CIM10 theme will be the Future of Software Development

CIM10 Project Instructions


Consult canvas discussion board and/or assignment page. This page and also the canvas conferences/expo page are two best places for deciding on project. But you need to pick one project,
Listed below are several project groups and titles, you need to look through and come up with a project. Your project title should be unique.

Consult schedule and canvas for exact dates. But in general projects have following key canvas milestones:

  • 05/04 Review AI Projects

    Think about something you want to do
    cliché: Those who are good at what they do are surpassed by those who work hard. Those who work hard are surpassed by those who love what they are doing.

  • 05/11 Present 5-10 Minute
    Create a Presenstation and/or Research your project. You may use AI to help with presentation, but you must do most of the work yourself.

  • Sunday 05/18 4-6PM Present 5-10 Minute On Project Thesis
    Select a tentative project title and post title on canvas discussion board
    Go back to the previous projects and watch student webcasts that are similar to your idea

AI Apps & Devices

AI Movies

  • Robot Movies -
    • The Day the Earth Stood Still
    • Westworld
    • I Robot
    • Terminator - AI Takes Over
    • Ex Machina
    • 2001: A Space Odyssey - IBM HAL had nervous breakdown (2010)
    • Blade Runner
    • A.I. Artificial Intelligence (wanted to come to life)
  • 1970s - Looking at AI being Self Aware and a Lot Smarter than it is.
  • 1990s
    • Matrix - Software-simulated Society
      Project related do we live in a software-simulated society - in the future can we develop the technology?
    • Terminator
  • Ready Player One (AR/VR world)
  • 2006 A spoof movie: Idiocracy, but if we become to dependent on automation and AI, what will our future look like.

AI SW/Game Development

AI Generated Ideas

Here are a few project ideas for a 10-minute PowerPoint presentation on AI, ML, and deep learning, tailored for a basic introduction to computers and office applications class:

  1. AI in Everyday Life
    • Objective: Students explore how AI is integrated into daily tools and services.
    • Content:
      • Slide 1: Title and introduction to AI.
      • Slides 2-3: Define AI, ML, and deep learning in simple terms (e.g., AI as "smart machines," ML as "learning from data," deep learning as "mimicking the brain").
      • Slides 4-6: Examples like virtual assistants (Siri, Alexa), recommendation systems (Netflix, YouTube), or facial recognition.
      • Slides 7-8: Benefits (e.g., convenience, efficiency) and challenges (e.g., privacy, bias).
      • Slide 9: Future of AI in daily life.
      • Slide 10: Conclusion and references.
    • Skills: Basic PowerPoint formatting, inserting images, and creating clear text slides.
  2. The Evolution of AI: Past, Present, Future
    • Objective: Students present a timeline of AI development.
    • Content:
      • Slide 1: Title and overview.
      • Slides 2-4: History of AI (e.g., 1950s Turing Test, 1980s expert systems, 2010s deep learning breakthroughs).
      • Slides 5-7: Current applications (e.g., self-driving cars, medical diagnostics, chatbots like Grok).
      • Slides 8-9: Predictions for AI’s future (e.g., smarter robots, ethical concerns).
      • Slide 10: Summary and sources.
    • Skills: Using timelines or SmartArt in PowerPoint, adding transitions, and organizing content chronologically.
  3. How AI is Changing a Specific Industry
    • Objective: Students pick an industry (e.g., healthcare, education, gaming) and explain AI’s impact.
    • Content:
      • Slide 1: Title and chosen industry.
      • Slides 2-3: Brief explanation of AI, ML, or deep learning relevant to the industry.
      • Slides 4-6: Specific examples (e.g., AI diagnosing diseases in healthcare, personalized learning in education).
      • Slides 7-8: Pros (e.g., faster processes) and cons (e.g., job displacement).
      • Slide 9: Future potential in the industry.
      • Slide 10: Conclusion and references.
    • Skills: Researching online, inserting charts or infographics, and applying consistent slide themes.
  4. AI Myths vs. Reality
    • Objective: Students debunk common misconceptions about AI.
    • Content:
      • Slide 1: Title and introduction.
      • Slides 2-3: What AI, ML, and deep learning actually are (simple definitions).
      • Slides 4-6: Common myths (e.g., “AI will take over the world,” “AI is only for geniuses”) and the reality (e.g., AI is a tool, anyone can learn about it).
      • Slides 7-8: Real-world AI examples to clarify myths.
      • Slide 9: Why understanding AI matters.
      • Slide 10: Summary and sources.
    • Skills: Adding animations, using bullet points effectively, and creating visually engaging slides.

