Third Year of Artificial Intelligence and Machine Learning (2020 Course)
| SEMESTER-V | ||
|---|---|---|
| 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. |
| 318548 | Elective-I-(A): Robotics Laboratory | CO1: Student must able to do the demonstration of Different robots. CO2: Student must know the different paths for robots. CO3: Student can able to do basic Program in Robotics. |
| 318548 | Elective-I-(B): Pattern Recognition Laboratory | CO1: Understand how to generate pattern features using various transforms based on data. CO2: Understand how to analyze pattern features using probability theory. CO3: Understand how to build classifiers using known probability distribution. CO4: Understand how to build classifiers using non parametric methods. CO5: Understand how to build linear classifiers using perception model. CO6: Understand how to build linear, nonlinear classifiers using SVM model. CO7: Understand how to build classifiers using syntactic model. CO8: Understand theory of unsupervised learning |
| 318548 | Elective-I-(C ) : Information Security Laboratory | CO1: Use tools and techniques in the area of Information Security. CO2: Use the cryptographic techniques for problem solving. CO3: Design and develop security solution. CO4: Protect and defend information systems. |
| 318548 | Elective-I-(D): Business Intelligence Laboratory | CO1: Compare and analyze different analytical tools used by businesses. CO2: Understand the application of critical notion of KPI using real time case studies. CO3: Design and implement the analytical models using suitable tools. CO4: Create visualizations using suitable tools. |
| 318549 | Seminar / Mini Project | CO1: Analyze a latest topic of professional interest. CO2: Identify an engineering problem, analyze it and propose a work plan to solve it. CO3: Communicate with professional technical presentation skills. CO4: Design solution to real life problems and analyze its concerns through shared cognition. CO5: Tackle technical challenges for solving real world problems with team efforts. |
| 318550 | Environmental Studies | CO1: The understand nature of environment studies & Importance. CO2: Design the Structure and function of ecosystem. CO3: The use of Natural Resources in real time environment. CO4: Undesirable changes occurring in the physical, chemical, and biological composition of natural environment consisting of air, water, and soil. CO5: The commitment of an organization or government to the laws, regulations, and other policy mechanisms concerning environmental issues. CO6: Humans impact their environment through their habits, actions, and choices. |
| 318551 | Mandatory Audit Course 3: A: Road Safety | CO1: Analyse traffic characteristics of roadways. CO2: Understand the importance of planning for traffic safety and rehabilitation. CO3: Acquire information and knowledge about people responsible for accidents and their duties. CO4: Evaluate the causes of road accidents and take part in road safety audit. CO5: Acquire a certificate in compulsory events based on the topic under study. |
| 318551 | Mandatory Audit Course 3: B: Engineering Economics | CO1: Understand rational decision making and impact on economics. CO2: Perform calculations for interest rates and rates of return. CO3: Calculate the present, annual and future worth of cash flows. CO4: Understand Fundamental approach and terminology of replacement analysis. |
| 318551 | Mandatory Audit Course 3: C: Language Study-Module III | CO1: Ability of basic communication. CO2: Knowledge of Japanese script (reading, writing and listening skills). CO3: Knowledge about Japanese culture, life style, manners and etiquettes. CO4: Develop interest to pursue professional Japanese Language course. |
| 318551 | Mandatory Audit Course 3: D: MOOC- Learn New skills | CO1: Promote interactive user forums to support community interactions among students, professors, and experts. CO2: Promote learn additional skills anytime and anywhere. CO3: Enhance teaching and learning on campus and online. |
| SEMESTER – VI | ||
|---|---|---|
| Course Code | Course Name | Course Outcomes |
| 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 ensembles methods to solve real time applications. CO6: Apply and build clustering models using clustering methods and its corresponding algorithms. |
| 318553 | Data Mining & Warehousing | CO1: Ability to understand the 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: Apply frequent pattern and association rule mining techniques for data analysis & 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 humane and Learning in Artificial Neural Networks. CO3: Understand Predictive learning with Feed Forward Neural Networks and Limitations. CO4: Analyse Neural network architectures for solving Optimization Problems. CO5: Investigate neural network architecture for descriptive tasks. CO6: Understand learning type 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 Internet of Things. CO4: Analyse AI and data Analytics for Industrial Internet of Things. CO5: Evaluation of Workforce and Human Machine Interaction and Application of Industrial Internet of Things. CO6: Ability to implement real field problem by gained knowledge of Industrial applications with IoT capability. |
| 318555 | Elective II (B): Brain Computer Interface | CO1: Comprehend and appreciate the significance and role of this course in the present contemporary world. CO2: Evaluate concept of BCI. CO3: Assign functions appropriately to the human and to the machine. CO4: Select appropriate feature extraction methods CO5: Use machine learning algorithms for translation. CO6: Learn the various applications of BCI. |
