B.Sc Artificial Intelligence & Data Science Syllabus – Subjects, Semester Wise Curriculum & Topics

Introduction

The B.Sc. Artificial Intelligence & Data Science syllabus is set to offer the student a solid base in artificial intelligence technologies and programming, data analytics and computational approaches. It has a curriculum that is a blend of computer science basics and mathematics, statistics, machine learning, and current data technologies. In three or four years (according to NEP), learners are taught to interpret data, create smart systems, and develop solutions with the help of artificial intelligence.

The curriculum equips students for the workforce in technology, data analysis, software development, and artificial intelligence studies.

Table of Contents

• B.Sc. Artificial Intelligence and Data Science, 1st Year Syllabus.
• B.Sc. Artificial Intelligence and Data Science, 2nd Year Syllabus.
• B.Sc. Artificial Intelligence and Data Science Syllabus, Third Year.
• Fourth Year (Research Year – as per NEP)
• Learning Practical and Project Training.
• Elective Subjects
• Skills Gained In the Syllabus.
• Overview Summary Table
• FAQs
• Conclusion

B.Sc. Artificial Intelligence and Information Syllabus (first year).

The first year aims at establishing the background of programming, mathematics, and the basics of computer science.

Major subjects include:

• Programming with Python
• Bases of Computer Science.
• Mathematics for Computing
• Statistics and Probability
• The Artificial Intelligence Introduction.
• Data Structures
• Environmental Studies
• English / Communication Skills.

This year supports the students in the acquisition of the fundamental knowledge of programming and analytical thinking skills.

B.Sc. Artificial Intelligence and Data Science, 2nd Year Syllabus.

The second year presents students with the fundamental ideas in data science and machine learning.

Key subjects include the following:

• Algorithms and Data Structures.
• Database management Systems.
• Basic Concepts of Machine Learning.
• Data Analytics
• Linear Algebra for AI
• Probability and Statistical Modelling.systems.
• Big Data Fundamentals

This step assists students in realising how data are stored, processed and analysed through the contemporary technologies.

Third Year Undergraduate Artificial Intelligence and Data Science Syllabus.

Year three is dedicated to advanced artificial intelligence technologies and the real world.

Important subjects include:

• Deep Learning
• Natural Language Processing.
• Computer Vision
• Data Mining
• Artificial Intelligence Implementations.
• Cloud Computing
• Project Work / Capstone Project – I.

This year will make students ready to work in the machine learning, intelligent systems, and advanced data analytics fields.

Fourth Year (Research Year - According to NEP)

The fourth year is elective and research-based as per the National Education Policy (NEP).

Major components include:

• Advanced Machine Learning
• Design of Artificial Intelligence System.
• Applied Data Science
• Research Seminar
• Dissertation / Thesis – II

This year comes in particularly handy for students who are planning a career of higher education or research in the fields of artificial intelligence and data science.

Practical Learning & Project Training

The B.Sc. Artificial Intelligence and Data Science curriculum puts a high importance on practice and applications.

Students acquire practical experience as they are exposed to the following:

• Software development and programming.
• Analysis of data based on real-life data sets.
• Development of the machine learning model.
• Industry projects and case studies.
• Presentations and technical seminars.
• Capstone projects and research work.

Such practices can teach students how artificial intelligence technologies are used in the current industries.

Elective Subjects

Students get the chance to take up elective subjects according to their interests and career objectives.

Common electives include:

• Robotics Intelligent Systems.
• Advanced Data Analytics
• Internet of Things (IoT)
• Business Intelligence
• Cybersecurity Basics
• Blockchain Technology
• Cloud Computing

Elective courses enable students to major in areas of new technologies.

Skills Gained Due to the Syllabus.

The syllabus assists students to acquire critical technical and professional expertise needed in the contemporary technology professions.

Some of the important skills acquired are:

• The development of programs and software.
• Visualisation and analysis of data.
• The development of a machine learning model.
• Design of artificial intelligence systems.
• Statistical interpretation and analysis.
• Rationality and problem-solving.
• Analytical decision-making

The skills would be needed in the field of artificial intelligence, data science, and software development.

Overview Summary Table

Frequently Asked Questions — B.Sc. Artificial Intelligence and Data Science Syllabus.

Conclusion

The B.Sc. Artificial Intelligence and Data Science curriculum is well designed in order to integrate programming, mathematics, artificial intelligence, and data analysis. The programme teaches a combination of theoretical studies, hands-on training, and research-based learning, which makes graduates ready to work in high-tech areas of artificial intelligence, data science, software development, and analytics, among others, with high growth potential.