    Tips for Students:

    • Use simple language since it’s an introductory class.
    • Include visuals (e.g., AI-related images, diagrams of neural networks) to make slides engaging.
    • Practice timing to fit the 10-minute limit (about 1 minute per slide).
    • Cite sources (e.g., websites, articles) on the final slide.

    Instructor Notes:

    • Provide a PowerPoint template with a consistent theme to simplify formatting.
    • Encourage students to use online resources like simplified AI articles or videos for research.
    • If time allows, have students present to practice public speaking and PowerPoint navigation.

    Let me know if you’d like a sample outline for one of these or additional ideas!

    • DeepLearning.AI
      • Why It’s Useful: Founded by AI expert Andrew Ng, this platform offers beginner-friendly courses and resources on AI, ML, and deep learning. It includes short, digestible explanations and real-world examples perfect for presentation content.
      • What to Explore:
        • Free introductory videos and articles on AI concepts (e.g., “What is Machine Learning?”).
        • Practical examples like neural networks for image recognition or chatbots.
        • The “AI for Everyone” course (free to audit) provides non-technical insights into AI applications.
      • How It Helps: Students can use clear definitions and case studies for slides on how AI impacts industries like healthcare or education.
      • Link: https://www.deeplearning.ai[](https://www.deeplearning.ai/)
    • Google AI / Machine Learning Crash Course
      • Why It’s Useful: Google’s platform provides free, interactive tutorials and a comprehensive Machine Learning Crash Course with animated videos and hands-on exercises. It’s designed for beginners and covers AI, ML, and deep learning fundamentals.
      • What to Explore:
        • The Crash Course modules on linear regression, neural networks, and classification models for simple explanations.
        • Teachable Machine (no-code tool to train basic ML models with images or sounds, great for demonstrating concepts).
        • Case studies on Google’s AI applications (e.g., translation, image recognition).
      • How It Helps: Students can include screenshots of Teachable Machine experiments or Google’s real-world AI examples in their slides.
      • Links:
    • Fast.ai
      • Why It’s Useful: Fast.ai offers a free, beginner-friendly course called “Practical Deep Learning for Coders” that emphasizes practical applications over heavy theory. It’s great for understanding how deep learning works in real life.
      • What to Explore:
        • Free lessons on computer vision, natural language processing (NLP), and tabular data analysis.
        • The accompanying book (free online) with examples like building a model to classify images.
        • Student project showcases on their forum for inspiration (e.g., simple AI models for games).
      • How It Helps: Students can use Fast.ai’s visuals, like neural network diagrams, or discuss simplified examples in their presentations.
      • Link: https://course.fast.ai[](https://course.fast.ai/)
    • Kaggle
      • Why It’s Useful: Kaggle is a hub for data science and ML with beginner-friendly tutorials, datasets, and community projects. It’s ideal for finding real-world ML applications to feature in presentations.
      • What to Explore:
        • Free “Kaggle Learn” micro-courses on ML basics, Python, and deep learning.
        • Public notebooks with simple projects (e.g., sentiment analysis, image classification).
        • Datasets on topics like movie recommendations or medical imaging for relatable examples.
      • How It Helps: Students can cite Kaggle project examples or include dataset visuals to show how ML processes data.
      • Link: https://www.kaggle.com[](https://ai-pro.org/learn-ai/articles/the-top-ai-resources-for-learning-courses-and-online-platforms/)
    • Towards Data Science (Medium)
      • Why It’s Useful: This Medium publication features beginner-friendly articles on AI, ML, and deep learning written by practitioners. It’s a great source for understandable explanations and case studies.
      • What to Explore:
        • Articles on topics like “How Netflix Uses AI” or “Introduction to Neural Networks.”
        • Tutorials on simple ML projects (e.g., predicting house prices with regression).
        • Opinion pieces on AI ethics for discussing challenges in presentations.
      • How It Helps: Students can summarize articles for slides or use infographics from posts to enhance visuals.
      • Link: https://towardsdatascience.com[](https://unicornplatform.com/blog/top-10-machine-learning-websites-you-need-to-follow-in-2023/)
    • Analytics Vidhya
      • Why It’s Useful: Analytics Vidhya provides tutorials, articles, and project ideas focused on data science, AI, and ML, with a beginner-friendly approach.
      • What to Explore:
        • Guides on ML algorithms (e.g., decision trees, neural networks).
        • Project ideas like building a recommendation system or analyzing social media sentiment.
        • Hackathons and competitions for inspiration on practical AI applications.
      • How It Helps: Students can find step-by-step project breakdowns to explain in their presentations or use code snippets as visuals.
      • Link: https://www.analyticsvidhya.com[](https://unicornplatform.com/blog/top-10-machine-learning-websites-you-need-to-follow-in-2023/)

