MCA degree program at RIT Roorkee aims at developing the required skills to help students be part of the industry that has been focusing on creating intelligent machines. The program has been crafted by experts. The classroom model of learning gives you an opportunity to interact with the faculty and other batch mates, and network with experts in different domains. The industry collaboration for this specialized degree program has enriched the course contents and strengthen academic delivery.
Companies which are hiring for AI and ML are Amazon NVIDIA, Microsoft, IBM, Accenture, Facebook, Intel, Samsung and many more. AI is everywhere. Its practical applications are found in workplaces, banks, cars, home, hospitals, even in the space. Hollywood animation, Google’s search engine, video, and computer games use AI techniques. AI helps financers predict the stock market movement and governments in policy decisions in health and transport.
Machine learning is a specialized field of AI that enables a system to learn from data rather than through explicit programming. Due to improvement in machine learning algorithms, availability of data and computation power, the use cases of AI have tremendously increased in recent past. Governments around the globe and corporations have been investing heavily in the AI. Due to this, the job opportunities in AI and data science have increased exponentially.
Course Objectives :
The primary objective of this course is to introduce the basic principles, techniques, and applications of Artificial Intelligence. Emphasis will be placed on the teaching of these fundamentals, not on providing a mastery of specific software tools or programming environments. Assigned projects promote a ‘hands-on’ approach for understanding, as well as a challenging avenue for exploration and creativity.
Learning outcomes:
Upon successful completion of this course, the student shall be able to:
- Demonstrate fundamental understanding of the history of artificial intelligence (AI) and its foundations.
- Apply basic principles of AI in solutions that require problem solving, inference, perception, knowledge representation, and learning.
- Demonstrate awareness and a fundamental understanding of various applications of AI techniques in intelligent agents, expert systems, artificial neural networks and other machine learning models.
- Demonstrate proficiency developing applications in an ‘AI language’, expert system shell, or data mining tool.
- Demonstrate proficiency in applying scientific method to models of machine learning.
- Demonstrate an ability to share in discussions of AI, its current scope and limitations, and societal implications.
