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Redesign the attached **Module Five** presentation into a polished, engaging training presentation for a **non-technical audience**. ## Audience The audience has little or no ba…
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Redesign the attached **Module Five** presentation into a polished, engaging training presentation for a **non-technical audience**. ## Audience The audience has little or no background in data analysis, statistics, programming, or technical tools. Make every concept easy to understand using plain language, relatable examples, simple visuals, and practical activities. ## Main learning journey Organize the presentation as a clear story: **Messy Data → Inspect → Clean Safely → Check Data Quality → Ask Better Questions → Choose the Right Visual → Interpret Carefully → Communicate an Insight** Keep the original learning objectives and activities, including: * Messy Data Challenge * Inspect Before You Touch * Building Cleaning Rules * Keeping a Change Log * Data Quality Detective * Asking descriptive, comparison, pattern/trend questions * Distinguishing a number from an insight * Choosing the right chart * Visual quality assurance * Turning a chart into an insight * Data Insight Card / final reflection ## Writing style * Use very simple, conversational English. * Avoid technical jargon wherever possible. * If a technical term is necessary, explain it in one short sentence. * Use short headlines that communicate the main message of each slide. * Keep text concise. * Prefer examples, diagrams, icons, and visual explanations over paragraphs. * Use no more than 3–5 short bullets on a slide. * Make each slide communicate **one main idea**. * Use questions frequently to keep participants engaged. * Keep the tone practical, encouraging, and professional. ## Presentation structure Create approximately **15–18 slides**. Use a structure such as: 1. **Title — From Messy Data to Clear Insights** Subtitle: How to clean, check, analyze, and explain data safely. 2. **The Big Picture** Show a simple visual journey: Messy Data → Clean Data → Quality Check → Question → Visual → Insight → Decision 3. **Messy Data Challenge** Show the example dataset visually. Highlight issues such as inconsistent capitalization, missing values, abbreviations, and different versions of Yes/No. 4. **Inspect Before You Touch** Explain that the first step is to identify problems before changing anything. 5. **What Should AI Change?** Introduce three clear categories: * Safe to standardize * Needs human review * Do not guess 6. **Build the Cleaning Rules** Use examples such as: * Y / yes / Yes → Yes * Missing age → Do not guess * PSS → Check meaning * Possible duplicate → Flag for review 7. **Keep a Change Log** Explain visually why every change should be traceable. 8. **Can You Trust the Cleaned Data?** Introduce data quality checks in simple language. 9. **Data Quality Detective** Present missing information, possible duplicates, unusual values, small categories, and entry errors as a visual checklist. 10. **Ask the Data the Right Question** Explain: * Descriptive: What is happening? * Comparison: What is different? * Trend/Pattern: What may be changing or related? 11. **A Number Is Not an Insight** Visually compare: * Number * Insight * Unsupported conclusion Make the difference extremely clear. 12. **Choose the Right Visual** Create a simple visual decision guide: * Compare categories → Bar chart * Change over time → Line chart * Part of a whole → Pie/donut chart only when appropriate * Relationship between numbers → Scatter plot * Exact values → Table 13. **Can a Correct Chart Still Mislead?** Show examples of good vs. misleading chart practices. 14. **Visual QA Checklist** Cover title, labels, units, scale, missing categories, exaggerated differences, and context. 15. **From Chart to Insight** Use the sentence structure: * The chart shows… * The chart does not tell us why… * The main insight is… * One limitation is… * I would investigate next… 16. **Data Insight Card** Turn the final activity into a visually attractive worksheet-style slide. 17. **Key Takeaways** End with 4 memorable principles: * Inspect before changing. * Never guess missing information. * Match the visual to the question. * State the finding, limitation, and next step. ## Visual design direction Create a **modern, clean, professional training deck**. ### Color palette Use an accessible, calm palette: * Deep navy or dark blue for titles and key text * Teal or medium blue as the primary accent * Warm amber/orange only for warnings or items needing attention * Soft green for safe/approved actions * Light gray or off-white backgrounds Do not use too many colors. Follow approximately a **60–30–10 color balance**: * 60% neutral/light background * 30% primary blue/teal * 10% accent colors Maintain strong contrast and make the slides readable from the back of a training room. ### Typography * Use a modern sans-serif font. * Large titles: approximately 30–40 pt or larger. * Body text: approximately 20–26 pt. * Avoid small text. * Use bold strategically for key words. * Do not use more than two font families. ### Layout * Use generous white space. * Keep strong visual hierarchy. * Align elements consistently. * Avoid crowded slides. * Use cards, simple diagrams, arrows, icons, and visual steps. * Use tables only when exact comparison is useful. * Simplify tables rather than showing excessive data. * Use rounded cards and subtle shapes rather than heavy borders or decorative effects. ## Data visualization best practices * Prefer simple bar and line charts. * Start bar charts at zero unless there is a strong reason not to. * Clearly label axes and units. * Avoid 3D charts. * Avoid unnecessary legends and gridlines. * Avoid decorative chart elements that do not help interpretation. * Highlight only the data point that matters. * Use color consistently: the same color should have the same meaning throughout the deck. * Never use misleading scales. * Include enough context for the audience to interpret the result correctly. ## Visual storytelling Where possible, replace text-heavy slides with: * Before/after examples * Simple process diagrams * Three-step frameworks * Checklists * Good vs. bad examples * Question cards * Illustrated data tables * Callout boxes * Simple icons representing people, records, questions, charts, warnings, and decisions Do not use generic decorative stock photos unless they directly support the lesson. ## Important Do not make the presentation feel technical or academic. It should feel like a **hands-on workshop** where participants learn how to work safely with data and AI. Preserve the meaning of the original content. Do not introduce advanced statistical concepts that are not in the source material. For each slide, prioritize: **Clarity first → visual communication second → decoration last.** The finished presentation should feel cohesive, accessible, modern, and suitable for an instructor presenting live to a non-technical professional audience.
Presentation overview
This community presentation was shared by Judah Sleibi as a complete 17-slide example. Redesign the attached **Module Five** presentation into a polished, engaging training presentation for a **non-technical audience**. ## Audience The audience has little or no ba… The preview lets you review the full sequence in order, rather than judging the design from a single cover image.
Use it as a reference for planning your own deck: notice how the amount of information changes from slide to slide, where visual emphasis appears, and how repeated design choices help the presentation feel connected. Community examples are inspiration, not locked templates, so you can keep the ideas that fit your audience and replace anything that does not.
Learn from the example
Look at the job each slide performs. Identify where the deck introduces its subject, develops the main points, adds evidence or examples, and moves toward a conclusion.
Notice which element attracts attention first and how headings, supporting text, images, and data are separated. Strong hierarchy makes the intended reading order obvious.
Compare spacing, typography, color, and repeated components across the slides. Consistent rules help varied content feel like one presentation instead of unrelated screens.
Make it your own
Begin with your audience and the decision, lesson, or action the presentation should support. Replace the topic, examples, evidence, and visuals with material you can verify, then edit every slide for one clear takeaway. You can borrow the visual direction without copying the creator's wording or message. Presenton will use this community deck as a design reference while you develop content for your own purpose.