    Tips for Students Using These Sites:

    • Research: Look for beginner-level content or search terms like “introduction to AI” or “machine learning for beginners” to avoid complex material.
    • Visuals: Download diagrams, charts, or screenshots from these sites (with proper attribution) to make PowerPoint slides engaging.
    • Citations: Include a reference slide citing these websites (e.g., “DeepLearning.AI, 2025”).
    • Examples: Focus on relatable applications (e.g., AI in Netflix, self-driving cars) to make presentations accessible to classmates.

    Additional Notes for Instructors:

    • Encourage students to explore one or two sites to keep research manageable.
    • Suggest using Google’s Teachable Machine for a hands-on demo (students can create a simple model and screenshot results for slides).
    • Provide a list of these URLs or a shared document to ensure easy access.

    If you’d like, I can generate a sample PowerPoint slide layout or provide more specific project examples from these sites! Let me know.

    Below are project ideas for a 10-minute PowerPoint presentation on the theme of AI, machine learning (ML), and deep learning, specifically focusing on their impact on employment, layoffs, work-week, and future jobs.

    1. AI and the Future of Work: Opportunities and Challenges

    • Objective: Students explore how AI is reshaping jobs, creating new opportunities, and causing disruptions like layoffs.
    • Content:
      • Slide 1: Title slide (e.g., “AI’s Impact on the Future of Work”) and student name.
      • Slides 2-3: Brief introduction to AI, ML, and deep learning (e.g., “AI automates tasks, ML learns from data, deep learning mimics human thinking”).
      • Slides 4-5: How AI affects jobs:
        • Examples of automation (e.g., AI in manufacturing replacing repetitive tasks, chatbots in customer service).
        • Layoffs caused by AI (e.g., retail self-checkouts reducing cashier roles).
      • Slides 6-7: New jobs created by AI:
        • Roles like AI trainers, data scientists, or ethics consultants.
        • Example: Demand for AI specialists grew 74% annually from 2015-2019 (source: World Economic Forum).
      • Slide 8: Impact on work-week:
        • AI could shorten work-weeks by automating tasks (e.g., experiments with 4-day work-weeks).
      • Slide 9: Future outlook: Balancing job losses with upskilling (e.g., learning AI tools).
      • Slide 10: Conclusion and references (e.g., cite World Economic Forum, news articles).
    • PowerPoint Skills: Use SmartArt for job creation vs. loss comparison, insert relevant images (e.g., robots, AI interfaces), and apply slide transitions.
    • Why It Works: Covers both positive and negative impacts, encouraging critical thinking about AI’s role in employment.

