BBC551BMI551

Artificial Intelligence & Machine Learning Lab

L-T-P0-0-2 Credits1 Session2026-27 TypeLab / Practical
Appears in 2 semesters · 2 branches

BCA · Sem 5 (Lab, code BBC551) · MCA Integrated · Sem 5 (Lab, code BMI551)

List of Experiments / Activities

  1. 1Program to demonstrate different types of intelligent agents.
  2. 2Program to solve AI problems (4-3 water jug, 8 -puzzle, 4 queens, 8 queens).
  3. 3Program to implement uninformed search algorithm (Breadth-first search, Depth-first search, Bidirectional, Uniform Cost).
  4. 4Program to implement heuristic search algorithm (Hill climbing, Best-first search, A*, AO*).
  5. 5Program to implement different game playing techniques.
  6. 6Program to implement various knowledge representation techniques.
  7. 7Program to implement chaining algorithm (forward, backward).
  8. 8Program to implement Regression (linear, multi-linear, logistic).
  9. 9Program to implement Classification algorithm (Decision tree, support vector machine, K-nearest neighbor, Naïve Bayes)
  10. 10Program to implement clustering algorithm (k-means, Hierarchical)
  11. 11Program to implement Association rule learning techniques.
  12. 12Program to implement algorithm for Reinforcement learning.
  13. 13Program to pre-process a real-world data set.
  14. 14Program to import and explore a dataset and identify the missing / duplicate values.
  15. 15Program to split a dataset into training and testing datasets.
  16. Note: The Instructor may add/delete/modify experiments, wherever he/she feels in a justified manner.
Course Outcomes (COs)5 outcomes

After completion of the course student will be able to:

  1. CO1Demonstrate the working of different types of intelligent agents and apply AI problem solving techniques to solve problemsK2
  2. CO2Implement and analyze uninformed, informed and local search techniques for AI problem solving.K3
  3. CO3Develop programs for knowledge representation and reasoning.K3
  4. CO4Implement and analyze various supervised, unsupervised and reinforcement machine learning algorithms.K3
  5. CO5Implement and evaluate data preprocessing and data transformation techniquesK3

Official AKTU syllabus

This subject is on page 21 of the original AKTU PDF.

Official AKTU syllabus PDF ↗