C951 -Introduction to Artificial Intelligence
C951 -Introduction to Artificial Intelligence
C951 Introduction to Artificial Intelligence
Welcome to C951: Introduction to Artificial Intelligence! This course focuses on machine learning, reasoning, knowledge representation, uncertainty, intelligence, search strategies, agents, and robotics. You’ll demonstrate competency through two performance assessments -creating a bot and programming a robot.
Performance Assessment resources
For task 1, you need to use a free account on pandorabots.com. You do not need to deploy the bot. It will be developed, run, and evaluated completely through the pandorabots.com site. See C951 task 1 FAQ, directions, and advice.
Here are some videos to help you get started:
1.0 Chatbot Programming with Pandorabots API
2.0 Chatbot development with AIML 2.0
3.0 Chatbot development with AIML2.0
For task 2, you need to create a “disaster robot.” See C951 task 2 directions and rubric. If you choose your job wisely, you can complete the project with only minor changes to the tutorial file (found in C:\Program Files\CoppeliaRobotics\CoppeliaSimEdu\tutorials). Keep in mind that this is not a CoppeliaSim course. Like AIML, it’s a tool we use, but their technical aspects should not be the focus. I recommend looking at the included tutorial .ttt files and choosing a job within the scope of the tools provided by those sample files. You can copy, paste, modify those scripts. Download and install the free educational version from coppeliarobotics.com.
C951 task 2: getting started with CoppeliaSim
Begin to learn the CoppeliaSim system: CoppeliaSim (aka V-Rep) introduction and bump sensor implementation
For task 3, you need to write a proposal for a project implementing machine learning -but you do not need to create a project. See C951 task 3 directions and rubric. As an introduction to machine learning, Task 3 is meant to be a prelude to your capstone project (but you can do something completely different). Start by reading part V of the textbook (chapters 19-22). Then do some research online to get some ideas.
Examples of machine learning general applications
Examples of machine learning real-world applications
Presentation of a very nice student capstone project (this presentation was intended for a general audience)
Course-Related Links
Learning Resources
Academic Confidence, Study Skills, Test Anxiety, Test-Taking Skills. Find them at
Student Success tab / Student Success Center / View Our Learning Resources (large white box top right)
Vocabulary is essential. Know all the words that show up on the preassessment -incorrect choices included and all the words in the glossary below. This is a multiple-choice assessment. So you don’t need to memorize everything; you’ll need to be able to recall things in context.
Master computation problems. The preassessment computation problems are very similar to what you’ll see on the assessment. There are fewer of these, but we know they’re coming. With a cut score of 67%, get a high percentage correct of these, and you only need to get about 50-55% of the remaining questions.
Learning Resources ~ always available ~ to improve:
Academic Confidence, Study Skills, Test Anxiety, Test-Taking Skills. Find them at
Student Success tab / Student Success Center / View Our Learning Resources (large white box top right)