Course Outcomes

SE:Sem I

SE:Sem-II

TE:Sem-I

TE:Sem-II

BE:Sem-I

BE:Sem-II

SE:Sem I

Course Code

Course Name

Course Outcomes (COs)

218541

Discrete Mathematics

CO1: Formulate and apply formal proof techniques and solve the problems with logical reasoning.

CO2: Analyze and evaluate the combinatorial problems by using probability theory.

CO3: Apply the concepts of graph theory to devise mathematical models.

CO4: Analyze types of relations and functions to provide solutions to computational problems.

CO5: Identify techniques of number theory and its application.

CO6: Identify fundamental algebraic structures.

218542

Data Structure & Algorithms

CO1: Perform basic analysis of algorithms with respect to time and space complexity.

CO2: Select appropriate searching and/or sorting techniques in the application development.

CO3: Implement abstract data type (ADT) and data structures for given application.

CO4: Design algorithms based on techniques like brute-force, divide and conquer, greedy, etc.

CO5: Apply learned algorithm design techniques and data structures to solve problems.

CO6: Design different hashing functions and use file organizations.

218543

Computer Networks

CO1: Understand data/signal transmission over communication media.

CO2: Understand basics of computer networking and compare functions of OSI and TCP/IP model using concepts of communication theory.

CO3: Analyze data link layer services, different access techniques, and Ethernet standards.

CO4: Understand the network layer services, apply skills of subnetting, supernetting, and routing mechanisms.

CO5: Illustrate services and protocols used at transport layer.

CO6: Understand and learn the different application layer protocols.

218544

Object Oriented Programming

CO1: Differentiate various programming paradigms.

CO2: Identify classes, objects, methods, and handle object creation, initialization, and destruction to model real-world problems.

CO3: Identify relationship among objects using inheritance and polymorphism principles.

CO4: Handle different types of exceptions and perform generic programming.

CO5: Use files for persistent data storage for real-world applications.

CO6: Apply appropriate design patterns to provide object-oriented solutions.

218545

Software Engineering

CO1: Classify various software application domains.

CO2: Analyze software requirements by using various modeling techniques.

CO3: Translate the requirement models into design models.

CO4: Apply planning and estimation to any project.

CO5: Use quality attributes and testing principles in the software development life cycle.

CO6: Discuss recent trends in Software Engineering by using CASE and agile tools.

218546

Data Structure & Algorithms Laboratory

CO1: Analyze algorithms and determine algorithm correctness and time efficiency class.

CO2: Implement abstract data type (ADT) and data structures for given application.

CO3: Design algorithms based on techniques like brute-force, divide and conquer, greedy, etc.

CO4: Solve problems using algorithmic design techniques and data structures.

CO5: Analyze algorithms with respect to time and space complexity.

218547

Object Oriented Programming Laboratory

CO1: Differentiate various programming paradigms.

CO2: Identify classes, objects, methods, and handle object creation, initialization, and destruction to model real-world problems.

CO3: Identify relationship among objects using inheritance and polymorphism.

CO4: Handle different types of exceptions and perform generic programming.

CO5: Use file handling for real-world applications.

CO6: Apply appropriate design patterns to provide object-oriented solutions.

218548

Computer Networks Laboratory

CO1: Implement small size network and use various networking commands.

CO2: Understand and apply networking and simulation tools like Packet Tracer.

CO3: Configure various routing and switching protocols using Packet Tracer.

CO4: Configure various client/server environments to use application layer protocols.

CO5: Explore the use of protocols in various wired applications.

218549

Humanities and Social Sciences

CO1: Aware of the various issues concerning humans and society.

CO2: Aware about their responsibilities towards society.

CO3: Sensitized about broader issues regarding the social, cultural, economic, and human aspects involved in social changes.

CO4: Understand the nature of the individual and the relationship between self and the community.

CO5: Understand major ideas, values, beliefs, and experiences that have shaped human history and cultures.

218550

Soft Skill Laboratory

CO1: Introspect about individual’s goals, aspirations by evaluating one’s SWOC and think creatively.

CO2: Develop effective communication skills including Listening, Reading, Writing, and Speaking.

CO3: Constructively participate in group discussions, meetings and prepare and deliver presentations.

CO4: Write precise briefs or reports and technical documents.

