B.Tech (AI & DS)

A Bachelor of Technology (B.Tech) in Artificial Intelligence and Data Science (AI & DS) is a four-year undergraduate program designed to provide a solid foundation in AI and data analytics. Below is a concise overview of the core courses typically included in this program, along with their benefits.

Core Courses and Benefits

 Introduction to Programming

Description: Basics of programming languages and problem-solving techniques, often using Python.
Benefits: Develops fundamental coding skills and logical thinking essential for AI and data science.

 Data Structures and Algorithms

Description: Study of data organization, management, and algorithms for efficient data manipulation.
Benefits: Enhances problem-solving skills and the ability to handle large data sets efficiently.

 Database Management Systems (DBMS)

Description: Principles of database design, SQL, NoSQL databases, and data retrieval techniques.
Benefits: Equips students with the skills to manage and query large databases effectively.

 Probability and Statistics

Description: Fundamentals of probability theory, statistical methods, and data analysis.

Benefits: Provides the mathematical foundation necessary for data interpretation and machine learning algorithms.

 Machine Learning

Description: Concepts of supervised, unsupervised, and reinforcement learning, including algorithm implementation.
Benefits: Prepares students to develop and apply machine learning models to real-world problems.

 Artificial Intelligence

Description: Study of AI principles, including natural language processing, computer vision, and robotics.
Benefits: Provides a comprehensive understanding of AI techniques and applications.

 Big Data Analytics

Description: Techniques for processing and analyzing large-scale data using tools like Hadoop and Spark.
Benefits: Equips students with the skills to manage and derive insights from massive data sets.

 Data Visualization

Description: Methods and tools for visualizing data to communicate insights effectively.
Benefits: Enhances the ability to present data findings clearly and compellingly.

 Deep Learning

Description: Study of neural networks, convolutional networks, and advanced deep learning techniques.
Benefits: Prepares students for cutting-edge research and applications in AI.

 Data Mining

Description: Techniques for discovering patterns and knowledge from large data sets.
Benefits: Equips students with skills to extract valuable information from complex data.

 Natural Language Processing (NLP)

Description: Study of computational techniques for processing and understanding human language.
Benefits: Prepares students for applications in text analysis, translation, and conversational AI.

Course Benefits

• Strong Technical Foundation: Comprehensive understanding of computer science principles.
• Analytical Skills: Enhances ability to analyze and interpret complex data.
• Career Opportunities: Broad job prospects in software development, system architecture, cybersecurity, and more.
• Hands-On Experience: Practical experience through labs, projects, and internships.
• Innovation and Research: Encourages creativity and advanced study in AI and data science..
• Versatility: Diverse electives allow specialization in areas of interest.