Course Overview

The "Techno Professional Skills for the Modern Workplace" course is a 12-week hybrid program designed for professionals seeking to enhance their technical skills and workplace effectiveness. Participants will develop essential technical proficiency relevant to their industries, cultivate analytical and critical thinking abilities, and improve their communication skills to convey technical information clearly to diverse audiences. The course begins with an introduction to the importance of technical skills, followed by modules on essential software tools, basic coding, data literacy, and cybersecurity fundamentals. Participants will learn effective communication strategies for technical concepts, explore project management methodologies like Agile and Scrum, and gain hands-on experience with collaboration tools such as Slack and Zoom. Emphasis is placed on problem-solving techniques, adapting to emerging technologies like AI and automation, and building professional networks. In the final weeks, the course will focus on personal branding and career development, including resume building and interview preparation. The program culminates in a capstone project where participants present their work, allowing for practical application of learned skills. Upon successful completion, participants will receive a certificate, equipping them to thrive in technology-driven environments and enhancing both individual performance and team collaboration.

Course Outcomes

• Demonstrated Technical Proficiency: Participants will be able to effectively use essential software tools and coding basics relevant to their industry, enhancing their overall technical competence.
• Enhanced Problem-Solving Skills: Learners will develop the ability to analyze complex challenges and apply critical thinking techniques to identify and implement effective solutions.
• Effective Communication: Participants will be equipped to communicate technical concepts clearly and confidently, both in written documentation and verbal presentations, tailored to various audiences.
• Collaboration in Tech-Driven Environments: Graduates will be able to leverage collaborative technologies and project management methodologies to work effectively within teams, whether in-person or remotely.
• Adaptability to Emerging Technologies: Learners will stay informed about the latest trends in technology and demonstrate the ability to adapt their skills and strategies to leverage new tools and innovations in their professional roles.

Course Overview

CO Curricular is going to make student aware of extra activities beyond usual core syllabus . Like coding, drawing poetry etc

Course Outcomes

Course Overview

This course covers fundamental concepts in Discrete Mathematics, including Boolean algebra, abstract algebra, combinatorics, graph theory, and logic. Topics include truth tables, basic logic gates, set theory, group theory, counting principles, graph theory fundamentals, and propositional calculus. Students explore various proof techniques, such as mathematical induction, and learn about the principles of satisfiability and validity in logical reasoning.

Course Outcomes

• Express a logic sentence in terms of predicates, quantifiers, and logical connectives.
• Derive the solution for a given problem using deductive logic and prove the solution based on logical inference.
• Classify its algebraic structure for a given a mathematical problem.
• Evaluate Boolean functions and simplify expressions using the properties of Boolean algebra.
• Develop the given problem as graph networks and solve with techniques of graph theory.

Course Overview

This course introduces foundational concepts in statistics, probability, and calculus, providing students with essential mathematical tools for data analysis and problem-solving.

Course Outcomes

• Understanding the fundamental concepts of probability and statistics.
• Describe important probability distributions like Binomial, Poisson Distributions and Normal Distributions
• Explain the concept of testing of hypothesis.
• Analyse the concepts of correlation, regression and estimations and their properties.
• Explain the concept sampling distributions and estimation.

Course Overview

This course covers fundamental concepts in Discrete Mathematics, including Boolean algebra, abstract algebra, combinatorics, graph theory, and logic. Topics include truth tables, basic logic gates, set theory, group theory, counting principles, graph theory fundamentals, and propositional calculus. Students explore various proof techniques, such as mathematical induction, and learn about the principles of satisfiability and validity in logical reasoning.

Course Outcomes

• Express a logic sentence in terms of predicates, quantifiers, and logical connectives.
• Derive the solution for a given problem using deductive logic and prove the solution based on logical inference.
• Classify its algebraic structure for a given a mathematical problem.
• Evaluate Boolean functions and simplify expressions using the properties of Boolean algebra.
• Develop the given problem as graph networks and solve with techniques of graph theory.