CO5: Practice professional etiquette, present oneself confidently, and successfully handle personal interviews.

CO6: Function effectively in multi-disciplinary and heterogeneous teams through the knowledge of teamwork, interpersonal relationships, conflict management, and leadership qualities.

218551 (A)

Mandatory Audit Course 3: Ethics and Values in Information Technology

CO1: Adapt the global ethical principles and modern ethical issues.

CO2: Apprehend ethics in the business relationships and practices of IT.

CO3: Implement trustworthy computing to manage risk and security vulnerabilities.

CO4: Analyze concerns of privacy, privacy rights in information-gathering practices in IT.

218551 (B)

Mandatory Audit Course 3: Quantitative Aptitude & Logical Reasoning

CO1: Apply basic concepts of quantitative abilities.

CO2: Use logical reasoning for solving real-world problems.

CO3: Compete in examinations like internships, industry placements, postgraduate admissions, civil services, etc.

218551 (C)

Mandatory Audit Course 3: Language Study Japanese – Module I

CO1: Converse with simple sentences in Japanese.

CO2: Recognize and read simple sentences in Japanese.

CO3: Write simple sentences in Japanese.

CO4: Be aware of Japanese society and people.

218551 (D)

Mandatory Audit Course 3: Cyber Security and Law

CO1: Understand the basic concepts of cyber security and its abilities.

CO2: Analyze and evaluate the cyber security needs of an organization.

CO3: Understand the importance of cyber laws and their practices.

CO4: Determine and analyze software vulnerabilities and security solutions to reduce the risk of exploitation.

SE:Sem-II

Course Code

Course Name

Course Outcomes (COs)

207003

Applied Mathematics

CO1: Solve Linear differential equations, essential in modeling and design of computer-based systems.

CO2: Apply concept of Fourier transform and Z-transform and its applications to continuous and discrete systems and image processing.

CO3: Apply statistical methods like correlation & regression analysis and probability theory for data analysis and predictions in machine learning.

CO4: Solve algebraic & transcendental equations and system of linear equations using numerical techniques.

CO5: Obtain interpolating polynomials, numerical differentiation and integration, numerical solutions of ordinary differential equations used in modern scientific computing.

218552

Operating Systems

CO1: Describe the role of modern operating systems and make use of shell commands to build shell scripts.

CO2: Describe the concept of thread and process management, compare different process scheduling algorithms, and justify what algorithm to use in a given scenario.

CO3: Explain synchronization and deadlock; analyze classical IPC problems, also infer the existence of deadlock in the system.

CO4: Apply the concepts of various memory management techniques.

CO5: Make use of concept of I/O management and file system.

CO6: Understand the concepts of different system software.

218553

Fundamentals of Artificial Intelligence and Machine Learning

CO1: Evaluate Artificial Intelligence (AI) methods and describe their foundations.

CO2: Analyze and illustrate how search algorithms play a vital role in problem solving, inference, perception, knowledge representation, and learning.

CO3: Demonstrate knowledge of reasoning and knowledge representation for solving real-world problems.

CO4: Recognize the characteristics of machine learning that make it useful to real-world problems.

CO5: Apply the different supervised learning methods of support vector machine and tree-based models.

CO6: Use different linear methods for regression and classification with their optimization through different regularization techniques.

218554

Database Management System

CO1: Apply fundamental elements of database management systems.

CO2: Design ER-models to represent simple database application scenarios.

CO3: Formulate SQL queries on data for relational databases.

CO4: Improve the database design by normalization & to incorporate query processing.

CO5: Apply ACID properties for transaction management and concurrency control.

CO6: Analyze various database architectures and technologies.

218555

Computer Graphics

CO1: Apply mathematical and logical aspects for developing elementary graphics operations like scan conversion of points, lines, circles, and apply it for problem solving.

CO2: Employ techniques of geometrical transforms to produce, position and manipulate objects in 2D and 3D space respectively.

CO3: Describe mapping from world coordinates to device coordinates, clipping, and projections in order to produce 3D images on 2D output devices.

CO4: Apply concepts of rendering, shading, animation, curves, and fractals using computer graphics tools in design, development, and testing of 2D, 3D modeling applications.

CO5: Perceive the concepts of virtual reality.

