Course Information
Course Code
1BAIA103/203
Credits
04
Total Hours
40 hours
Examination
Theory (3 hours)
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Course Objectives
- Explore the need for parallel programming.
- Explain how to parallelize on MIMD systems .
- To demonstrate how to apply MPI library and parallelize the suitable programs.
- To demonstrate how to apply OpenMP pragma and directives to parallelize the suitable programs.
Course Modules
Introduction to AI and Applications Model Question Paper Solution Set-01
Model Question Paper-1 with effect from 2025
Introduction to AI and Applications Model Question Paper Solution Set-02
Model Question Paper-1 with effect from 2025
Module 1: Introduction to Artificial Intelligence
Topics: Artificial Intelligence, How Does AI Work?, Advantages and Disadvantages of Artificial Intelligence, History of Artificial Intelligence, Types of Artificial Intelligence, Weak AI,..
Module 2: Introduction to Prompt Engineering:
Topics: SIntroduction to Prompt Engineering, The Evolution of Prompt Engineering, Types of Prompts, How Does Prompt Engineering Work?,.
Module 3: Machine Learning
Topics: fTechniques in AI, Machine Learning Model, Regression Analysis in Machine Learning, Classification Techniques, Clustering Techniques..
Module 4: Trends in AI
Topics: AI and Ethical Concerns, AI as a Service (AIaaS), Recent trends in AI, Expert System, Internet of Things, Artificial Intelligence of Things (AIoT)..
Module 5: Robotics
Topics: Robotics, Robotics-an Application of AI, Drones Using AI, No Code AI, Low Code AI..