| 318555 | Elective II (C): AI for Cyber Security | CO1: Understand the fundamental of AI and Cyber Security. CO2: Analyze the cyber security threats and malware threats with AI. CO3: Analyze and apply network anomaly detection techniques to machine learning problems. CO4: Apply various algorithms to protect the sensitive information. CO5: Understand and apply tools for the various GANs attacks. CO6: Understand to evaluate algorithms. |
| 318555 | Elective II (D): Video Analytics | CO1: Understand the algorithms available for performing analysis on video data and address the challenges. CO2: Design video analytic algorithms for security applications. CO3: Design video analytic algorithms for business intelligence. CO4: Design custom made video analytics system for the given target application. CO5: Analyse the 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 the various kinds of tools. CO2: Demonstrate the classification, clustering and etc. in large data sets. CO3: Ability to add mining algorithms as a component to the exiting tools. CO4: To learn physical design, logical design and enabling technologies of internet of things. CO5: To acquire knowledge about IoT platforms. |
| 318557 | Software Lab III- DMW & Brain Computer Interface | CO1: Demonstrate the classification, clustering and etc. in large data sets. CO2: Ability to add mining algorithms as a component to the exiting tools. CO3: Study the utilization of drives system related to the electroencephalogram (EEG) signals for neuro rehabilitation. CO4: Understand the concept of Brain Computer Interface Systems that can be designed and developed with the overall goal of supporting a wide range of users for a wide range of applications. CO5: Process multi-channel EEG data using a suitable tool in the computing environment which will be helpful for developing, prototyping and testing Brain Computer Interface approaches. CO6: Solve the interoperability and standardization issues of Brain Computer Interface software platforms and to identify and design new applications of Brain Computer Interface. |
| 318557 | Software Lab III- DMW & AI for Cyber Security | CO1: Ability to understand the various kinds of tools. CO2: Demonstrate the classification, clustering and etc. in large data sets. CO3: Ability to add mining algorithms as a component to the exiting 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 solution to real life problems and analyze its concerns through shared cognition. CO2: Apply learning by doing approach in Video Analytics 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. CO5: Demonstrate the classification, clustering and etc. in large data sets. CO6: Ability to add mining algorithms as a component to the exiting tools. |
| 318558 | Internship / Skill Development / Global Certification Program | CO1: To demonstrate professional competence through industry internship. CO2: To apply knowledge gained through internships to complete academic activities in a professional manner. CO3: To choose appropriate technology and tools to solve given problem. CO4: To demonstrate abilities of a responsible professional and use ethical practices in day to day life. CO5: Creating network and social circle, and developing relationships with industry people. CO6: To analyse various career opportunities and decide carrier goals. |
| 318559 | Seminar & Technical Communication | CO1: Analyze a latest topic of professional interest. CO2: Enhance technical writing skills. CO3: Identify an engineering problem, analyze it and propose a work plan to solve it. CO4: Communicate with professional technical presentation skills. |
| 318560(A) | Mandatory Audit Course 4 The Science of Happiness | CO1: Understand what happiness is and why it matters to you. CO2: Learn how to increase your own happiness. CO3: Understand of the power of social connections and the science of empathy. CO4: Understand what is mindfulness and its real world applications. |
| 318560(B) | Mandatory Audit Course 4: Emotional Intelligence | CO1: Analyze the differences in the EI theories that are regularly applied. CO2: Describe components of emotional intelligence and identify them within behaviour. CO3: Acquire information and knowledge about responsibility for social management. CO4: Communicate effectively (Verbal and Non Verbal) about emotional intelligence. |
| 318560(C) | Language study-Module IV | CO1: Do Better Communication in Japanese language. CO2: Demonstrate knowledge of Japanese Language Scripts (Reading, Writing, etc). CO3: Demonstrate knowledge of Japanese culture, lifestyle, etc. CO4: Pursue advanced Professional Japanese Language course. |
| 318560(D) | Mandatory Audit Course 4: MOOC- Learn New skills | CO1: Promote interactive user forums to support community interactions among students, professors, and experts. CO2: Promote learn additional skills anytime and anywhere. CO3: Enhance teaching and learning on campus and online |
Second Year Artificial Intelligence & Machine Learning (2020 Course)
| SEMESTER – III | ||
|---|---|---|
| Course Code | Course Name | Course Outcomes |
| 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 solution 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 implement learned algorithm design techniques and data structures to solve problems. CO6: Design different hashing functions and use files 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 of files for persistent data storage for real world application. 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 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 to 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 of 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 application. CO6: Apply appropriate design patterns to provide object-oriented solutions. |
