UNLOCK the Potential of Technology with Our
Bachelor of Computer
Applications

Relational Database Management System

This course covers relational database management, including data models like Hierarchical, Network, Relational, and Object-oriented, as well as the Entity- Relationship Model and Relational Algebra Operations. It also covers normalization, data-driven applications, SQL for data retrieval and modification, transaction management, database recovery techniques, and current database trends like parallel databases, spatial databases, distributed databases, and DWDM.

Data Structures and Algorithms

This course covers essential topics in data structures and algorithms. It focuses on sorting, searching, linked lists, tree structures, graph theory, symbol tables, and dynamic trees. It provides a complete understanding of fundamental data structures and algorithms, laying a strong foundation in computer science.

Entrepreneurship, Innovation, and Sustainability

This course teaches students how to navigate the intersection of entrepreneurship, innovation, and sustainability. It covers fundamental concepts, skills, and strategies needed to start and manage a sustainable business in a challenging and evolving contemporary world. The course emphasizes integrating innovative thinking with sustainable practices, equipping students with the tools to address societal and environmental challenges through entrepreneurial endeavours.

Business Statistics and Business Mathematics

The course introduces students to mathematical and statistical methods and techniques essential for making informed business decisions. This course emphasizes the practical application of mathematical and statistical tools to analyze and interpret data, enabling students to draw meaningful conclusions and support evidence-based decision-making within organizational contexts.

Islamic Studies

The course provides a basic introduction to the history and beliefs of Islam, one of the world's most influential religions. It focuses on the origins and spread as well as its contributions to the contemporary world. The course studies Islam and practices to promote an understanding of its rich heritage and diversity.

Operating Systems

This course provides a comprehensive understanding of operating systems, covering the fundamental concepts of process management, memory allocation, file systems, and security. Students will gain practical skills in system administration and learn how to optimize the performance of computer systems.

Structured Query Language

Focused on database management, this course introduces students to SQL, the standard language for relational database queries. Students will learn how to create, retrieve, and manipulate data in relational databases, gaining essential skills for data management in various applications.

Network Essentials

This course covers the fundamental principles of networking and explores topics such as network protocols, data transmission, and network security. Students will gain a foundational understanding of how computer networks operate and the essential components involved in data communication.

Introduction to Cloud Computing

This course comprehensively explores Cloud Computing and Virtualization, covering essential concepts, architectures, and practical implementations. Students will gain an understanding of Cloud Computing layers, Virtualization techniques, Cloud Architecture models, and security considerations. The course incorporates hands-on projects and real-world applications to reinforce theoretical knowledge.

Business and Managerial Communication

This course explores key concepts crucial for effective professional interaction. Through a focus on critical thinking development, students will acquire the skills necessary to navigate the dynamics of business communication, fostering excellence in written and verbal communication for both internal and external organizational contexts. The curriculum thoroughly examines theories and practical strategies, empowering students at various levels—managerial, organizational, corporate, individual, and group—to contribute meaningfully to societal engagement and become adept and socially conscious members of the community.

Cross-Cultural Management

The Cross-Cultural Management course develops knowledge and skills to navigate diverse cultural contexts in global business. It prepares students for leadership roles in international business by emphasizing cultural intelligence and cross-cultural communication. It also helps the students understand the role of culture in society, including its relationship to business practices and also gives an international perspective on managing business. It provides insight into the relationship between national values and workplace attitudes and behaviors in different countries.

Web Performance Analysis

The course focuses on the relevance and purpose of web performance analysis and explains the components of web analytics, including key performance indicators of web performance. It demonstrates the use of tools to measure web performance, explain how to track events on the website, and generate a report on the analysis of visitors to a website.

Internet of Things

Through this course, students will learn to design, implement, and manage IoT solutions, addressing the integration of sensors, data communication, and applications for a more intelligent and more connected world. The course also explores the interconnected world of devices and systems in the Internet of Things (IoT).

