Knowledge Representation
If you like applying Knowledge Representation, every challenge here gives you a chance to practice it on a real industry brief.
- CodeBeginnerNew
Intelligent Agent for a Smart-Thermostat Pricing-Aware Schedule
Design an intelligent agent with: perception (read sensor history), basic learning (cluster comfort intervals from 7 days of observations), decision-making (schedule heating to …
- Intelligent Agents
- Basic Learning
- Python Or Javascript
Introduction to Artificial Intelligence (CS Elective) - CodeBeginnerNew
Knowledge-Graph Recommender for a Niche Online Bookstore
Model the catalog as a knowledge graph (nodes: books, authors, genres, themes, eras, awards; edges: wrote, in-genre, has-theme, won, similar-to). Use Neo4j or a simple Python in…
- Knowledge Representation
- Knowledge Graphs
- Python Or Javascript
Introduction to Artificial Intelligence (CS Elective) - CodeBeginnerNew
Reason about Drone Mission Plans with Probabilistic Logic
Build a small Bayesian network (around 12 nodes) capturing weather, no-fly-zone proximity, battery state, operator certification, and mission risk. Implement exact inference (va…
- Bayesian Networks
- Probabilistic Inference
- Knowledge Representation
Introduction to Artificial Intelligence
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
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