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From Degree to Industry — Pathways, Skills & Roadmaps

# MASTER PROMPT — GENERATE A PREMIUM, FULLY PICTORIAL INDUSTRY PRESENTATION You are an expert **presentation designer, academic-industry strategist, curriculum analyst, infograp…

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# MASTER PROMPT — GENERATE A PREMIUM, FULLY PICTORIAL INDUSTRY PRESENTATION You are an expert **presentation designer, academic-industry strategist, curriculum analyst, infographic designer, and visual storyteller**. Create a **premium, professional, highly visual 36-slide presentation** based primarily on the provided source documents: 1. **IAB_Feedback_Performa_v1.docx** 2. **IAB Execution Plan v3.docx** 3. **Evaluation Criteria Handbook.docx** 4. **BSSE_Handbook_Completed.docx** 5. **BSDS_Handbook_updated.docx** 6. **BSAI_Handbook_updated.docx** The presentation is for: * Industry Advisory Board members * Senior industry professionals * University leadership * Faculty * Alumni * Employers * Senior students * Academic stakeholders The purpose is to visually communicate how the three undergraduate programs: * **BS Artificial Intelligence** * **BS Data Science** * **BS Software Engineering** connect **academic learning → industry skills → projects → experience → employability → career growth**. --- # 1. PRESENTATION TITLE ## FROM DEGREE TO INDUSTRY ### Career Pathways, Skills, Salaries, Roadmaps & Industry Readiness Use a premium subtitle such as: **Connecting Academic Learning with Real-World Career Outcomes** --- # 2. MOST IMPORTANT REQUIREMENT — FULLY PICTORIAL This is NOT a traditional text-heavy PowerPoint. The presentation MUST be: ## VISUAL-FIRST + PICTORIAL + INFOGRAPHIC-DRIVEN Target approximately: **75–85% visual content** **15–25% text** The audience should understand the main message of each slide primarily by looking at the visual composition. Do NOT create slides that look like Word documents. Do NOT copy paragraphs from the handbooks onto slides. Do NOT create slides filled with bullet points. Instead transform information into: * Infographics * Diagrams * Career ladders * Roadmaps * Timelines * Process flows * Skill pyramids * Ecosystem maps * Visual matrices * Technology stacks * Career journeys * Salary progression charts * Circular diagrams * Illustrated workflows * Architecture diagrams * Before → After flows * Student → Project → Career pipelines * Icon-based visual systems * Large numerical callouts * Visual comparisons * Minimal charts * Premium illustrations * Subtle 3D visual elements ### CORE RULE **INFORMATION → VISUAL STORY → SHORT LABELS → MINIMAL SUPPORTING TEXT** Never: **INFORMATION → PARAGRAPH → MORE PARAGRAPH** --- # 3. TEXT RULES Text must support the visual, not replace it. ### Maximum: * 3–5 bullets per visual section * Prefer 2–5 words per bullet * Avoid paragraphs * Avoid long sentences * Avoid excessive descriptions * Avoid dense tables * Avoid text-heavy comparison slides Use: **Machine Learning** **Deep Learning** **Computer Vision** **NLP** **Generative AI** instead of: "Students should develop strong expertise in machine learning, deep learning, computer vision, NLP and generative AI." --- # 4. SOURCE FIDELITY Treat the six provided documents as the **primary authoritative source**. Preserve their terminology, program structure, differentiators, roadmap concepts, learning philosophy, certifications, specializations, employability concepts, and industry-validation framework. Do NOT silently invent facts. Do NOT invent: * University partnerships * Employers * Job-placement statistics * Industry partnerships * Salary data * Certification claims * Rankings * Accreditation claims * Current market statistics * Job-opening statistics * Company logos * Employment guarantees If a claim is not supported by the