Course Overview

This course introduces foundational concepts in statistics, probability, and calculus, providing students with essential mathematical tools for data analysis and problem-solving.

Course Outcomes

• Understanding the fundamental concepts of probability and statistics.
• Describe important probability distributions like Binomial, Poisson Distributions and Normal Distributions
• Explain the concept of testing of hypothesis.
• Analyse the concepts of correlation, regression and estimations and their properties.
• Explain the concept sampling distributions and estimation.

Course Overview

Students gain a comprehensive understanding of core concepts in computer science through lectures and hands-on laboratory sessions, covering topics such as algorithms, data structures, and programming languages.

Course Outcomes

• Explain the working of a computer and its various components
• Discuss the use of Software and programming in a computer system.
• Outline the basic concepts of Computer Networks and Internet Protocols.
• Develop Proficiency in Identifying different types of computer viruses, worms, and malware to enhance threat awareness.
• Apply the role of various Software packages for Office Automation

Course Overview

Students gain a comprehensive understanding of core concepts in computer science through lectures and hands-on laboratory sessions, covering topics such as algorithms, data structures, and programming languages.

Course Outcomes

• Explain the basic terminology used in computer programming to write, compile and debug programs in C programming language.
• Examine the syntax and semantics and be fluent in the use of various Operators of C Programming.
• Demonstrate the concept of Conditional statements and looping in programming.
• Develop programs to describe the applications of derived data types such as arrays and strings etc.
• Illustarte the dynamics of memory by the use of pointers and Structures

Course Overview

This course explores fundamental principles of electrical engineering, including circuit analysis, electromagnetism, and electronic devices, through theoretical study and practical laboratory experiments.

Course Outcomes

• Analyses basic DC and AC electric circuits.
• Explain the working principles of transformers and electrical machines.
• Explain the concepts of electric power transmission and distribution of power
• Understand the wiring methods, electricity billing, and working principles of circuit protective devices and personal safety measures
• Verify KCL, KVL, and maximum power transfer theorem (MPTT) and analyze the effects of open and short circuits in DC circuits.

Course Overview

This course explores fundamental principles of electrical engineering, including circuit analysis, electromagnetism, and electronic devices, through theoretical study and practical laboratory experiments.

Course Outcomes

• Analyses basic DC and AC electric circuits.
• Explain the working principles of transformers and electrical machines.
• Explain the concepts of electric power transmission and distribution of power
• Understand the wiring methods, electricity billing, and working principles of circuit protective devices and personal safety measures
• Verify KCL, KVL, and maximum power transfer theorem (MPTT) and analyze the effects of open and short circuits in DC circuits.

Course Overview

Students study the principles of physics relevant to computing science, including mechanics, thermodynamics, and electromagnetism, through theoretical instruction and laboratory experiments.

Course Outcomes

• understand the importance of Applied Physics in describing the physical phenomena.
• Employ the knowledge of crystallography and X-Rays to understand the structure-property relationship of materials
• Implement the concept of Theory of relativity and Quantum mechanics for research applications.
• Recognize the use of Laser, Magnetic materials, Superconductors and optical fibers in various fields.
• Acquire Basic knowledge of EMFT in communication and Nanophysics for its applications in the field of medicine, data storage devices and electronics.

Course Overview

Students study the principles of physics relevant to computing science, including mechanics, thermodynamics, and electromagnetism, through theoretical instruction and laboratory experiments.

Course Outcomes

• understand the importance of Applied Physics in describing the physical phenomena.
• Employ the knowledge of crystallography and X-Rays to understand the structure-property relationship of materials
• Implement the concept of Theory of relativity and Quantum mechanics for research applications.
• Recognize the use of Laser, Magnetic materials, Superconductors and optical fibers in various fields.
• Acquire Basic knowledge of EMFT in communication and Nanophysics for its applications in the field of medicine, data storage devices and electronics.

