PG Diploma – Artificial Intelligence

Artificial Intelligence (AI) is one of the most current popular in the field of computer science and engineering. Artificial Intelligence is immersive and has a huge impact on society.AI deals with intelligent behavior, learning, and adaptation in machines, robots, and body-less computer programs. AI is everywhere: search engines use it to improve answers to queries, to recognize speech, to translate languages, email programs use it to filter spam, banks use it to predict exchange rates and stock markets, doctors use it to recognize tumors, robots use it to localize themselves and obstacles, autonomous cars use it to drive, video games use it to enhance the player’s experience, adaptive telescopes use it to improve image quality, smartphones use it to recognize objects/faces/gestures/voices/music, etc. Finally, all AI students are trained to be academic professionals and need the academic and professional skills and mind-set that come with such positions.

People are conversing the possibility of intelligent learning and AI risks. Big companies such as Google, Amazon, Baidu, Microsoft etc. are investing billions in AI, and the AI-related job market is growing extremely rapidly.

PG Diploma in Artificial Intelligence covers the essential aspects of customary symbolic and sub- symbolic aspects. This One year with industry oriented program divided into Two semesters which offers wide-range of learning modules including machine learning techniques, IOT, neural network and fuzzy logic, computer vision, robotics, etc. with four credits each and with course structure meticulously designed which helps in developing extensive skill set suitable for further research, study and application development.

This course will introduce the basic principles in artificial intelligence research. It will cover simple exemplification schemes, problem solving paradigms, constraint propagation, and search strategies. Areas of application such as knowledge representation, natural language processing, expert systems and robotics will be explored. The LISP, PROLOG, PYTHON and R-Programming language will also be introduced.

Duration: 1 year Program
  • Communicate clearly and effectively using the technical language of the field correctly.
  • Describe the key components of the artificial intelligence (AI) areas and its relation and role in Computer Science.
  • Identify and describe artificial intelligence techniques, knowledge representation, automated planning and agent systems, machine learning, and probabilistic reasoning.
  • Implement and design appropriate AI solution techniques for such problems.
  • Analyze and understand the computational trade-offs involved in applying different AI techniques and models.
  • Understand Comprehend and differentiate between theoretical concepts and practical aspects of machine learning.
  • Implement classical Artificial Intelligence techniques, such as search algorithms, minimax algorithm, neural networks.
  • Understand and master the concepts and principles of machine learning, including its mathematical and heuristic aspects.
  • Understand neural networks and multi-layer data abstraction, empowering you to analyze and utilize data like never before.
  • Ability to apply Artificial Intelligence techniques for problem-solving and explain the limitations of current Artificial Intelligence techniques.
  • To have an understanding of the basic issues of knowledge representation and blind and heuristic search, as well as an understanding of other topics such as minimax, resolution, etc. that play an important role in AI programs.
  • A minimum aggregate score of 55% at the level of graduation in B.Sc.-IT/ B.E./B.Tech. or an equivalent degree with Mathematics as one of the main subjects of study completed from a recognized Institute or University.
  • Candidates waiting for their final year’s exam results can also apply for this course on a provisional basis.
  • Past academic credentials
  • Completion of Application Form including Statement of Purpose.
  • Entrance Test.
  • Personal Interview.

SEMESTER-I

S.No. Module Name Credit
1. Introduction to AI 4
2. Real Time Operating System 4
3. Natural Language Processing 4
4. Business Intelligence 4
5. Neural Network and Fuzzy Logic 4

 

SEMESTER-II

S.No. Module Name Credit
1. Pattern Recognition 4
2. Machine Learning 4
3. Python Programming 4
4. Automatic Speech Recognition 4
5. Computer Graphics 4