documents, either: 1. omit it, or 2. clearly mark it as an **industry benchmark / illustrative assumption / subject to validation**. Do not present assumptions as official university facts. --- # 5. INDUSTRY ADVISORY BOARD FRAMEWORK The IAB validation framework contains 9 major dimensions. Represent them visually: 1. **Program Value Proposition** 2. **Key Jobs After Degree** 3. **Key Skills Required** 4. **Starting Salaries & Roles** 5. **Certifications Embedded** 6. **Program Architecture / Roadmap** 7. **Courses** 8. **Industry Exposure** 9. **Projects / PBL / FYP** Create a visual 9-part wheel or ecosystem rather than a text list. --- # 6. CORE PROGRAM PHILOSOPHY Where appropriate, visually reinforce the program philosophy: ## LEARN → BUILD → DEPLOY → EXPERIENCE → DEMONSTRATE → EARN → GROW Use this as a recurring visual language throughout the presentation. --- # 7. PROGRAM VISUAL IDENTITIES Create three distinct but consistent visual identities. ## BS ARTIFICIAL INTELLIGENCE Core visual concept: **DATA → MODEL → INTELLIGENCE → DEPLOYMENT → AI PRODUCT** Visual themes: * Machine Learning * Deep Learning * Computer Vision * NLP * Generative AI * Robotics * Responsible AI * MLOps * AI deployment --- ## BS DATA SCIENCE Core visual concept: **DATA → CLEAN → ANALYZE → MODEL → VISUALIZE → DECIDE** Visual themes: * Data * Statistics * Analytics * Machine Learning * Visualization * Data Engineering * Forecasting * Cloud * Data governance --- ## BS SOFTWARE ENGINEERING Core visual concept: **IDEA → DESIGN → CODE → TEST → DEPLOY → SCALE** Visual themes: * Programming * Software development * APIs * Databases * Architecture * Testing * Cloud * DevOps * Deployment --- # 8. SLIDE COUNT Create EXACTLY: ## 36 SLIDES Structure: ### INTRODUCTION Slides 1–4 ### BS ARTIFICIAL INTELLIGENCE Slides 5–14 ### BS DATA SCIENCE Slides 15–24 ### BS SOFTWARE ENGINEERING Slides 25–34 ### CROSS-PROGRAM CONCLUSION Slides 35–36 Do NOT add extra slides. Do NOT remove slides. --- # 9. COMPLETE SLIDE-BY-SLIDE STRUCTURE ## SLIDE 1 — TITLE ### FROM DEGREE TO INDUSTRY Subtitle: **Career Pathways, Skills, Salaries, Roadmaps & Industry Readiness** Create a premium hero visual showing: **UNIVERSITY → SKILLS → PROJECTS → INDUSTRY → CAREER** Almost no text. Use an elegant professional illustration. --- # SLIDE 2 — WHY INDUSTRY ALIGNMENT MATTERS Create a large visual bridge. LEFT: ### ACADEMIA Courses Knowledge Theory Projects ↓ BRIDGE ↓ RIGHT: ### INDUSTRY Skills Products Experience Employability Use visual icons instead of paragraphs. --- # SLIDE 3 — WHAT INDUSTRY VALIDATES Create a 9-part visual wheel. Center: ### INDUSTRY VALIDATION Around it: Value Proposition Jobs Skills Salaries Certifications Architecture Courses Industry Exposure Projects Use one icon per dimension. --- # SLIDE 4 — THE INDUSTRY-READY GRADUATE Create a circular journey: **LEARN** ↓ **BUILD** ↓ **DEPLOY** ↓ **EXPERIENCE** ↓ **DEMONSTRATE** ↓ **EARN** ↓ **GROW** This should be a major infographic. --- # BS ARTIFICIAL INTELLIGENCE # SLIDE 5 — AI INDUSTRY LANDSCAPE Center: ## ARTIFICIAL INTELLIGENCE Surround with visual nodes: Machine Learning Deep Learning Computer Vision NLP Generative AI Robotics Responsible AI MLOps Create a visual ecosystem. --- # SLIDE 6 — WHERE AI PROFESSIONALS WORK Create an illustrated industry ecosystem. Examples where supported by the source/context: Healthcare FinTech E-Commerce Manufacturing Technology Automotive Security Cloud Do not invent specific company partnerships. Use industry icons rather than company logos. --- # SLIDE 7 — AI CAREER PATHWAYS Create a large career ladder: **Junior AI/ML Engineer** ↓ **AI/ML Engineer** ↓ **Senior AI Engineer** ↓ **AI Lead** ↓ **AI Leadership** Use role icons and progression arrows. --- # SLIDE 8 — AI SALARY & CAREER PROGRESSION Create a visual ascending career staircase/chart. Use the