Course Overview

Building on foundational communication skills, this course emphasizes effective business communication strategies, including professional writing, presentation techniques, and interpersonal communication in organizational settings. Students learn to analyze and interpret data to make informed business decisions, focusing on creating value for stakeholders.

Course Outcomes

• Recognize the need for life skills and values (Understand)
• Identify own strengths and opportunities (Analyse)
• Recognize the importance of vocabulary enrichment (Understand)
• Understand the basic tenets of communication and apply the basic communication practices in different types of communication (Apply)
• Apply the life skills to different situations (Apply)

Course Overview

Building on foundational communication skills, this course emphasizes effective business communication strategies, including professional writing, presentation techniques, and interpersonal communication in organizational settings. Students learn to analyze and interpret data to make informed business decisions, focusing on creating value for stakeholders.

Course Outcomes

• Recognize the need for life skills and values (Understand)
• Identify own strengths and opportunities (Analyse)
• Recognize the importance of vocabulary enrichment (Understand)
• Understand the basic tenets of communication and apply the basic communication practices in different types of communication (Apply)
• Apply the life skills to different situations (Apply)

Course Overview

This course introduces fundamental concepts of linear algebra, covering topics such as vectors, matrices, linear transformations, eigenvalues, and eigenvectors. The accompanying lab sessions provide hands-on experience with matrix operations, solving linear equations, and applications in computer graphics and engineering.

Course Outcomes

• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.
• Define matrices, linear equations, and determinants, recall basic vector algebra.
• Understand basic concepts such as vector spaces, linear dependence /independence of vectors, basis and linear maps
• Analyze and calculate eigen values, eigen vectors, rank nullity of a matrix / linear map.
• Prove theorems, apply Gram-Schmidt process on inner product spaces, diagonalize special matrices.
• Apply concepts of linear algebra to various applications including real life problems.

Course Overview

Students learn statistical techniques for data analysis and modeling, including probability distributions, hypothesis testing, regression analysis, and experimental design. Labs offer practical experience in applying statistical software to analyze real-world data sets and interpret results.

Course Outcomes

• Compute the probabilities of composite events along with an understanding of the random variables.
• Perform and interpret the various design of experiments and their implementation using different statistical software.
• measure the different components of the time-series
• Learn the Markov processes with a study of stochastic process, multivariate data and their applications to real word problems.
• Implementation of statistical techniques using statistical packages viz. SPSS and etc.

Course Overview

This course explores data structures such as arrays, linked lists, trees, and graphs, along with algorithm design and analysis techniques. Labs focus on implementing data structures and algorithms in programming languages like C, C++ or Java, emphasizing efficiency and problem-solving skills.

Course Outcomes

• Illustrate the Basic concepts of Data Structures.
• Apply Data Structure techniques on computing problem
• Analyse and develop algorithms to solve real world problems.
• Implement and developed program for various concepts of data structures including array, stack, queue, graphs and trees.
• Demonstarte and analyze various sorting algorithms and hashing techniques.

Course Overview

Students study the fundamental principles of electronics, including circuit analysis, semiconductor devices, and digital electronics. Lab sessions provide hands-on experience with electronic components, circuit design, and measurement techniques using instruments like oscilloscopes and multimeters.

Course Outcomes

• Interpret different number systems, binary codes and Boolean algebra to minimize logic expressions
• Develop K-maps to minimize and optimize logic functions up to 5 variables
• Infer the knowledge about various logic gates and logic families and analyze basic circuits of these families
• Design and implement Combinational and Sequential logic circuits.
• Describe and compare various memory systems, shift registers and analog to digital and digital to analog conversion circuits

Course Overview

This course introduces basic economic principles, including microeconomics and macroeconomics concepts such as supply and demand, market structures, GDP, inflation, and fiscal policy. Students explore economic theories and their applications to real-world issues, gaining insights into decision-making processes in various economic contexts.