Text Mining

The course helps students understand basic concepts relating to and methods of extracting information and mining text data. It teaches processing techniques to prepare text data for statistical modeling and apply Machine Learning algorithms to the text data for text analysis and inference.

Foundations of Data Warehousing and Data Mining

The course delves into the world of Data Warehousing and Data Mining. This is an intensive course designed to provide a solid foundation in fundamental concepts and practical applications. Students will explore the fundamentals of Data Warehousing, including architecture, modeling, and indexing. Additionally, the course covers the distinctions between OLTP and OLAP technologies, delves into Data Mining techniques, and concludes with the application of these technologies in real-world scenarios. Through case studies and hands-on exploration, participants will gain the skills necessary to harness the power of data for informed decision-making.

Introduction to Artificial Intelligence

Students will explore the foundations of AI and its potential applications across various domains. the course delves into the basics of artificial intelligence, covering key concepts such as machine learning, natural language processing, and problem-solving.

Cloud Applications for Business Processes

Through this course, students will explore how cloud-based solutions enhance efficiency and flexibility in various business processes. They also understand the processes of integration of cloud applications into business workflows.

Data Science I

In this course, students will work with data to derive meaningful insights, laying the groundwork for advanced analytics. They begin the journey into data science, covering data exploration, cleaning, and fundamental statistical analysis.

Service Learning

Through Service learning, students have an opportunity to engage with the community and participate in activities that fulfill the needs of society. Students are expected to work in the field, spending a specified number of hours in a non-governmental organisation or a service sector area.

Machine Learning

This course deals with machine learning techniques, exploring algorithms for classification, regression, and clustering. Students will apply machine learning to real- world datasets, honing their skills in building predictive models.

Cloud Architectures and Security

Through this course, students will gain knowledge in designing secure and scalable cloud architectures. This course covers cloud security best practices and principles, preparing students to address the challenges of cloud-based infrastructure.

Essentials of Business Intelligence

The course emphasizes using data to inform business decision-making and strategy. It explores the fundamentals of business intelligence, covering data warehousing, reporting, and analytics.

Natural Language and Responsive AI

This course explores natural language processing and responsive artificial intelligence. Students will understand how AI systems can interpret and respond to human language, opening avenues for intelligent and interactive applications.

Cloud Administration and Management

This course addresses the practical aspects of maintaining and securing cloud-based infrastructures. Students will develop expertise in cloud administration, covering the management and optimization of cloud resources.

Data Preparation and Data Management

Equip yourself with essential skills in data preparation and management with this course. Covering the entire data lifecycle, participants will learn techniques for cleaning, transforming, and organizing data for effective analysis. The course also addresses data governance, security, and compliance, ensuring a holistic understanding of data management practices.

Predictive Analytics

In this course, students will explore algorithms and techniques for forecasting future trends and outcomes using historical data. They delve into advanced analytics with a focus on predictive modeling.

Fog Computing and Edge Computing

This course explores fog computing and edge computing paradigms, understanding how these distributed computing models complement cloud-based architectures. Students will learn to design and implement solutions at the network edge.

Big Data Storage and Analytics

Explore the storage and analytics aspects of big data in this comprehensive course. Participants will understand various storage solutions for handling massive datasets alongside analytics tools and techniques to process, analyze, and derive meaningful insights from diverse data sources.

Research Methodology

The Research Methodology course provides students with the foundational knowledge and skills to conduct rigorous and systematic research across various disciplines. Research is an integral part of academic and professional pursuits, and this course provides an in-depth understanding of the principles, methods, and ethical considerations involved in designing, executing, and presenting research projects. Participants will develop the capabilities to evaluate research literature critically, formulate research questions, develop hypotheses and employ appropriate methodologies to contribute meaningfully to their fields of study.

Neural Network

The course introduces students to basic Neural Networks (NN) concepts and helps them apply various NN learning processes and rules. Students will be able to design and implement Neural Networks (NN) applications in different sectors such as manufacturing, finance, medical, etc., sketch and use various perceptron models & networks.