following **only as indicative handbook/validation benchmarks**: **Junior AI/ML Engineer** PKR 80k–120k/month ↓ **AI/ML Engineer** PKR 150k–200k/month ↓ **Senior AI Engineer / Lead** PKR 250k–350k/month ↓ **AI Director / Leadership** PKR 400k+/month Add small footer: **Indicative benchmark — subject to Industry Advisory Board validation** Do not present these numbers as guaranteed salaries. --- # SLIDE 9 — AI SKILLS EMPLOYERS NEED Create a visual skill pyramid. ### FOUNDATION Python Mathematics Statistics ↓ ### CORE Machine Learning Deep Learning NLP Computer Vision ↓ ### ADVANCED Generative AI LLMs MLOps Responsible AI ↓ ### OUTCOME ## DEPLOYABLE AI SYSTEMS --- # SLIDE 10 — AI TECHNOLOGY STACK Create a visual technology stack. ### PROGRAMMING Python ### AI TensorFlow PyTorch ### CLOUD AWS Azure ### ADVANCED Generative AI MLOps ### OUTPUT AI Products Only use technologies supported by the source documents. --- # SLIDE 11 — AI CERTIFICATIONS Create premium visual certification cards. Show certifications named in the handbook, including: AWS AI/ML Microsoft Azure AI Google TensorFlow NVIDIA Deep Learning Use certification-style visual badges. Do not invent certification levels or claims. --- # SLIDE 12 — AI ROADMAP: YEAR 1 → YEAR 4 Create a horizontal illustrated timeline. ### YEAR 1 Python Mathematics Programming ↓ ### YEAR 2 Machine Learning Algorithms Data ↓ ### YEAR 3 Deep Learning Computer Vision NLP Generative AI ↓ ### YEAR 4 MLOps Deployment Industry Project FYP ↓ ## AI ENGINEER --- # SLIDE 13 — AI INDUSTRY EXPERIENCE Create a visual pipeline: **CLASSROOM** → **REAL INDUSTRY PROBLEM** → **DATA** → **MODEL** → **DEPLOYMENT** → **PORTFOLIO** → **CAREER** Use icons and illustrations. --- # SLIDE 14 — 1 STUDENT → 1 AI PRODUCT Make this a powerful visual. **STUDENT** ↓ **PROBLEM** ↓ **DATASET** ↓ **AI MODEL** ↓ **APPLICATION** ↓ **DEPLOYMENT** ↓ **GITHUB** ↓ **PORTFOLIO** ↓ **CAREER** Very little text. --- # BS DATA SCIENCE # SLIDE 15 — DATA SCIENCE INDUSTRY LANDSCAPE Center: ## DATA → INSIGHT → DECISION Around it: Analytics Statistics Machine Learning Forecasting Visualization Data Engineering Business Intelligence Data Governance Use a connected data ecosystem. --- # SLIDE 16 — WHERE DATA PROFESSIONALS WORK Create a visual industry ecosystem: Finance Healthcare Retail Marketing Manufacturing Technology E-Commerce Government Use icons. --- # SLIDE 17 — DATA SCIENCE CAREER PATHWAY Create a career ladder: **Data Analyst** ↓ **Junior Data Scientist** ↓ **Data Scientist** ↓ **Senior Data Scientist** ↓ **Lead / Head of Data** Use visual progression. --- # SLIDE 18 — DATA SCIENCE SALARY PATH Create a visual salary staircase. Use as indicative benchmarks: **Data Analyst / Junior Data Scientist** PKR 70k–100k/month ↓ **Data Scientist** PKR 150k–200k/month ↓ **Senior Data Scientist** PKR 250k–350k/month ↓ **Head of Data Science** PKR 400k+/month Footer: **Indicative benchmark — subject to Industry Advisory Board validation** --- # SLIDE 19 — DATA SCIENCE SKILL STACK Create a layered visual. ### FOUNDATION Python SQL Statistics ↓ ### ANALYTICS Data Cleaning EDA Visualization ↓ ### MODELING Machine Learning Prediction Forecasting ↓ ### ENGINEERING Pipelines Cloud Data Infrastructure ↓ ### OUTCOME Business Insight Decision Impact --- # SLIDE 20 — DATA CAREER ECOSYSTEM Do NOT create a boring table. Create four connected visual role cards: ### DATA ANALYST **Insights** ### DATA SCIENTIST **Predictions** ### ML ENGINEER **Production Models** ### DATA ENGINEER **Data Infrastructure** Show how the roles connect through the data lifecycle. --- # SLIDE 21 — DATA SCIENCE TECHNOLOGY STACK Create an illustrated technology stack: Python R SQL Databases Cloud Analytics Visualization Machine Learning Use icons and minimal labels. Only include technologies supported by the handbook. --- # SLIDE 22 — DATA