    2. Will AI Take Our Jobs? Myths and Realities

    • Objective: Students debunk myths about AI causing widespread unemployment and highlight realistic impacts on jobs and work-weeks.
    • Content:
      • Slide 1: Title slide (e.g., “AI and Jobs: Separating Fact from Fiction”).
      • Slides 2-3: Define AI, ML, and deep learning simply (e.g., “AI is like a smart assistant, ML learns patterns, deep learning solves complex problems”).
      • Slides 4-5: Common myths:
        • Myth: “AI will replace all jobs.”
        • Reality: AI automates tasks, not entire jobs (e.g., accountants use AI for data analysis but still make decisions).
      • Slides 6-7: Real impacts:
        • Layoffs in sectors like manufacturing (e.g., 30% of factory tasks automated by 2030, per McKinsey).
        • New roles in AI development, cybersecurity, and human-AI collaboration.
      • Slide 8: Work-week changes: AI boosting productivity, potentially leading to shorter work-weeks (e.g., Japan’s Microsoft 4-day week trial).
      • Slide 9: Preparing for the future: Importance of learning AI-related skills (e.g., coding, data analysis).
      • Slide 10: Summary and sources (e.g., McKinsey reports, news on work-week trials).
    • PowerPoint Skills: Create a myth vs. reality table, use animations to reveal points, and include charts showing job trends.
    • Why It Works: Engages students by addressing fears about AI while providing a balanced view of job impacts.

    3. AI’s Role in Redefining the Work-Week

    • Objective: Students investigate how AI could lead to shorter work-weeks and what this means for employment.
    • Content:
      • Slide 1: Title slide (e.g., “Can AI Give Us a Shorter Work-Week?”).
      • Slides 2-3: Overview of AI, ML, and deep learning (e.g., “AI automates repetitive tasks, freeing up human time”).
      • Slides 4-5: How AI boosts productivity:
        • Examples: AI scheduling tools, automated report generation, or ML optimizing supply chains.
        • Case study: Microsoft Japan’s 4-day work-week trial increased productivity by 40% using AI tools.
      • Slides 6-7: Impact on employment:
        • Potential for fewer hours but same output, reducing burnout.
        • Risk of layoffs if companies cut jobs instead of hours.
      • Slide 8: Future jobs: Roles that support AI-driven workplaces (e.g., AI system managers, productivity analysts).
      • Slide 9: Challenges: Ensuring fair access to shorter work-weeks and retraining workers.
      • Slide 10: Conclusion and references (e.g., cite Microsoft trial, productivity studies).
    • PowerPoint Skills: Insert infographics on productivity gains, use consistent slide themes, and embed a short video clip (if allowed) about work-week experiments.
    • Why It Works: Focuses on a trending topic (shorter work-weeks) that resonates with students and ties directly to AI’s workplace impact.

    4. Jobs of the Future: How AI is Creating New Careers

    • Objective: Students highlight emerging AI-driven careers and discuss how current jobs may evolve, addressing concerns about layoffs.
    • Content:
      • Slide 1: Title slide (e.g., “AI and the Jobs of Tomorrow”).
      • Slides 2-3: Introduction to AI, ML, and deep learning (e.g., “AI powers innovation, ML finds patterns, deep learning solves big problems”).
      • Slides 4-5: Jobs at risk of automation:
        • Examples: Data entry, assembly line work (e.g., 47% of jobs at risk by 2030, per Oxford study).
        • Layoff trends in industries like retail or logistics.
      • Slides 6-7: New AI-driven careers:
        • Roles like AI ethicists, machine learning engineers, or robotic process automation specialists.
        • Growing demand: AI job postings up 119% from 2018-2022 (source: LinkedIn).
      • Slide 8: Work-week impact: AI enabling flexible or remote work through automation.
      • Slide 9: How to prepare: Learning AI basics, soft skills like creativity, and adaptability.
      • Slide 10: Summary and sources (e.g., LinkedIn reports, Oxford studies).
    • PowerPoint Skills: Use icons to represent new job roles, create a timeline of job evolution, and apply slide animations for emphasis.
    • Why It Works: Optimistic focus on new opportunities while acknowledging automation’s challenges, encouraging students to think about their future careers.

    Recommended Resources for Research
    To support these projects, students can explore the following beginner-friendly websites for data, case studies, and visuals on AI’s impact on employment:

    • World Economic Forum (weforum.org): Reports on the “Future of Jobs” with stats on AI-driven job creation and losses.
    • McKinsey & Company (mckinsey.com): Articles on AI automation, work-week trends, and industry impacts (search “AI and employment”).
    • LinkedIn Economic Graph (linkedin.com): Insights on emerging AI job roles and hiring trends.
    • BBC News or The Guardian: Search for articles on AI layoffs or work-week experiments (e.g., Microsoft Japan’s 4-day week).
    • Towards Data Science (towardsdatascience.com): Beginner-friendly articles on AI’s workplace effects and future careers.

