CSE(AI&ML) LAB-1

Data Structures Lab:-

The objectives of the Data Structures Lab (DS Lab) are to introduce the fundamental concepts of data structures, including their design, implementation, and application. In the DS Lab, students gain hands-on experience with various data structures such as arrays, linked lists, stacks, queues, trees, graphs, and hash tables. This lab focuses on the practical implementation and manipulation of these structures, as well as the development of algorithms for data processing and management.

OOPS Through JAVA Lab:-

The objectives of the Object-Oriented Programming Systems (OOPS) Through Java Lab are to introduce the fundamental concepts of object-oriented programming using Java, and to provide practical experience in designing and implementing object-oriented applications. In the OOPS Through Java Lab, students will learn the principles of object-oriented design and programming, including classes, objects, inheritance, polymorphism, and interfaces. This lab focuses on building robust, reusable, and maintainable software using Java.

Data Visualization and R Programming Lab:-

The objectives of the Data Visualization and R Programming Lab are to introduce students to the fundamental concepts and techniques of data visualization and to develop proficiency in R programming for data analysis. This lab provides hands-on experience in creating various types of visualizations, performing data manipulation, and analyzing data using R, which is a powerful language and environment for statistical computing and graphics.

Software Testing Methodologies:-

The objectives of the Software Testing Methodologies Lab are to introduce students to the principles and practices of software testing, and to provide hands-on experience in various testing techniques and tools. This lab covers different types of testing, test case design, test automation, and the use of testing tools to ensure software quality and reliability.

Database Management Lab:-

The objectives of the Database Management Lab are to introduce students to the fundamental concepts of database systems, and to provide hands-on experience in designing, implementing, and managing databases. This lab covers various aspects of d atabase management including database design, SQL programming, transaction management, and database connectivity.

Machine Learning Lab

This lab provides hands-on experience with key Machine Learning (ML) concepts and algorithms. Students will implement supervised and unsupervised learning models, including linear regression, logistic regression, decision trees, SVMs, k-means clustering, and neural networks using Python and libraries such as NumPy, pandas, scikit-learn, and TensorFlow. The lab emphasizes data preprocessing, model training, evaluation, and performance tuning through real-world datasets and projects. Students Understand core ML algorithms and their applications, Gain practical experience in model development and evaluation, work with real-world datasets using Python-based ML tools.

Deep Learning Lab

The Deep Learning lab offers practical exposure to neural networks and advanced deep learning architectures. Students will build, train, and evaluate models using frameworks like TensorFlow and PyTorch. The lab covers key topics such as feedforward networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders, and transfer learning. Emphasis is placed on data preprocessing, model optimization, and real-world applications like image and text classification. Through guided experiments and mini-projects, students gain a solid understanding of deep learning workflows and tools, preparing them for research and industry roles in AI and data science.

Python Programming Lab

The Python Programming lab introduces students to the fundamentals of programming using Python. It covers basic syntax, data types, control structures, functions, modules, file handling, and exception handling. Students will also explore object-oriented programming, data structures like lists, tuples, and dictionaries, and basic libraries such as math and random. Emphasis is placed on writing clean, efficient code and solving real-world problems through hands-on exercises and mini-projects. By the end of the lab, students will be equipped with the skills needed to develop and debug Python programs confidently for academic and professional use.

Node Js:-

The objectives of the Node.js Lab are to provide students with practical experience in server-side development using Node.js. This lab focuses on building scalable, efficient, and real-time web applications and services using Node.js and its associated frameworks and libraries.

Network Programming Lab:-

The Network Programming Lab is designed to provide students with practical experience in developing and implementing networked applications. This lab focuses on understanding and applying network programming concepts, using various protocols, and developing applications that communicate over networks.

Operating Systems Lab:-

The Operating Systems Lab (OS Lab) aims to introduce students to fundamental concepts, design principles, and implementations of operating systems. In this lab, students explore various aspects of operating systems, including process management, memory management, file systems, virtualization, and distributed operating systems. Practical sessions involve working with Linux-based systems such as Fedora and Ubuntu.

Project Lab

The department's project laboratory provides students with a valuable opportunity to gain hands-on experience in a cutting-edge environment. Here, students become proficient in both the technical and creative skills essential for success in the field of Computer Science and Engineering. The Project Laboratory plays a crucial role in fostering practical learning, enabling students to develop innovative proposals and bring their final projects to life.