218556

Operating System Laboratory

CO1: Apply the basics of Linux commands.

CO2: Build shell scripts for various applications.

CO3: Implement basic building blocks like processes and threads under Linux.

CO4: Develop various system programs for OS concepts in user space like concurrency control, CPU scheduling, memory management, and disk scheduling in Linux.

CO5: Develop system programs for inter-process communication in Linux.

218557

Computer Graphics Laboratory

CO1: Apply line and circle drawing algorithms to draw objects.

CO2: Apply polygon filling methods for objects.

CO3: Apply polygon clipping algorithms for objects.

CO4: Apply 2D transformations on objects.

CO5: Implement curve generation algorithms.

CO6: Demonstrate the animation of objects using animation principles.

218558

Database Management System Laboratory

CO1: Install and configure database systems.

CO2: Analyze database models and entity relationship models.

CO3: Design and implement a database schema for a given problem domain.

CO4: Implement relational database systems.

CO5: Populate and query a database using SQL DDL, DML, and DCL commands.

CO6: Design a backend database of an organization as a case study.

218559

Project Based Learning – II

CO1: Design solutions to real-life problems and analyze their concerns through shared cognition.

CO2: Apply a “learning by doing” approach to promote lifelong learning.

CO3: Tackle technical challenges for solving real-world problems with team efforts.

CO4: Collaborate and engage in multi-disciplinary learning environments.

218560

Code of Conduct

CO1: Understand the basic perception of profession, professional ethics, moral and social issues, industrial standards, and the role of ethics in engineering.

CO2: Aware of the professional rights and responsibilities of an engineer, including safety and risk benefit analysis.

CO3: Understand the societal and environmental impacts of professional engineering solutions and the need for sustainable development.

CO4: Apply ethical principles to resolve situations in professional lives.

218561 (A)

Mandatory Audit Course 4: Water Supply and Management

CO1: Relate the relationship between the environment and ecology, estimating water requirements for public water supply schemes.

CO2: Assess the quality of water as per BIS and select appropriate treatment methods.

CO3: Analyze the suitable distribution system for a locality and identify appurtenances used.

CO4: Summarize the arrangement of water supply and fittings in buildings.

CO5: Determine the need for water conservation and rural water supply systems.

CO6: Identify sources of water pollution and suitable control measures.

218561 (B)

Mandatory Audit Course 4: Language Study Japanese – Module II

CO1: Have Japanese communicative competence for primitive social conversations in Japanese.

CO2: Comprehend Japanese grammar and script.

CO3: Translate simple sentences between Japanese and English.

CO4: Be aware of Japanese society and culture.

218561 (C)

Mandatory Audit Course 4: e-Waste Management and Pollution Control

CO1: Discuss various types of e-waste sources.

CO2: Understand the impact of various e-wastes.

CO3: Identify characteristics of various e-waste pollutants.

CO4: Understand the processes of e-waste recycling and relevant technologies.

CO5: Discuss causes, effects, and control measures of environmental pollution.

CO6: Demonstrate safe disposal methods for e-waste and pollution control.

218561 (D)

Mandatory Audit Course 4: Intellectual Property Rights

CO1: Exhibit the concepts of intellectual property rights (IPR).

CO2: Differentiate among various forms of IPR.

CO3: Formulate and characterize innovative ideas and inventions into IPR.

CO4: Demonstrate knowledge of patent law and IP regulations.

TE:Sem-I

Course Code

Course Name

Course Outcomes

318541

Design and Analysis of Algorithm

CO1: Calculate computational complexity using asymptotic notations for various algorithms.

CO2: Demonstrate a familiarity with divide-conquer and greedy algorithms.

CO3: Describe and analyze the dynamic-programming paradigm for optimal solution.

CO4: Solve problems using backtracking approach.

CO5: Compare different methods of Branch and Bound strategy.

CO6: Classify P, NP, and NP Complete, NP hard problem.

318542

IoT with Artificial Intelligence

CO1: Understand internet of Things and its hardware and software components.

CO2: Describe intelligent IOT systems.

CO3: Analyze Protocol standardization for IOT.

CO4: Perform an analysis of IOT security issues using AI technology.

CO5: Identify the role of cloud computing in IOT.

CO6: Develop IoT infrastructure for popular applications.

