PG Diploma Artificial Intelligence Syllabus and Subjects

Duration

Average Fees

INR 2 - 4 LPA

Rahil Ahmed

Updated on Oct 3, 2022 by Rahil Ahmed

Rahil Ahmed

Updated on Oct 3, 2022 by Rahil Ahmed

Post Graduate Diploma in Artificial Intelligence syllabus is a one-year-long postgraduate course where the students learn about growth in the business by moulding key strategies and decision-making capabilities through technology that can think like a human being.

Semester Wise PG DAI Syllabus

Post Graduate Diploma in Artificial Intelligence course syllabus helps students to learn to make a computer that can learn, plan, and solve the problems of humans autonomously. PG DAI course have been studied for more than half a century. Two semesters in the curriculum are equally combined into the one-year duration of the Post Graduate Diploma in Artificial Intelligence course. Post Graduate in Diploma in Artificial Intelligence subjects list is given below according to the semesters:

PG DAI First Year Syllabus

Semester I

Semester II

Introduction to AI

Pattern Recognition

Problem Formulation

Distance-Based Neural Networks

Production System

Multilayer Neural Network

Ontology

Decision Trees

Propositional Logic

Population-Based Search

First-Order Predicate Logic

Research Proposal

Fuzzy Logic

Research Project

PG DAI Subjects

Post Graduate Diploma in Artificial Intelligence subjects are divided into core and elective subjects. The curriculum is decided on the basis of the needs of the industry leaders, and hence, the education that the students receive is very relevant. Listed below are the PG DAI course subjects that are core in the curriculum and the students study about:

  • Machine Learning
  • Artificial Intelligence
  • Machine Learning
  • Deep Machine Learning
  • Algorithms
  • Types of Machine Learning
  • Linear Algebra
  • Regression

PG DAI Course Structure

In the Post Graduate Diploma in Artificial Intelligence course structure, the students learn about both the core and elective subjects. Additionally, there are practical lab sessions and theoretical classroom lectures. The core subjects are subjects that are considered vital for the students' learning. The elective subjects make the curriculum flexible and diverse. The course structure is given below:

  • II Semesters
  • Postgraduate Diploma Course
  • Core Subjects
  • Elective Subjects
  • Research Project

PG DAI Teaching Methodology and Techniques

The teaching methodologies of the PG DAI are designed with a mixture of traditional lectures, practical sessions, seminars and group discussions. The course has teaching methodologies and techniques designed to ensure that the students pursuing this course have access to all the infrastructure and facilities available. Listed below are the teaching methodology and strategies in general:

  • Lectures
  • Practical Sessions
  • Research Papers
  • Seminars
  • Group Discussions
  • Internships

PG DAI Projects

During the Post Graduate Diploma in Artificial Intelligence course, students are expected to work on a research project. This research project helps the assessors understand the students’ understanding of the specialization and subjects. Some of the popular Post Graduate Diploma in Artificial Intelligence project topics undertaken by the students are mentioned below:

  • Clustering
  • Reinforcement Learning
  • Neural Networks
  • Natural Language Processing
  • Predictive Analysis
  • Ensemble Techniques
  • Machine Learning Applications across Industries

PG DAI Reference Books

Post Graduate Diploma in Artificial Intelligence books are available for the students to rent, purchase, and download online. These books are a key part of the student’s learning as they can really help the students learn about their specialization in greater depth and detail. Listed below are some of the popular PG DAI books that the students can invest in:

PG DAI Reference Books

Name of Book

Author

Fundamentals of Data Structures in C‖,2nd edition

Ellis Horowitz, S. Sahni, Freed

Mastering C++

K.R.Venugopal, Rajkumar Buyya

Core Java Volume I—Fundamentals, 9th Ed (Core Series)

Cay S. Horstman and Gary Cornell

A Textbook of Engineering Mathematics

Erwin Kreyzig

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