SCIENCE CERTIFICATIONS Create visual certification cards: AWS Data Analytics Microsoft Azure Data Scientist Google Data Analytics IBM Data Science Keep descriptions minimal. --- # SLIDE 23 — DATA SCIENCE ROADMAP Create a four-year visual timeline. ### YEAR 1 Python Mathematics Statistics ↓ ### YEAR 2 SQL Analytics Visualization ↓ ### YEAR 3 Machine Learning Predictive Modeling Data Engineering ↓ ### YEAR 4 Cloud Industry Project FYP ↓ ## DATA PROFESSIONAL --- # SLIDE 24 — INDUSTRY-READY DATA SCIENTIST Create a large end-to-end data pipeline: **RAW DATA** → **CLEAN** → **ANALYZE** → **MODEL** → **VISUALIZE** → **INSIGHT** → **DECISION** → **IMPACT** Use illustrations rather than text. --- # BS SOFTWARE ENGINEERING # SLIDE 25 — SOFTWARE ENGINEERING INDUSTRY LANDSCAPE Create a software ecosystem around: Web Mobile Cloud Enterprise SaaS APIs DevOps AI Applications Center: ## SOFTWARE ENGINEERING --- # SLIDE 26 — SOFTWARE ENGINEERING CAREER PATHWAYS Create a career ladder: **Junior Software Engineer** ↓ **Software Engineer** ↓ **Senior Software Engineer** ↓ **Tech Lead** ↓ **Software Architect / Engineering Leadership** --- # SLIDE 27 — BEYOND CODING Center: ## SOFTWARE ENGINEER Surround with: Programming Architecture Testing Security Databases Cloud DevOps Communication Problem Solving Use a radial infographic. --- # SLIDE 28 — SOFTWARE ENGINEERING SKILL STACK Create a vertical skill pyramid: Programming ↓ DSA ↓ Development ↓ Databases + APIs ↓ Testing ↓ Architecture ↓ Cloud + DevOps ↓ Production Systems --- # SLIDE 29 — SOFTWARE ENGINEERING SPECIALIZATIONS Create a branching visual tree. ## SOFTWARE ENGINEERING ├── Web / Mobile ├── Cloud / DevOps ├── Architecture ├── QA / Testing ├── Databases ├── Data Engineering └── AI Applications Use icons for each branch. --- # SLIDE 30 — SOFTWARE ENGINEERING CERTIFICATIONS Create visual certification cards using certifications supported by the source handbook. Examples may include: AWS Microsoft Azure Google Cloud DevOps Do not add unsupported certifications. --- # SLIDE 31 — SOFTWARE ENGINEERING ROADMAP Create a four-year timeline. ### YEAR 1 Programming Problem Solving ↓ ### YEAR 2 DSA Databases Development ↓ ### YEAR 3 Architecture Testing Cloud ↓ ### YEAR 4 DevOps Industry Project FYP Deployment ↓ ## SOFTWARE ENGINEER --- # SLIDE 32 — INDUSTRY EXPERIENCE Create a product-development pipeline: **REAL PROBLEM** → **REQUIREMENTS** → **DESIGN** → **DEVELOP** → **TEST** → **DEPLOY** → **MAINTAIN** Make this look like a professional software lifecycle diagram. --- # SLIDE 33 — PORTFOLIO GRADUATION Create a visual transformation: **GitHub Repositories** ↓ **Deployed Applications** ↓ **System Designs** ↓ **Industry Projects** ↓ **Technical Portfolio** ↓ **Interview Evidence** Use a laptop / GitHub-style / application mockup visual. --- # SLIDE 34 — STUDENT PROJECT → CAREER ASSET Create: **CLASS PROJECT** → **REAL PROBLEM** → **PRODUCT** → **DEPLOYMENT** → **GITHUB** → **PORTFOLIO** → **INTERVIEW** → **CAREER** Main visual statement: ## PROJECTS BECOME CAREER EVIDENCE --- # SLIDE 35 — AI vs DATA SCIENCE vs SOFTWARE ENGINEERING DO NOT create a conventional dense table. Create three large visual columns. ### AI ## BUILD INTELLIGENCE Machine Learning Deep Learning CV NLP Generative AI MLOps --- ### DATA SCIENCE ## TURN DATA INTO DECISIONS Analytics Statistics Machine Learning Visualization Data Engineering --- ### SOFTWARE ENGINEERING ## BUILD RELIABLE SOFTWARE Programming Architecture Testing Cloud DevOps At the bottom create one shared visual: **BUILD → DEPLOY → DEMONSTRATE → CREATE VALUE** Do not rank the three programs. --- # SLIDE 36 — THE INDUSTRY-READY GRADUATE Make this the strongest visual slide of the entire presentation. Center: # INDUSTRY-READY GRADUATE Around the graduate create visual nodes: 🎓 Knowledge 🧠 Skills 🛠 Projects ☁ Deployment 🏢 Industry Experience 📜 Certifications 💼 Portfolio 💰 Earning Potential 🚀 Career Growth At the bottom: # LEARN → BUILD → DEPLOY → EXPERIENCE → DEMONSTRATE → EARN → GROW Closing statement: **The goal is not simply to graduate. The goal is to become ready for the world beyond graduation.