Generative AI for Data Analysis Training Course
Generative AI for Data Analysis Training Course equips professionals with practical skills to combine Generative AI, data analytics, prompt engineering, business intelligence, automation, and advanced data interpretation to transform raw data into actionable insights.
Course Overview
Generative AI for Data Analysis Training Course
Introduction
Generative AI for Data Analysis Training Course equips professionals with practical skills to combine Generative AI, data analytics, prompt engineering, business intelligence, automation, and advanced data interpretation to transform raw data into actionable insights. Participants learn how modern AI tools can accelerate data cleaning, exploratory data analysis (EDA), statistical analysis, visualization, reporting, forecasting, and decision support while maintaining analytical accuracy and human oversight. The course emphasizes practical workflows using AI-assisted analytics, natural-language data querying, automated insight generation, AI-powered dashboards, predictive analytics, and data storytelling.
Designed for the modern data-driven workplace, this course demonstrates how Generative AI can reduce repetitive analytical tasks and improve the speed and accessibility of business intelligence. Through hands-on exercises and realistic case studies, participants explore AI-assisted Excel analytics, Python-enabled analysis, SQL workflows, visualization, anomaly detection, scenario analysis, automated reporting, and responsible AI. By the end of the program, learners can integrate Generative AI into existing analytical processes to produce faster, clearer, and more decision-ready insights while recognizing limitations such as hallucinations, bias, data privacy, and model reliability.
Course Duration
5 days
Course Objectives
By the end of this course, participants will be able to:
- Understand Generative AI fundamentals and their application to modern data analytics.
- Apply prompt engineering techniques to generate accurate and useful analytical outputs.
- Perform AI-assisted data cleaning, preparation, and transformation.
- Use Generative AI for exploratory data analysis (EDA) and pattern discovery.
- Generate and interpret AI-powered data visualizations and dashboards.
- Use AI to support statistical analysis and hypothesis testing.
- Integrate Generative AI with Excel, spreadsheets, SQL, and Python analytics workflows.
- Identify trends, correlations, anomalies, and outliers using AI-assisted techniques.
- Apply predictive analytics and forecasting to business datasets.
- Build automated data analysis reports and executive summaries.
- Use AI for data storytelling and insight communication.
- Implement responsible AI, data privacy, governance, and human-in-the-loop controls.
- Develop practical AI-powered data analysis workflows that improve productivity and decision-making.
Target Audience
- Data Analysts and Business Analysts
- Business Intelligence Professionals
- Data Scientists and Analytics Specialists
- Finance and Accounting Professionals
- Marketing and Sales Analysts
- Operations and Supply Chain Professionals
- Managers and Decision-Makers
- IT Professionals and Digital Transformation Teams
Course Modules
Module 1: Generative AI Fundamentals for Data Analysis
- Generative AI concepts, capabilities, and analytical applications
- Large Language Models (LLMs) and AI-assisted analytics
- Generative AI vs. traditional data analysis
- Understanding AI-generated insights and limitations
- Case Study: Using Generative AI to analyze monthly business performance data
Module 2: Prompt Engineering for Data Analytics
- Designing effective analytical prompts
- Context, role, constraints, and output formatting
- Few-shot prompting for analytical tasks
- Chain-of-thought alternatives and structured reasoning approaches
- Case Study: Creating prompts that transform raw sales data into management insights
Module 3: AI-Assisted Data Preparation and Cleaning
- Identifying missing, duplicate, and inconsistent data
- AI-assisted data transformation and normalization
- Detecting data quality issues
- Generating formulas and transformation logic
- Case Study: Cleaning a customer database containing duplicate and incomplete records
Module 4: Exploratory Data Analysis with Generative AI
- AI-assisted descriptive statistics
- Identifying patterns, relationships, and trends
- Correlation and segmentation analysis
- Outlier and anomaly detection
- Case Study: Analyzing customer transactions to identify purchasing patterns
Module 5: AI-Powered Visualization and Data Storytelling
- Selecting appropriate charts and visualizations
- Generating visualization recommendations with AI
- Dashboard design principles
- AI-assisted narrative generation
- Case Study: Converting operational KPIs into an executive dashboard and data story
Module 6: AI for Advanced Analytics, Forecasting and Prediction
- AI-assisted statistical analysis
- Trend analysis and time-series forecasting
- Scenario and what-if analysis
- Predictive analytics workflows
- Case Study: Forecasting product demand using historical sales data
Module 7: AI Integration with Excel, SQL and Python
- Generating and optimizing Excel formulas
- Using AI to write and explain SQL queries
- AI-assisted Python data analysis
- Debugging and improving analytical code
- Case Study: Building an automated sales-analysis workflow using SQL, Python, and Generative AI
Module 8: Automated Reporting, Governance and Responsible AI
- Automated analytical reports and executive summaries
- AI-assisted KPI monitoring and insight generation
- Data privacy and security considerations
- AI governance, validation, bias, and hallucination management
- Case Study: Designing a human-reviewed AI reporting workflow for senior management
Training Methodology
- Interactive lectures and presentations.
- Group discussions and brainstorming sessions.
- Hands-on exercises using real-world datasets.
- Role-playing and scenario-based simulations.
- Analysis of case studies to bridge theory and practice.
- Peer-to-peer learning and networking.
- Expert-led Q&A sessions.
- Continuous feedback and personalized guidance.
Register as a group from 3 participants for a Discount
Send us an email: info@datastatresearch.org or call +254724527104
Certification
Upon successful completion of this training, participants will be issued with a globally- recognized certificate.
Tailor-Made Course
We also offer tailor-made courses based on your needs.
Key Notes
a. The participant must be conversant with English.
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
c. Course duration is flexible and the contents can be modified to fit any number of days.
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
e. One-year post-training support Consultation and Coaching provided after the course.
f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.