Virtualization and Security

Through this course, students will be able to understand the concepts of information security and their application in a virtualized environment. Students will be able to understand the virtualization technology and its architecture and identify various types of vulnerabilities in a virtualized system and multiple technologies used for the security of virtualized servers and storage. Students will also be able to understand and use the concepts of automated cloud security, identity & access management, and assess the legal and policy requirements for standards of virtualization security like PCI-DSS, etc.

Advanced Big Data Analytics

The course will cover advanced analytics approaches, such as machine learning algorithms, and provide participants with practical experience using these methods to address challenging data problems. Discover the nuances of advanced big data analytics with this course, which focuses on innovative methods and resources for obtaining insightful information from large datasets.

Multimodal Machine Learning

This course will help the student understand the concept of Multimodal Machine Learning and learn about the different modalities used in Multimodal Machine Learning. It will help them evaluate and implement Multimodal Machine Learning models and explore the challenges and limitations of Multimodal Machine Learning.

Grid Computing and Utility Computing

This course explores grid and utility computing, covering distributed computing models and resource-sharing strategies to optimize computing efficiency and scalability.

Open Source Tools for Data Science

This course covers popular tools and platforms, empowering students to work with diverse data science ecosystems. Gain proficiency in using open-source tools for data science.

Internship

An internship is an opportunity for students to gain practical experience in their discipline. Students have an opportunity to apply theoretical knowledge to real-world situations, gain valuable industry experience, and refine essential skills that can enhance their employability and professional growth.

Supervised Machine Learning and Advances

In this course, students will explore advanced concepts in supervised machine learning, including ensemble methods, deep learning, and model optimization. Students will also deepen their understanding of complex machine-learning algorithms.

Cloud-based Solution Architecture

This course gives participants the tools to design successful cloud-based solutions by covering architecture patterns, cloud service selection, and best practices for developing reliable and affordable apps. They will also explore the principles of developing robust and scalable cloud-based systems.

Data Visualization

The Data Visualization course is designed to equip students with the knowledge and skills to transform complex data into meaningful visual representations. In today's data- driven world, effective data visualization is crucial for conveying insights, facilitating decision-making, and communicating information to diverse audiences. This course explores the principles, techniques, and tools used in creating compelling visualizations, focusing on the art and science of presenting data in clear, thoughtful, and aesthetically pleasing ways.

Deep Learning

Through this course, students will be able to identify and define key concepts in Deep Learning, including Neural Networks (NN) and Artificial Neural Networks (ANN). Students will be able to apply their knowledge to analyze and identify similarities and differences between biological neurons and perceptrons, design and implement DNN architectures for various machine learning tasks, and analyze and evaluate the impact of optimization choices on Deep Learning model convergence and generalization.

Statistical Machine Learning

Students will apply statistical concepts to machine learning problems, honing skills essential for data-driven decision-making. Students will gain a deep understanding of statistical machine-learning techniques and explore algorithms and methodologies for pattern recognition and predictive modeling.

Cloud Data Centre Management

This course covers the principles of cloud computing, virtualization, and data center architecture, preparing students to manage resources and services effectively in a cloud-based infrastructure. Learn the essentials of managing data centers in a cloud environment.

AI Applications in Social Media

The course helps students understand social media's role and relevance in society and build real-life applications that serve contemporary needs. It also provides knowledge of tools to investigate and analyze social media data, and visualize and predict social media behavior.

Cloud and AI

The integration of artificial intelligence (AI) with cloud computing systems is examined in this course, which covers essential ideas, industry best practices, and practical applications. By leveraging cloud infrastructure, participants will learn how to scale, deploy, and use resources more effectively.

Python for Data Science

This course covers data manipulation, analysis, and visualization using Python, a versatile programming language in the data science ecosystem. Students will gain proficiency in using Python for data science applications.

Project

The Project is an opportunity for students to engage in independent research work under the broad supervision of an advisor. Students can engage in academic research or an industry-rated project. Students have to collate data and use research methods, and discipline-related skills to analyse and present a report.