B.Tech in Computer Science Engineering (Artificial Intelligence and Machine Learning)

In the second semester, students advance their mathematical skills with Engineering Mathematics II and study Computer Organization and Architecture to understand the internal workings of computers. Data Structures and Algorithms cover essential methods for managing and manipulating data, while Object-Oriented Programming (OOP) introduces key programming principles. Discrete Mathematics and Database Management Systems (DBMS) provide further theoretical and practical insights, and Computer Graphics explores visual representation in computing.

The third semester focuses on core technical concepts, including Engineering Mathematics III and Operating Systems, which cover software that manages computer hardware. Students study Computer Networks to understand network communication fundamentals, and Software Engineering for methodologies in software project management. Web Technologies introduce web development techniques, while Elective I allows students to explore additional areas of interest related to AI and ML.

In the fourth semester, students delve into Design and Analysis of Algorithms, exploring efficient algorithm creation. Principles of Programming Languages introduce various programming paradigms, and Compiler Design covers the process of translating programming languages. Mobile Application Development focuses on mobile platforms, while Theory of Computation provides insights into computational theory. Elective II offers further specialization in AI and ML-related topics.

The fifth semester is dedicated to AI and ML fundamentals, with courses such as Machine Learning, which covers techniques for creating data-driven systems. Deep Learning explores neural networks and their applications, while Natural Language Processing (NLP) focuses on the interaction between computers and human language. Advanced Database Systems and Elective III offer further specialization, and students work on a mini project to apply their learning.

During the sixth semester, students study Cybersecurity to understand techniques for protecting systems and data. Cloud Computing covers cloud technologies and services, while Internet of Things (IoT) explores interconnected systems and devices. Big Data Analytics provides methods for handling large datasets, and Elective IV allows students to select advanced topics. Industrial Training offers practical experience in applying AI and ML in real-world settings.

In the seventh semester, students engage in Project Work I, applying their skills to comprehensive projects. Advanced AI Techniques cover cutting-edge methods in artificial intelligence, while Data Warehousing and Mining explores techniques for managing and analyzing data. Professional Ethics and Communication prepare students for the workforce, and Elective V provides additional specialization opportunities.

The final semester focuses on Project Work II, where students complete an extensive project. The Dissertation allows for in-depth research on a chosen AI or ML topic, while Advanced Topics in AI and ML covers the latest developments in the field. Students also participate in an Internship to gain practical industry experience, ensuring they are ready to excel in their careers.