318543

Web Technology

CO1: Analyze behavior of web pages using web technologies.

CO2: Develop Static and Dynamic website using technologies like HTML, CSS, Bootstrap.

CO3: Demonstrate the use of web scripting languages.

CO4: Develop web application with Front End & Back End Technologies.

CO5: Develop mobile website using JQuery Mobile.

CO6: Deploy web application on cloud using AWS.

318544

Management and Entrepreneurship for IT Industry

CO1: Define management, organization, entrepreneur, planning, staffing, ERP and outline their importance in entrepreneurship.

CO2: Utilize the resources available effectively through ERP.

CO3: Make use of IPRs and institutional support in entrepreneurship.

CO4: Understand the role of entrepreneurs in economic development, and barriers, Identification of business opportunities, feasibility studies.

CO5: Understand the contents of project report, ERP and project.

CO6: Understand IPRs and institutional support in entrepreneurship, Case Study of Entrepreneurs.

CO7: Learners will explore entrepreneurial skills and management function of a company with special reference to SME sector.

318545

Elective-I-(A): Robotics

CO1: Understand basic concepts of robotics.

CO2: Select appropriate Components and can able to do basic modeling & drive for Robotic applications.

CO3: Understand Kinematics and transformations.

CO4: Compare and select robot and end effectors, Sensors, grippers as per application.

CO5: Know about the fundamentals of robot programming and applications.

CO6: Study coverage of application and issues in Future in Robotics.

318545

Elective-I-(B): Pattern Recognition

CO1: Understand Bayesian Decision Theory, the canonical classifier model, and how different classification methods define decision boundaries.

CO2: Estimate unknown Probability Density functions.

CO3: Apply performance evaluation methods for pattern recognition and understand about the clustering concepts.

CO4: Select appropriate techniques for addressing recognition problems.

CO5: Implement basic pattern recognition algorithms.

CO6: Summarize current pattern recognition research verbally and in writing and analyze the estimation methods.

318545

Elective-I-(C): Information Security

CO1: Model the cyber security threats and apply formal procedures to defend the attacks.

CO2: Apply appropriate cryptographic techniques by learning symmetric key cryptography.

CO3: Apply appropriate cryptographic techniques by learning asymmetric key cryptography.

CO4: Design and analyze web security solutions by deploying various cryptographic techniques along with data integrity algorithms.

CO5: Identify and Evaluate Information Security threats and vulnerabilities in Information systems and apply security measures to real time scenarios.

CO6: Demonstrate the use of standards and cyber laws to enhance Information Security in the development process and infrastructure protection.

318545

Elective I (D): Business Intelligence

CO1: Apply conceptual knowledge on how Business Intelligence is used in decision making process.

CO2: Use modelling concepts in Business Intelligence.

CO3: Understand and apply the concepts of business reports and analytics with the help of visualization for business performance management.

CO4: Comprehend the model based decision making using prescriptive analytics.

CO5: Analyze the role of analytics and intelligence in Business.

CO6: Comprehend different Business Intelligence trends and its future impacts.

318546

Software Laboratory I (IoT with Artificial Intelligence)

CO1: Understand IOT Application Development using Raspberry Pi/ Beagle board/ Arduino board.

CO2: Develop and modify the code for various sensor based applications using wireless sensor modules and working with a variety of modules like environmental modules.

CO3: Make use of Cloud platform to upload and analyze any sensor data.

318547

WT Laboratory

CO1: Develop Static and Dynamic responsive website using technologies HTML, CSS, Bootstrap and AJAX.

CO2: Create Version Control Environment.

CO3: Develop an application using front end and backend technologies.

CO4: Develop mobile website using JQuery Mobile.

CO5: Deploy web application on cloud using AWS.

TE:Sem-II

Course Code	Course Title	Course Outcomes (COs)
318552	Machine Intelligence for Data Science	CO1: Apply data preprocessing methods on open access data and generate quality data for analysis. CO2: Apply appropriate statistical measure for machine learning applications. CO3: Apply regression techniques to machine learning problems. CO4: Apply and build classification models using SVM. CO5: Apply decision tree and ensemble methods to solve real-time applications. CO6: Apply and build clustering models using clustering methods and corresponding algorithms.
318553	Data Mining & Warehousing	CO1: Ability to understand various kinds of tools. CO2: Apply frequent pattern and association rule mining techniques for data analysis. CO3: Apply appropriate classification and clustering techniques for data analysis. CO4: Study Warehouse with design and Components. CO5: Apply suitable pre-processing and visualization techniques for data analysis. CO6: Design a Data warehouse system and perform business analysis with OLAP tools.
318554	Artificial Neural Networks	CO1: Recognize Learning Tasks and Learning Problems. CO2: Differentiate between Learning in humans and Learning in Artificial Neural Networks. CO3: Understand Predictive learning with Feed Forward Neural Networks and their limitations. CO4: Analyze Neural network architectures for solving Optimization Problems. CO5: Investigate neural network architecture for descriptive tasks. CO6: Understand learning types in Deep Neural Networks and their Applications.
318555	Elective II (A): Industrial Internet of Things	CO1: Describe Industrial Internet of Things and Cyber Physical manufacturing. CO2: Demonstrate Cyber Physical and Cyber Manufacturing systems. CO3: Describe Architectural design patterns for Industrial IoT. CO4: Analyze AI and data analytics for Industrial IoT. CO5: Evaluate Workforce and Human-Machine Interaction in Industrial IoT applications. CO6: Implement real field problems using Industrial IoT knowledge.
318555	Elective II (B): Brain Computer Interface	CO1: Comprehend and appreciate the significance and role of BCI. CO2: Evaluate the concept of BCI. CO3: Assign functions appropriately to humans and machines. CO4: Select appropriate feature extraction methods. CO5: Use machine learning algorithms for translation. CO6: Learn various applications of BCI.
318555	Elective II (C): AI for Cyber Security	CO1: Understand the fundamentals of AI and Cyber Security. CO2: Analyze cybersecurity and malware threats using AI. CO3: Apply network anomaly detection techniques to machine learning problems. CO4: Apply algorithms to protect sensitive information. CO5: Understand and apply tools for various GANs attacks. CO6: Evaluate algorithms.
318555	Elective II (D): Video Analytics	CO1: Understand algorithms for video data analysis and address challenges. CO2: Design video analytics algorithms for security applications. CO3: Design video analytics algorithms for business intelligence. CO4: Create custom video analytics systems for target applications. CO5: Analyze images using various coding techniques.
318556	Software Laboratory II	CO1: Demonstrate proficiency with statistical analysis of data. CO2: Use statistical analyses with professional statistical software. CO3: Apply data science concepts and methods to solve problems.
318557	Software Lab III – DMW & Industrial Internet of Things	CO1: Ability to understand various kinds of tools. CO2: Demonstrate classification, clustering, and other techniques on large data sets. CO3: Add mining algorithms as components to existing tools. CO4: Learn physical and logical design and enabling technologies of IoT. CO5: Acquire knowledge about IoT platforms.
318557	Software Lab III – DMW & Brain Computer Interface	CO1: Demonstrate classification, clustering, and other techniques on large data sets. CO2: Add mining algorithms as components to existing tools. CO3: Study the utilization of drive systems related to EEG signals for neurorehabilitation. CO4: Understand the concept of BCI systems for various applications. CO5: Process multi-channel EEG data using suitable tools. CO6: Solve interoperability and standardization issues in BCI software platforms.
318558	Internship / Skill Development / Global Certification Program	CO1: Demonstrate professional competence through industry internship. CO2: Apply knowledge from internships to academic activities. CO3: Choose appropriate technology and tools to solve problems. CO4: Demonstrate responsibility and ethical practices in professional life. CO5: Develop relationships with industry professionals. CO6: Analyze various career opportunities and set career goals.
318557	Software Lab III – DMW & AI for Cyber Security	CO1: Ability to understand various kinds of tools. CO2: Demonstrate classification, clustering, and other techniques on large data sets. CO3: Add mining algorithms as components to existing tools. CO4: Demonstrate proficiency with statistical analysis of data. CO5: Use statistical analyses with professional statistical software. CO6: Apply data science concepts and methods to solve problems.
318557	Software Lab III – DMW & Video Analytics	CO1: Design solutions to real-life problems through shared cognition. CO2: Apply a learning-by-doing approach in video analytics. CO3: Tackle technical challenges for real-world problem-solving with team efforts. CO4: Collaborate and engage in multidisciplinary learning environments. CO5: Demonstrate classification, clustering, and other techniques on large data sets. CO6: Add mining algorithms as components to existing tools.
318559	Seminar & Technical Communication	CO1: Analyze a latest topic of professional interest. CO2: Enhance technical writing skills. CO3: Identify an engineering problem and propose a solution. CO4: Communicate effectively with technical presentation skills.
318560(A)	Mandatory Audit Course 4 – The Science of Happiness	CO1: Understand what happiness is and why it matters. CO2: Learn how to increase personal happiness. CO3: Understand the power of social connections and empathy. CO4: Learn mindfulness and its real-world applications.
318560(B)	Mandatory Audit Course 4 – Emotional Intelligence	CO1: Analyze the differences in EI theories. CO2: Identify components of emotional intelligence in behavior. CO3: Learn responsibility for social management. CO4: Communicate effectively about emotional intelligence.
318560(C)	Language Study – Module IV	CO1: Communicate better in Japanese language. CO2: Demonstrate knowledge of Japanese Language Scripts. CO3: Understand Japanese culture and lifestyle. CO4: Pursue advanced professional Japanese language courses.
318560(D)	Mandatory Audit Course 4 – MOOC: Learn New Skills	CO1: Support community interactions through forums. CO2: Promote learning additional skills anytime and anywhere. CO3: Enhance teaching and learning on campus and online.

BE:Sem-I

Course Code	Course Name	Course Outcomes
318541	Design and Analysis of Algorithm	CO1: Calculate computational complexity using asymptotic notations for various algorithms. CO2: Demonstrate a familiarity with divide-conquer and greedy algorithms. CO3: Describe and analyze the dynamic-programming paradigm for optimal solution. CO4: Solve problems using backtracking approach. CO5: Compare different methods of Branch and Bound strategy. CO6: Classify P, NP, and NP Complete, NP hard problem.
318542	IoT with Artificial Intelligence	CO1: Understand Internet of Things and its hardware and software components. CO2: Describe intelligent IoT systems. CO3: Analyze Protocol standardization for IoT. CO4: Perform an analysis of IoT security issues using AI technology. CO5: Identify the role of cloud computing in IoT. CO6: Develop IoT infrastructure for popular applications.
318543	Web Technology	CO1: Analyze behavior of web pages using web technologies. CO2: Develop static and dynamic websites using HTML, CSS, Bootstrap. CO3: Demonstrate the use of web scripting languages. CO4: Develop web application with front-end and back-end technologies. CO5: Develop mobile websites using JQuery Mobile. CO6: Deploy web applications on cloud using AWS.
318544	Management and Entrepreneurship for IT Industry	CO1: Define management, organization, entrepreneur, planning, staffing, ERP and outline their importance in entrepreneurship. CO2: Utilize the resources available effectively through ERP. CO3: Make use of IPRs and institutional support in entrepreneurship. CO4: Understand the role of entrepreneurs in economic development, barriers, identification of business opportunities, and feasibility studies. CO5: Understand the contents of project report, ERP, and project. CO6: Understand IPRs and institutional support in entrepreneurship, Case Study of Entrepreneurs. CO7: Explore entrepreneurial skills and management function of a company with special reference to SME sector.
318545	Elective-I-(A): Robotics	CO1: Understand basic concepts of robotics. CO2: Select appropriate components and perform basic modeling and drive for robotic applications. CO3: Understand Kinematics and transformations. CO4: Compare and select robot and end effectors, sensors, and grippers as per application. CO5: Learn fundamentals of robot programming and applications. CO6: Study applications and future issues in robotics.
318545	Elective-I-(B): Pattern Recognition	CO1: Understand Bayesian Decision Theory and classifier models. CO2: Estimate unknown Probability Density Functions. CO3: Apply performance evaluation methods and clustering concepts. CO4: Select appropriate techniques for recognition problems. CO5: Implement basic pattern recognition algorithms. CO6: Summarize current research and analyze estimation methods.
318545	Elective-I-(C): Information Security	CO1: Model cybersecurity threats and apply formal defense procedures. CO2: Apply symmetric key cryptographic techniques. CO3: Apply asymmetric key cryptographic techniques. CO4: Design and analyze web security solutions with cryptographic techniques. CO5: Identify and evaluate Information Security threats and apply security measures. CO6: Demonstrate the use of standards and cyber laws in security development.
318545	Elective-I-(D): Business Intelligence	CO1: Apply Business Intelligence in decision-making processes. CO2: Use modeling concepts in Business Intelligence. CO3: Apply business reports and analytics using visualization. CO4: Comprehend model-based decision-making using prescriptive analytics. CO5: Analyze the role of analytics and intelligence in business. CO6: Understand Business Intelligence trends and future impacts.
318546	Software Laboratory I (IoT with AI)	CO1: Develop IoT applications using Raspberry Pi/Beagle/Arduino boards. CO2: Code various sensor-based applications using wireless modules. CO3: Utilize cloud platforms to upload and analyze sensor data.
318547	WT Laboratory	CO1: Develop static and dynamic websites using HTML, CSS, Bootstrap, AJAX. CO2: Create a version control environment. CO3: Develop front-end and back-end applications. CO4: Build mobile websites using JQuery Mobile. CO5: Deploy web applications on AWS cloud.
318548	Elective-I-(A): Robotics Laboratory	CO1: Demonstrate different robots. CO2: Identify different robot paths. CO3: Perform basic programming in robotics.

