MS Artificial Intelligence

MS(AI) degree really gives students a solid foundation of skills and knowledge that are crucial to helping them adapt to the rapid changes taking place there. The AI degree program provide the foundation and advanced skills in the principles and technologies underlying AI, including logic, representation of knowledge, probabilistic models, and machine learning. Students can pursue topics in depth, with courses available in areas such as computer vision, remote sensing, data science and natural language processing.

Artificial Intelligence is a fast-paced and challenging field that establishes it as the main driving force of major industries in the near future. The revolutionary changes that it is bringing forth are becoming more apparent, whether it’s in your smartphone or in the soon-to-be-realized prospect of self-driving vehicles.

AI technologies are the next big thing, and to make it big in the field, have to equip with the necessary skills and knowledge to gain not only a preemptive advantage but long-term adaptability as well. Whether it’s deep learning, healthcare applications, natural language processing, data analytics or big-data mining, AI pretty much covers all these fields and a lot of companies are looking for individuals that specialize on it.

The decision-making in businesses today demands the skills in analysis of history databases and automated-expert assistance to ensure uniformity, preciseness and intelligence in decisions at electronic pace. The program objectives include but are not limited to:

  • To equip students to transform data into actionable insights to make complex business decisions.
  • To enable students, understand and analyze a problem and arrive at computable solutions.
  • To enable students to incorporate rational intelligence in automated decisions
  • To expose students to the set of technologies of artificial intelligence that will lead the market in the coming decades.
  • To gain hands-on experience on AI tools, data-centric tools, robotic tools, Vision tools, visualization and big data applications at the same rigorous scale as in a practical data science project.
  • To enable students to develop, understand and analyze algorithms in the field of AI.

To enable students to understand and develop processes for natural language.

Course details:

Core Subjects:

  • Advanced Analysis of Algorithms – 3 Credits
  • Advanced Artificial Intelligence – 3 Credits
  • Machine Learning – 3 Credits
  • Research Methods – 1 Credit

Elective Courses:

Course Title

Credit Hours

Advanced Data Mining

3

Robotics

3

Advanced Computer Vision

3

Bayesian Data Analysis

3

Big Data Analytics

3

Advanced Natural Language Processing

3

Deep Learning

3

Inference & Representation

3

Knowledge Representation

3

Knowledge Engineering

3

Distributed Machine Learning

3

Social Network Analysis

3

Time Series analysis and Prediction

3

Spatial Data Analysis

3

Intelligent Systems

3

Optimization Techniques

3

Operations Research

3

Research Methods in AI

1

Knowledge-Based Systems

3

Expert Systems and Applications

3

Brain-Informatics

3

Intelligent Decision Support Systems

3

Artificial Intelligence in Industry

3

Deep Reinforcement Learning

3

Genetic Algorithms

3

Data Visualization

3

Data Security

3

 

Semester wise model:

Semester 1

Course Title

Credit Hours

Advanced Artificial Intelligence

3

Machine Learning

3

Advanced Analysis of Algorithms

3

Research Methods

1

Total

10

Semester 2

Course Title

Credit Hours

Elective I

3

Elective II

3

Elective III

3

Total

9

Semester 3

Course Title

Credit Hours

Elective IV

3

Thesis-I

3

Total

6

Semester 4

Course Title

Credit Hours

Elective

3

Thesis-II

3

Total

6

TOTAL CREDIT HOURS

31