** Keep the final slide elegant and visually powerful. --- # 10. VISUAL DESIGN SYSTEM Create a consistent premium visual language. ### BACKGROUND Use: * White * Warm white * Very light neutral backgrounds ### TYPOGRAPHY Use: * Modern sans-serif * Strong hierarchy * Large titles * Short labels * Excellent readability ### COLORS Primary: * Deep navy * Charcoal * Soft neutral tones Use subtle program-specific accents: ### AI Subtle blue / indigo accent ### DATA SCIENCE Subtle teal / green accent ### SOFTWARE ENGINEERING Subtle orange / amber accent Do not make the presentation colorful or childish. --- # 11. DESIGN STYLE The overall aesthetic should feel like: **Premium Consulting Deck + Modern University Presentation + Technology Industry Report** Use: * Editorial layouts * Clean grids * Large whitespace * Elegant typography * Premium infographics * High-quality vector illustrations * Subtle 3D elements * Minimal shadows * Refined iconography * Thin connector lines * Professional charts * Sophisticated composition The presentation should look suitable for: **University leadership + Industry Advisory Board + Senior executives.** --- # 12. ABSOLUTELY AVOID DO NOT use: ❌ Dark cyberpunk themes ❌ Neon colors ❌ Hacker aesthetics ❌ Gaming aesthetics ❌ Futuristic overload ❌ Excessive gradients ❌ Glowing text ❌ Random stock-photo collages ❌ Generic AI robot images everywhere ❌ Cartoonish educational graphics ❌ Giant paragraphs ❌ Dense tables ❌ Tiny unreadable text ❌ Wall-of-text slides ❌ Repeated identical cards ❌ Clip-art-looking visuals ❌ Excessive decorative elements --- # 13. IMAGE & ILLUSTRATION RULES Use images only when they communicate something meaningful. Prefer: * Professional technology illustrations * Abstract data visualizations * Software development environments * AI pipeline illustrations * Data pipeline illustrations * Cloud architecture visuals * Career journey illustrations * Student-to-professional transformation * Industry environment illustrations Avoid generic stock photos of people smiling at laptops. Every image must support the slide's message. --- # 14. VISUAL DIVERSITY Do NOT use the same layout repeatedly. Across the 36 slides deliberately vary between: * Hero visual * Radial infographic * Timeline * Career ladder * Pipeline * Skill pyramid * Ecosystem map * Visual comparison * Technology stack * Circular process * Transformation diagram * Illustrated workflow * Large-number visual * Portfolio mockup * Architecture-style diagram The deck should feel designed, not automatically templated. --- # 15. ANIMATION / TRANSITIONS If the presentation platform supports animation: Use subtle professional animation. Examples: * Timeline elements appearing sequentially * Career ladder ascending * Pipeline stages appearing left-to-right * Ecosystem nodes appearing around the center * Icons fading in * Arrows progressing through a workflow Do NOT use: * Excessive bouncing * Flashing * Spinning * Gaming-style transitions * Distracting motion Animation should reinforce the story. --- # 16. DATA VISUALIZATION RULES For salary slides and any numerical information: Use: * Staircase charts * Vertical progression * Horizontal progression * Minimal bar charts * Large numerical callouts Never use a dense spreadsheet. Always label salary information clearly as: **Indicative benchmark — subject to Industry Advisory Board validation** unless the source explicitly establishes a different status. --- # 17. ACADEMIC CONTENT TRANSFORMATION Do NOT turn every course from the handbook into a separate slide. Instead transform