    Tips for Students

    • Simplify Content: Use analogies (e.g., “AI is like a super-smart calculator”) to explain complex ideas.
    • Visuals: Include images of AI in action (e.g., robots, self-checkout machines) or charts showing job trends. Download visuals from cited sources with proper attribution.
    • Timing: Aim for 1 minute per slide (10 slides = 10 minutes). Practice pacing to avoid rushing.
    • Citations: List sources on the final slide (e.g., “McKinsey, 2023”) to build credibility.

    Instructor Notes

    • Provide a PowerPoint template with pre-set fonts and colors to focus students on content creation.
    • Encourage group discussions before research to brainstorm job examples (e.g., “What jobs do you think AI could replace?”).
    • Suggest using Google Scholar or news sites for recent stats (e.g., search “AI layoffs 2025” or “AI work-week impact”).
    • If possible, allow students to present in small groups to build confidence using PowerPoint’s presenter view.

    Let me know if you’d like a detailed slide-by-slide outline for one of these ideas, sample PowerPoint visuals, or additional resources tailored to this topic!

     

    1. AI-Powered Galaxy Exploration: Navigating the Cosmos

    • Objective: Students explore how AI can enhance space exploration, from analyzing distant stars to guiding spacecraft.
    • Content:
      • Slide 1: Title slide (e.g., “AI: The Key to Exploring the Galaxy”).
      • Slides 2-3: Introduction to AI, ML, and deep learning (e.g., “AI makes decisions, ML learns from space data, deep learning analyzes images like a brain”).
      • Slides 4-5: AI in galaxy exploration:
        • Autonomous spacecraft navigation (e.g., NASA’s AI systems for Mars rovers like Perseverance).
        • ML analyzing telescope data (e.g., identifying exoplanets with Google’s ML algorithms).
      • Slides 6-7: Deep learning applications:
        • Classifying galaxies or detecting habitable planets from Hubble or James Webb Space Telescope images.
        • Example: AI discovered 301 new exoplanets in 2021 using Kepler data.
      • Slide 8: Benefits: Faster data analysis, cost-efficient missions, and exploring unreachable regions.
      • Slide 9: Challenges: AI errors in space or ethical concerns about autonomous systems.
      • Slide 10: Conclusion and references (e.g., NASA, Google AI blog).
    • PowerPoint Skills: Insert images of telescopes or rovers, use animations to show AI processing data, and create a starry background theme.
    • Why It Works: Connects AI to exciting space missions, making it engaging and relatable for students.

    2. Terraforming Planets with AI: Building New Worlds

    • Objective: Students investigate how AI could help terraform planets like Mars or Venus for human habitation.
    • Content:
      • Slide 1: Title slide (e.g., “Can AI Terraform Mars?”).
      • Slides 2-3: Define AI, ML, and deep learning (e.g., “AI plans terraforming, ML optimizes resources, deep learning models environments”).
      • Slides 4-5: What is terraforming?
        • Transforming a planet’s atmosphere, temperature, or surface to support life.
        • Examples: Adding oxygen to Mars or cooling Venus.
      • Slides 6-7: AI’s role in terraforming:
        • ML simulating climate models to predict terraforming outcomes (e.g., NASA’s Mars climate simulations).
        • Deep learning designing robotic systems to release greenhouse gases or build habitats.
      • Slide 8: Future potential: AI coordinating drones to plant algae or melt polar ice caps on Mars.
      • Slide 9: Challenges: Time (centuries for terraforming), costs, and ethical concerns (e.g., altering planets).
      • Slide 10: Summary and sources (e.g., NASA, scientific articles).
    • PowerPoint Skills: Use diagrams of planetary atmospheres, embed a short video clip of Mars (if allowed), and apply consistent slide transitions.
    • Why It Works: Combines sci-fi appeal with practical AI applications, sparking creativity.