Course Outcomes

• Understand the key issues related to the Indian economy
• Understand major policy debates especially in the Indian context
• Understand the difference between growth and development and factors in development
• Understand role of population in economic development and issue of unemployment
• Understand financial and banking sector reforms and monetary policy with special reference to India

Course Overview

This course covers fundamental concepts in environmental science, including ecosystems, biodiversity, climate change, pollution, and sustainability. Students explore the interconnections between human activities and the natural environment, gaining awareness of environmental issues and potential solutions for creating a more sustainable future.

Course Outcomes

• Demonstrate the multidisciplinary nature of environmental studies
• Learning about natural resource, its importance and environmental impacts of Human activities on natural resource
• Explain environment and ecosystem, concept of biodiversity.
• Aware students about problems of environmental pollution, its impact and control measures.
• Illustrate the human population and the environment

Course Overview

This course explores formal languages, automata theory, and computational models. Topics include regular languages, finite automata, context-free grammars, pushdown automata, and Turing machines. Students learn about language recognition, parsing techniques, and the theoretical foundations of computation.

Course Outcomes

• Describe formal models of computation, such as finite automata, pushdown automata, and Turing machines.
• Design Finite Automata’s for different Regular Expressions and Languages.
• Compare different types of Grammars and design context free grammars for formal languages.
• Construct and analyze Push Down automata and Turing Machine for formal languages.
• Classify machines by their power to recognize languages

Course Overview

This course delves into the design and organization of computer systems. Topics include digital logic circuits, CPU architecture, memory systems, input/output systems, and assembly language programming. Students gain insight into the underlying hardware components and their interactions.

Course Outcomes

• Outline the basics of instructions sets and their impact on processor design
• Examine the control unit design approaches, memory design technologies and I/O transfers.
• Explain the concepts of pipelining in Computer Architecture.
• Interpret and analyze Parallel Processing Principles and Applications.
• Demonstrate the concepts of Memory Organization Through Mapping Functions and Replacement Algorithms.

Course Overview

This course introduces object-oriented programming concepts and techniques. Topics include classes, objects, inheritance, polymorphism, encapsulation, and abstraction. Students learn to design and implement object-oriented solutions to complex problems, emphasizing modularity, reusability, and maintainability. Practical lab sessions provide hands-on experience with programming languages like C++.

Course Outcomes

• Demonstrate the fundamental principles of OO programming, OO analysis, design and development.
• Explain the principles of data abstraction, encapsulation and inheritance in C++
• Describe the concepts of polymorphism and virtual function on computing problem.
• Design applications for a range of problems using file and exception handling.
• Illustrate the process of data file manipulation using C++

Course Overview

This course covers statistical methods and techniques used in computer science applications. Topics include probability theory, statistical inference, hypothesis testing, regression analysis, and data visualization. Students learn to apply statistical principles to analyze and interpret data, with practical exercises in statistical software tools.

Course Outcomes

• Concepts of probability and statistics
• Data analysis, statistical pattern recognition and data mining concepts
• Classification and regression trees
• Multiple Regression Analysis, Logistic Regression, k- Nearest Neighbor Classification
• Implementations of Logistic regression and Apriori algorithms

Course Overview

This course explores principles and practices in software development. Topics include software requirements analysis, design methodologies, software testing, quality assurance, and project management. Students learn to apply software engineering principles to develop reliable, scalable, and maintainable software systems. Practical lab sessions focus on applying software engineering techniques in real-world projects.

Course Outcomes

• Explain software engineering principles involved in building large software programs.
• Illustrate the concepts and process of requirements specification and requirements validation.
• Analyze system models for designing patterns.
• Distinguish the concept of software testing.
• Apply estimation techniques, schedule project activities and compute pricing.

Course Overview

This course provides an overview of the Indian Constitution and its significance in the legal and political framework of India. Topics include the Preamble, fundamental rights and duties, directive principles of state policy, and the structure of government. Students gain an understanding of the constitutional principles and their impact on Indian society and governance.

Course Outcomes

• Explain the background of the present constitution of India and features.
• Utilize the fundamental rights and duties.
• