Page 13 - AI Ver 3.0 class 10_Flipbook
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SUB-UNIT                   LEARNING OUTCOMES                    SESSION/ ACTIVITY/ PRACTICAL
                  Statistical  Data:  Use  Case  Relate  AI  project  stages  to  the  stages  of  No-Code  AI  Session
                  Walk through         projects                                  ● Important concepts in Statistics.
                                       Able to use no-code tool Orange Data mining.  ● Orange data mining
                                       To  perform  data  exploration,  modeling  and  evaluation   ●  AI  project  cycle  in  Orange  data  mining  (Palmer
                                       with Orange data mining.                   penguins case study)

                                                                                 Activity: MS Excel for Statistical Analysis.
                                                                                 Link: https://docs.google.com/spread-
                                                                                 sheets/d/1f5G-JXyP7EV2fy1hax47YVaH5gyq8KZy/
                                                                                 edit?usp=drive_link&ouid=109928090180926267402
                                                                                 &rtpof=true&sd=true
                                                                                 Case study using Orange data mining (Palmer
                                                                                 Penguins).
                                                                                 Link: https://drive.google.com/drive/u/0/folders/1fm-
                                                                                 cRVb-ilTyUhmUv4DWT1BFsaCoQ2BmF

                 UNIT 5: Computer Vision (To be assessed through Theory)
                        SUB-UNIT                   LEARNING OUTCOMES                    SESSION/ ACTIVITY/ PRACTICAL
                  Introduction         Define the concept of Computer Vision and understand  Session: Introduction to Computer Vision
                                       its applications in various fields.       Session: Applications of CV
                  Concepts of Computer   Understand the basic concepts of image representation,  Session: Understanding CV Concepts
                  Vision               feature extraction, object detection, and segmentation.  ● Computer Vision Tasks
                                                                                 ● Basics of Images-Pixel, Resolution, Pixel value
                                                                                 ● Grayscale and RGB images
                                                                                 Activities:
                                                                                 ● Game- Emoji Scavenger Hunt
                                                                                     https://emojiscavengerhunt.withgoogle.com/
                                                                                 ● RGB Calculator:
                                                                                     https://www.w3schools.com/colors/colors_rgb.asp
                                                                                 ● Create your own pixel art:
                                                                                    www.piskelapp.com
                                                                                 ● Create your own convolutions:
                                                                                    http://setosa.io/ev/image-kernels/

                 UNIT 5: Computer Vision (To be assessed through Practicals)
                        SUB-UNIT                   LEARNING OUTCOMES                    SESSION/ ACTIVITY/ PRACTICAL
                  No-Code AI Tools     To  demonstrate  proficiency  in  using  no-code  AI  tools  Introduction to Lobe: https://www.lobe.ai/
                                       for  computer  vision  projects.  To  deploy  models,  fine-  Teachable Machine:
                                       tune  parameters,  and  interpret  results.  Skills  acquired
                                                                                  https://teachablemachine.withgoogle.com/
                                       include data preprocessing, model selection, and project
                                                                                  ● Activity: Build a Smart Sorter
                                       deployment.
                                                                                  Orange Data Mining Tool:
                                                                                  https://orangedatamining.com/download/
                                                                                  ●  Activity: Build a real-world Classification Model:
                                                                                   Coral Bleaching (Use Case Walkthrough)
                                                                                  ●  Link to the steps involved in project development
                                                                                   and dataset:
                                                                                  https://drive.google.com/drive/folders/1ppJ4d-8yOFJ
                                                                                  2G22rHHpjNrK0ejdIAe5Q?usp=sharing





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