| 218548 | Computer Networks Laboratory | CO1: Implement small size network and its use of various networking commands. CO2: Understand and apply of networking and simulation tool i.e packet tracer. CO3: Configure the various routing and switching protocols using packet tracer. CO4: Configure various client/server environments to use application layer protocols. CO5: Explore 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: Able to understand the nature of the individual and the relationship between self and the community. CO5: Able to 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 discussion, 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 team work, Inter-personal relationships, conflict management and leadership quality. |
| 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: Analyse concerns of privacy, privacy rights in information-gathering practices in IT. |
| 218551 (B) | Mandatory Audit Course3: 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 about 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: Analyse and evaluate the cyber security needs of an organization. CO3: Understand the importance of cyber laws and its practices. CO4: Determine and analyse software vulnerabilities and security solutions to reduce the risk of exploitation. |
| SEMESTER – IV | ||
|---|---|---|
| Course Code | Course Name | Course Outcomes |
| 207003 | Applied Mathematics | CO1: Solve Linear differential equations, essential in modelling 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 given scenario. CO3: Explain synchronization and deadlock; analyse 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 softwares. |
| 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 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 makes 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, circle, and apply it for problem solving. CO2: Employ techniques of geometrical transforms to produce, position and manipulate Objects in 2 dimensional and 3-dimensional space respectively. CO3: Describe mapping from a world coordinates to device coordinates, clipping, and projections in order to produce 3D images on 2D output device. CO4: Apply concepts of rendering, shading, animation, curves and fractals using computer graphics tools in design, development and testing of 2D, 3D modelling applications. CO5: Perceive the concepts of virtual reality. |
| 218556 | Operating System Laboratory | CO1: To apply the basics of Linux commands. CO2: To build shell scripts for various applications. CO3: To implement basic building blocks like processes, threads under the Linux. CO4: To develop various system programs for the functioning of OS concepts in user space like concurrency control, CPU Scheduling, Memory Management and Disk Scheduling in Linux. CO5: To develop system programs for Inter Process Communication in Linux. |
| 218557 | Computer Graphics Laboratory | CO1: Apply line& circle drawing algorithms to draw the objects. CO2: Apply polygon filling methods for the object. CO3: Apply polygon clipping algorithms for the object. CO4: Apply the 2D transformations on the object. CO5: Implement the curve generation algorithms. CO6: Demonstrate the animation of any object using animation principles. |
| 218558 | Database Management System Laboratory | CO1: Install and configure database systems. CO2: Analyze database models & 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 / DCL commands. CO6: Design a backend database of any one organization: CASE STUDY |
| 218559 | Project Based Learning – II | CO1: Design solution to real life problems and analyze its concerns through shared cognition. CO2: Apply learning by doing approach in PBL 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, various moral and social issues, industrial standards, code of ethics and role of professional ethics in engineering field. CO2: Aware of professional rights and responsibilities of an engineer, responsibilities of an engineer for safety and risk benefit analysis. CO3: Understand the impact of the professional Engineering solutions in societal and Environmental contexts, and demonstrate the knowledge of, and need for sustainable development. CO4: Acquire knowledge about various roles of engineers in variety of global issues and able to apply ethical principles to resolve situations that arise in their professional lives. |
| 218561 (A) | Mandatory Audit course 4: Water Supply and Management | CO1: Relate the relations between the environment and ecology, estimating water requirement for public water supply scheme. CO2: Assess the quality of water as per BIS and select the appropriate treatment method required for the water source. CO3: Analyse the suitable distribution system for a locality and know the appurtenances used. CO4: Summarize the arrangement of water supply and fittings in a building. CO5: Determine the need of conservation of water and rural water supply. CO6: Identify the 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 conversation in Japanese. CO2: Comprehend Grammar of Japanese Script. CO3: Translate simple sentences from Japanese to English and vice a versa. CO4: Be aware about Japanese society and people. |
| 218561 (C) | Mandatory Audit course 4 : e-Waste Management and Pollution Control | CO1: Discuss various types of e-waste sources. CO2: Understand impact of various e-wastes. CO3: Identify characteristics of various e-Waste pollutants. CO4: Understand process of e-Waste Recycling and relevant technologies. CO5: Discuss causes, effects and control measures of different environment pollution. CO6: Demonstrate Safe methods for disposal of e-waste and controlling the pollution. |
| 218561 (D) | Mandatory Audit course 4: Intellectual Property Rights | CO1: Exhibit the concepts of Intellectual Property Rights. CO2: Differentiate among different IPR. CO3: Formulate and characterize innovative ideas and inventions into IPR. CO4: Demonstrate knowledge of advances in patent law and IP regulations |