Dr. GC Jana
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Artificial Intelligence (Theory & Lab) | CSE472 / CSP472
Offered by: Dr. Gopal Chandra Jana (Dr. GC Jana)
Assistant Professor, Department of CSE, SoCSE, Sharda University
Email: First_Name [dot] Last_Name {@} sharda.ac.in
Course Home Syllabus (CSE472) Syllabus (CSP472) Evaluations Schemes Lectures Lab Assignments Post Doubts Important Dates Course Feedback Check CA Marks Thanks Important Announcement

This Artificial Intelligence (Theory & Lab) (CSE472 / CSP472) course content is designed for undergraduate students in the Department of Computer Science and Engineering at Sharda University. The course provides a comprehensive foundation in Artificial Intelligence concepts, problem-solving techniques, and real-world applications. It is structured into five major units: Unit 1: Introduction to Artificial Intelligence, which covers the foundations, goals, and intelligent agents; Unit 2: Problem Solving Agents, focusing on search techniques such as Uninformed Search Strategies (such as BFS; DFS; UCS; DLS; IDS), Informed Search Strategies (Greedy Best-First; A* Search; Heuristic Functions) and Minimax & Alpha-Beta Pruning; Unit 3: Knowledge and Reasoning, which introduces logic, inference mechanisms, and reasoning methods; Unit 4: Learning Paradigms and Artificial Neural Networks, covering supervised, unsupervised, and reinforcement learning along with ANN models; and Unit 5: Applications of Artificial Intelligence, highlighting real-world use cases and future trends in AI. The lab component (CSP472) complements theoretical concepts through hands-on implementation using Python, LISP, PROLOG, and opensource AI/ML libraries, enabling students to develop and analyze intelligent systems. Students gain practical experience in algorithm design, model development, and solving real-world AI problems through course projects. The course is supported by structured lecture notes, reference books, Additional PPTs and study material links, assignments, lab experiments, interactive tools, and evaluation schemes, ensuring a balanced approach to both conceptual understanding and practical skill development.

πŸ“˜ Syllabus (CSE472 - Theory)

πŸ’» Syllabus (CSP472 - Lab)

πŸ“Š Evaluation Schemes

Component Theory (CSE472) Lab (CSP472)
Total Marks 100 (CA: 25 + MSE: 15 + ESE: 60) 100 (CA: 60 + ESE: 40)
Continuous Assessment β€’ Assessment 1: 10 Marks (Units 1 & 2)
β€’ Assessment 2: 5 Marks (Units 3 & 4)
β€’ Assignment 1: 5 Marks (Units 1 & 2)
β€’ Assignment 2: 5 Marks (Units 3, 4, and 5)
β€’ Practical Records File
β€’ Performance in experiments (In-Class)
β€’ Course Project (Implementation, Working Source Code, and Results)
β€’ Viva-Voce (throughout semester)
Mid Semester Exam 15 Marks NA
End Semester Exam 60 Marks 40 Marks

πŸ“š Lectures

Theory lecture materials have been uploaded unit-wise. Please go through and review all the lecture content and additional materials carefully. If you have any doubts, post them using the β€œPost Doubt” option.

πŸ§ͺ Artificial Intelligence Lab (CSP472)

πŸ’‘ Note: In the AI Lab, we will be using tools like CLIPS, PROLOG, Python, Google Colab, including various AI, ML, and DL libraries to perform the experiments.

πŸ“˜ List of Experiments

Find the list of lab experiments with instructions and notes.

πŸ”— View Experiments

πŸ“– Lab Manual

Download the official AI Lab Manual for complete guidelines.

⬇️ Download Lab Manual

πŸ“€ Lab Submissions

Please submit your lab reports and code files using your respective group link.

πŸ‘¨β€πŸ’» Submission Link for Group 1 πŸ‘©β€πŸ’» Submission Link for Group 2

πŸ“‘ Assignments

πŸ“Œ Common Instructions

  • All assignments must be submitted before the due date.
  • Upload your solution in PDF format.
  • Plagiarism will not be tolerated.
  • Late submissions may not be accepted.
  • All assignments must be handwritten. Answers and solutions should be presented in a clear, step-by-step illustrative manner. Running text format will not be accepted.
  • Students may be asked to explain their answers and solutions while obtaining the instructor’s signature. Grades will be awarded based on the explanation and understanding demonstrated.
  • If any AI tools (such as GPTs) are used in preparing the assignment, students must also submit the complete script or prompt history along with the assignment.

πŸ“˜ Assignment 1: Based on Unit-1 and 2

Due Date: 14th Feb 2026

  • All questions are compulsory.
  • Prepared and Submit as a single PDF file.
  • Submit scanned handwritten PDF document using the link mentioned below.
πŸ“„ View Assignment-1

πŸ”— Submit Here

πŸ“˜ Assignment 2: Based on Unit-3 and 4

Due Date: 27th March 2026

  • All questions are compulsory.
  • Include clear reasoning steps.
  • Submit scanned handwritten PDF document using the link mentioned below.
πŸ“„ View Assignment-2

πŸ”— Submit Here

❓ Post Your Doubts

Please fill in your details and doubt. Your submission will be recorded securely.







πŸ“… Important Dates

Theory (CSE472)
  • Assessment 1: 19th Feb to 23 Feb 2026 (Units 1 & 2) βœ”οΈ
  • Assessment 2: 06 Apr to 12 Apr 2026 (Units 3 & 4) βœ”οΈ
  • Assignment 1: 14 Feb 2026 (Submission) βœ”οΈ
  • Assignment 2: 20th March 2026 (Submission) βœ”οΈ
  • Mid Semester Exam: 9th to 14th March 2026 βœ”οΈ
  • End Semester Exam: As per University Schedule
Lab (CSP472)
  • Practical Records File: Ongoing (Weekly Check) βœ”οΈ
  • Performance in Experiments: Continuous (In-Class) βœ”οΈ
  • Course Project: Final Submission – 15 Apr 2026 βœ”οΈ
  • Viva-Voce: Throughout Semester βœ”οΈ
  • End Semester Lab Exam (External): As per University Schedule βœ”οΈ

πŸ’‘ Your feedback is extremely valuable in improving the course content and teaching effectiveness. Please take a few minutes to share your thoughts and suggestions with me.

πŸš€ Fill Out the Feedback Form

Thanks From Your Course Instructor

Dear Students,

Thank you for your active participation in the course. Your enthusiasm, curiosity, and commitment make this learning journey inspiring.

Keep asking questions, keep exploring, and never stop learning!

β€” Dr. Gopal Chandra Jana
(Course Instructor)