power BI using proper schema design
  • Write DAX measures for business KPIs and time intelligence analysis
  • Develop optimized and mobile-ready Power BI dashboards
  • Build professional Tableau dashboards using calculated fields and advanced visual techniques
  • Present analytical findings clearly through compelling data storytelling

Target Audience

This program is ideal for:

  • Working professionals who handle reports and want to improve decision-making skills
  • Finance and accounting officers
  • HR and operations managers
  • Business analysts and aspiring data analysts
  • Graduates seeking employable analytics skills
  • Entrepreneurs who want to analyze sales and operational data
  • Monitoring and evaluation officers
  • MIS and reporting officers

Career Opportunities

  • Data Analysts
  • Business Intelligence Professionals
  • Power BI Specialists
  • Professionals who manage data for decision-making
  • IT Managers
  • Data Scientists

Course Content

The program is divided into 4 comprehensive modules covering AI, Statistics, Excel, Power BI, and Tableau.

Module 1 – AI & Statistics ▼
Introduction to Artificial Intelligence (AI) for Data Analysts
  • Prompting Engineering
  • Statistics in Data Analytics
Statistical Concepts
  • Introduction to Statistics
  • Types of Data
  • Statistical Analysis
  • Population and Samples
  • Type of Sampling Technique
Advanced Statistical Methods
  • Measures of Central Tendency and Dispersion
  • Probability Distribution
  • Covariance & Correlation
  • Hypothesis Testing
Module 2 - Data Analysis with Advanced Excel â–¼
1. Data Foundation & Preparation
  • Data organization techniques and data cleaning best practices
  • Complex data importing and transformation using Power Query
  • Data validation techniques and quality control measures
2. Advanced Data Analysis
  • Advanced pivot table techniques and Power Pivot modeling
  • Advanced LOOKUP functions, array formulas, and dynamic ranges
  • Statistical analysis using Excel's built-in functions
3. Business Intelligence & Modeling
  • Advanced What-If analysis and Scenario Manager
  • Optimization using Solver for business decisions
  • Financial modeling and forecasting techniques
4. Automation & Advanced Tools
  • VBA programming for task automation
  • Creating interactive dashboards and reports
  • Custom function development
5. Data Integration & Visualization
  • Advanced charting and visualization techniques
  • Real-time data refresh and automated reporting
Module 3 - Data Visualization with Power BI â–¼
1. Power BI Fundamentals
  • Introduction to Power BI Desktop interface and features
  • Understanding data visualization principles
  • Basic chart types and their appropriate use cases
2. Data Connection & Preparation
  • Connecting to various data sources (Excel, CSV, Web)
  • Data transformation basics in Power Query
  • Advanced Power Query transformations (merging, appending, custom columns)
3. Data Modeling
  • Understanding star and snowflake schemas
  • Creating and managing relationships
  • Best practices for data model optimization
  • Working with date tables and time intelligence
4. DAX Fundamentals & Advanced
  • Basic calculations and measures
  • Filter context and row context
  • Time intelligence functions
  • Advanced DAX patterns (variables, iterator functions, error handling)
5. Advanced Visualization & Interactive Features
  • Custom visuals from marketplace
  • Drill-through and drill-down functionality
  • Bookmarks and advanced filtering
  • Mobile-optimized reports
Module 4 - Data Visualization with Tableau â–¼
1. Introduction to Tableau Public
  • Understanding the Tableau interface and workspace
  • Differences between Tableau Public and other versions
  • Data connection options in Tableau Public
  • Basic navigation and terminology
2. Data Foundation
  • Data preparation and cleaning techniques
  • Understanding data types and roles
  • Data blending and joining multiple sources
  • Working with extracts vs. live connections
3. Visualization Fundamentals
  • Essential chart types and their applications
  • Best practices for data visualization
  • Custom formatting and styling
  • Interactive dashboards creation
4. Advanced Analytics
  • Calculated fields and LOD expressions
  • Advanced table calculations
  • Statistical analysis techniques
  • Trend analysis and forecasting
5. Geographic Analysis
  • Working with spatial data
  • Custom territories and geocoding
  • Advanced mapping techniques
6. Dashboard Development and Story Telling
  • Dashboard design principles
  • Interactive filters and actions
  • Creating compelling data stories
  • Performance optimization

Eligibility Requirements

  • Basic familiarity with computers and Microsoft Office (especially Excel)
  • Understanding of basic business concepts
  • No prior programming or advanced analytics experience required
  • Willingness to learn and engage in hands-on lab exercises

Note: This is a beginner to intermediate level course. While basic Excel knowledge is helpful, we will cover fundamentals before advancing to complex topics.