BE:Sem-II

Course Code	Name of Subject/ Course	Course Outcome (COs)
418550	Natural Language Processing	CO1: Describe the fundamental concepts of NLP, challenges and issues in NLP. CO2: Analyze Natural languages morphologically, syntactically, and semantically. CO3: Illustrate various language modelling techniques. CO4: Integrate the NLP techniques for the information retrieval task. CO5: Demonstrate the use of NLP tools and techniques for text-based processing of natural languages. CO6: Develop real-world NLP applications.
418551A	Distributed Systems	CO1: Analyze and evaluate the design choices and trade-offs involved in building distributed systems. CO2: Design and implement efficient distributed systems using middleware. CO3: Design and implement effective inter-process communication strategies in distributed systems. CO4: Develop fault-tolerant distributed systems by implementing replication and fault tolerance strategies. CO5: Apply distributed file, multimedia, and web-based systems to real-world scenarios. CO6: Incorporate recent trends and technologies in the design and implementation of distributed systems.
418551B	Software Project Management	CO1: Apply the practices and methods for successful Software Project Management. CO2: Use various tools of Software Project Management. CO3: Create, Design and Evaluate Projects. CO4: Demonstrate different tools used for Project Tracking, Monitoring & Control. CO5: Analyse a case study for a distributed team and comment. CO6: Discuss and use modern tools for Software Project Management.
418551C	Computer Vision	CO1: Implement fundamental image processing techniques required for computer vision. CO2: Apply feature extraction techniques. CO3: Apply Hough Transform for line, circle, and ellipse detections. CO4: Implement three-dimensional analysis techniques. CO5: Implement Motion detection and object tracking techniques. CO6: Develop skills to implement diverse computer vision applications.
418552A	Reinforcement Learning	CO1: Describe theories and processes in a reinforcement learning problem. CO2: Understand and apply basic Reinforcement Learning algorithms for simple sequential decision-making problems in uncertain conditions. CO3: Evaluate the performance of the solution and find the optimal strategy. CO4: Understand how to fine-tune the target to have better learning performance. CO5: Learn approximation methods and algorithms for optimizing the problem. CO6: Understand how to decompose a reinforcement learning problem into a hierarchy of subproblems or subtasks.
418552B	Big Data Analytics	CO1: Identify Big Data and its Business Implications. CO2: List the components of Hadoop and Hadoop Eco-System. CO3: Manage Job Execution in Hadoop Environment. CO4: Develop Big Data Solutions using Hadoop Eco-System. CO5: Apply Machine Learning Techniques using R. CO6: Analyze Infosphere BigInsights Big Data Recommendations.
418552C	Artificial Intelligence using R programming	CO1: Understand the use of R programming language. CO2: Use programming structures like loops, functions, exceptions in R. CO3: Understand the basic terminologies of statistics used in AI. CO4: Understand the basic terminologies of probability used in AI. CO5: Understand the concept of regression. CO6: Implement Machine learning algorithms using R.

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