From DATA to DECISIONS :
Conversational Data Analyst with
Generative AI Essentials
Duration of
Course
1 Day
Mode : Online/F2F
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OTHER COURSES
Accredited Training Provider of MSTB for
From DATA to DECISIONS :
Conversational Data Analyst
with Generative AI Essentials
04 - 06 May
CT-SEC
ONLINE
From Data to Decisions :
Conversational Data Analysis with Generative AI Essentials
Course Information
From Data to Decisions: Conversational Data Analysis with Generative AI Essentials course introduces participants to practical, structured and accessible data analysis using conversational Generative AI tools.
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The course focuses on enabling professionals to collect, organise and analyse data using AI-powered Large Language Models (LLMs) through structured prompting techniques. Emphasis is placed on lowering the barrier to entry, allowing participants to perform meaningful data analysis without requiring advanced statistical, programming or data science expertise.
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Participants will learn how to design basic data collection strategies, prepare datasets, conduct general analysis, generate simple data visualisations, and transform insights into decision-ready outputs such as reports and presentation slides.
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Primary AI Tools Covered: ChatGPT, Copilot, Gemini, QwenChat, Kimi
Who Should Attend This Course
This course is suitable for professionals involved in operational reporting, planning and decision-making, including :
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Executives and Senior Executives Managers and Team Leaders Operations and Performance Officers HR and L&D Professionals Marketing and Business Development Teams Administrative and Support Staff involved in reporting Non-technical analysts and data users.
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It is ideal for professionals who want to perform structured data analysis using AI tools without needing advanced analytical or technical backgrounds.
Topics Coverage (1-Day Course)
Module 1 : Data Foundations & Collection Design
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Defining decision-making objectives Types of data: quantitative vs qualitative Structured vs unstructured data Planning a simple data collection strategy AI-assisted survey and form creation.
Module 2 : Data Preparation & Tool Selection
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Extracting and organising datasets Basic data cleansing concepts Comparing ChatGPT, Copilot, Gemini, QwenChat and Kimi for analytical tasks Responsible data handling and privacy considerations.
Module 3 : General & Specific Conversational Data Analysis
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Uploading datasets into AI tools Structured prompt design for data analysis Summarising datasets and identifying trends Basic segmentation and comparison analysis Generating simple data visualisations (bar charts, pie charts, summary tables) Interpreting and validating AI-generated insights.
Module 4 : From Insights to Decision Outputs
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Refining AI-generated recommendations Creating presentation slides using AI assistance Developing short analytical reports Communicating insights clearly to stakeholders.
By the End of This Course, Participants Will Be Able To :
Upon successful completion, participants will be able to:
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Given a defined workplace decision-making objective and a structured template, design a simple data collection approach that appropriately identifies relevant quantitative and qualitative data sources aligned to the objective.
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Given access to selected conversational AI platforms (ChatGPT, Copilot, Gemini, QwenChat, Kimi), develop AI-assisted data collection instruments (e.g., surveys, forms, feedback templates) that meet clarity, relevance and usability standards for operational deployment.
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Given raw datasets (e.g., survey responses or spreadsheet data), organise and prepare the data into analysis-ready formats suitable for upload into conversational AI tools with minimal errors.
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Given uploaded datasets in conversational AI platforms, construct structured prompts to perform general data analysis (summarisation, trend identification, comparison) and produce logically coherent analytical outputs.
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Given AI-generated analytical outputs, generate simple data visualisations (e.g., bar charts, pie charts, summary tables) through conversational prompting that accurately reflect the analysed data.
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Given analysed data and AI-generated visualisations, produce a short decision-ready output (e.g., presentation slide deck or brief report) that clearly communicates key insights and recommended actions.
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Given guided practice scenarios, demonstrate the ability to conduct conversational data analysis independently without relying on advanced statistical or technical expertise.
Course Duration
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Duration: 1 Days
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Total Contact Hours: 7 Hours
Additional Information
Training Approach
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Instructor-led, interactive sessions Hands-on AI demonstrations Guided dataset exercises Structured prompt design workshops Real-world decision scenarios.
Delivery Mode
Virtual (online) Instructor-Led Training (VILT) or Classroom (Physical Face-to-Face)
Materials Provided
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Data collection planning templates AI-assisted survey and form templates Essential data analysis prompting guide Sample dataset exercises Simple data visualisation prompt guide Participant Learning Support Chatbot Certificate of Completion.
Why Choose This Course?
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Accessible entry into conversational AI-powered data analysis
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No advanced statistical knowledge required
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Faster insight generation and reporting
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Improved clarity through AI-assisted visualisation
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Practical and immediately applicable workplace skills
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Designed for measurable operational impact