    3. AI as the Brain of Interstellar Missions

    • Objective: Students explore how AI could enable long-distance space missions to explore or colonize the galaxy.
    • Content:
      • Slide 1: Title slide (e.g., “AI: Guiding Humanity to the Stars”).
      • Slides 2-3: Overview of AI, ML, and deep learning (e.g., “AI controls spacecraft, ML maps routes, deep learning finds habitable zones”).
      • Slides 4-5: AI in interstellar exploration:
        • Autonomous navigation for missions beyond our solar system (e.g., AI for Breakthrough Starshot’s nanocraft to Alpha Centauri).
        • ML predicting asteroid threats or cosmic radiation risks.
      • Slides 6-7: AI for colonization:
        • Deep learning designing self-sustaining habitats on exoplanets.
        • Example: AI optimizing resource use (water, oxygen) for future space colonies.
      • Slide 8: Benefits: Enabling missions humans can’t directly control due to distance.
      • Slide 9: Challenges: AI reliability over decades, communication delays, and ethical issues.
      • Slide 10: Conclusion and references (e.g., Breakthrough Starshot, NASA).
    • PowerPoint Skills: Create a timeline of interstellar missions, use space-themed templates, and insert charts showing AI’s role in mission planning.
    • Why It Works: Appeals to students’ interest in interstellar travel while grounding ideas in current AI capabilities.

    4. AI and the Search for Habitable Planets

    • Objective: Students focus on how AI helps identify and prepare distant planets for potential human settlement or exploration.
    • Content:
      • Slide 1: Title slide (e.g., “AI’s Role in Finding New Earths”).
      • Slides 2-3: Introduction to AI, ML, and deep learning (e.g., “AI searches for planets, ML analyzes data, deep learning predicts habitability”).
      • Slides 4-5: AI in exoplanet discovery:
        • Deep learning analyzing light curves from telescopes (e.g., NASA’s TESS mission using AI to find exoplanets).
        • Example: Google’s ML identified two new planets in the Kepler-90 system.
      • Slides 6-7: AI for terraforming preparation:
        • ML modeling soil or water conditions on Mars or exoplanets.
        • AI designing robotic systems to test planetary surfaces for human survival.
      • Slide 8: Future vision: AI scouting planets for colonization or mining resources.
      • Slide 9: Challenges: Limited data, high costs, and ethical debates about planetary changes.
      • Slide 10: Summary and sources (e.g., NASA TESS, Google AI).
    • PowerPoint Skills: Use infographics of exoplanet data, apply slide animations to reveal discoveries, and include images of distant planets.
    • Why It Works: Ties AI to the exciting quest for new worlds, encouraging students to think big.

    Recommended Resources for Research
    Students can use these beginner-friendly websites to find information, visuals, and examples for their presentations:

    • NASA (nasa.gov): Articles on AI in Mars rovers, exoplanet discovery, and climate modeling. Search “AI space exploration” or “Mars terraforming.”
    • Google AI Blog (ai.googleblog.com): Case studies on ML for exoplanet detection and space data analysis.
    • Breakthrough Initiatives (breakthroughinitiatives.org): Information on AI for interstellar missions like Starshot.
    • Space.com: News articles on AI in space exploration and terraforming concepts (search “AI terraform Mars”).
    • Towards Data Science (towardsdatascience.com): Beginner-friendly articles on AI applications in astronomy and planetary science.

    Tips for Students

    • Simplify Concepts: Use analogies (e.g., “AI is like a cosmic GPS for spacecraft”) to explain complex ideas.
    • Visuals: Include images of Mars, exoplanets, or telescopes from NASA (cite sources). Download diagrams of AI systems or planetary models for slides.
    • Timing: Keep each slide to ~1 minute (10 slides = 10 minutes). Rehearse to stay within the limit.
    • Citations: List sources on the final slide (e.g., “NASA, 2025”) for credibility.

    Instructor Notes

    • Provide a PowerPoint template with a space-themed design (e.g., starry backgrounds, futuristic fonts) to streamline formatting.
    • Encourage students to explore NASA’s free image gallery for high-quality visuals.
    • Suggest group brainstorming sessions to discuss sci-fi-inspired ideas (e.g., “How would AI build a Mars base?”) before research.
    • If time allows, have students present using PowerPoint’s presenter view to practice navigation skills.

    Let me know if you’d like a detailed slide outline for one of these ideas, sample PowerPoint visuals, or more resources specific to AI in space exploration or terraforming!