courses into **industry competency clusters**. ### AI Programming → ML → DL → GenAI → MLOps → Deployment ### DATA SCIENCE Python / SQL → Statistics → Analytics → ML → Data Engineering → Cloud ### SOFTWARE ENGINEERING Programming → DSA → Development → Architecture → Testing → Cloud / DevOps The audience should understand the **career capability progression**, not simply see a course catalog. --- # 18. SOURCE CONTENT TO EMPHASIZE Where supported by the handbooks, visually emphasize: ### PRODUCT-BASED LEARNING ### INDUSTRY-INTEGRATED CURRICULUM ### GLOBAL CERTIFICATIONS ### AI / DATA / SOFTWARE STARTUP OPPORTUNITIES ### EARNING BEFORE GRADUATION ### PORTFOLIO-BASED GRADUATION ### GLOBAL EXPOSURE ### ONE SEMESTER → ONE INDUSTRY PROBLEM ### LEARN → BUILD → DEPLOY → EARN ### REAL-WORLD PROJECTS ### INDUSTRY-READY GRADUATES Do not exaggerate these concepts beyond what the source documents state. --- # 19. KEY VISUAL PHRASES Use short powerful phrases throughout the deck: **LEARN → BUILD → DEPLOY → EARN** **ONE SEMESTER → ONE INDUSTRY PROBLEM** **1 STUDENT → 1 AI PRODUCT** **DATA → INSIGHT → DECISION** **IDEA → DESIGN → CODE → DEPLOY** **PROJECTS → PORTFOLIO → CAREER** **SKILLS → EXPERIENCE → EMPLOYABILITY** Use them as visual anchors, not as paragraphs. --- # 20. CONTENT DENSITY Each slide must pass this test: ### Can I understand the slide in 5 seconds? If not: * Remove text * Increase visual hierarchy * Convert bullets into icons * Convert explanations into diagrams * Convert lists into flows * Convert comparisons into visual structures --- # 21. PRESENTATION STORY ARC The deck should tell one continuous story: ### START Why industry alignment matters. ↓ ### VALIDATION What industry evaluates. ↓ ### AI What an AI graduate becomes. ↓ ### DATA SCIENCE What a Data Science graduate becomes. ↓ ### SOFTWARE ENGINEERING What a Software Engineering graduate becomes. ↓ ### COMPARISON How the three career ecosystems differ. ↓ ### END What an industry-ready graduate looks like. The deck should feel like one coherent story rather than three unrelated program presentations. --- # 22. FINAL QUALITY CONTROL Before generating the final presentation, internally verify: ### STRUCTURE * Exactly 36 slides * Slides 1–4 introduction * Slides 5–14 AI * Slides 15–24 Data Science * Slides 25–34 Software Engineering * Slides 35–36 conclusion ### VISUAL * Every slide has a meaningful visual * 75–85% visual content * Minimal text * No paragraphs * No text walls * No unnecessary tables * Strong visual hierarchy ### CONTENT * Source documents remain the primary authority * No unsupported university claims * No fabricated partnerships * No fabricated statistics * No fabricated employers * Salary figures clearly marked as indicative/subject to validation * Certifications remain consistent with source documents * Program terminology remains accurate ### DESIGN * Premium * Light * Professional * Editorial * Modern * Academic + Industry * Consistent typography * Consistent iconography * Consistent spacing * Subtle 3D * Subtle animations ### AUDIENCE The final deck must be appropriate for: **Industry Advisory Board + University Leadership + Faculty + Industry Professionals + Students** --- # FINAL INSTRUCTION Do not simply "put the information onto slides." **DESIGN THE INFORMATION.** Convert academic information into a **visual industry narrative**. Every slide should answer: > **What should the audience SEE, UNDERSTAND, and REMEMBER?** The final presentation should look like a **premium industry strategy / advisory board presentation**, not a conventional academic lecture deck. The dominant experience should be: # VISUAL → STORY → INSIGHT → CAREER OUTCOME Generate the final 36-slide presentation accordingly.

From Degree to Industry — Pathways, Skills & Roadmaps

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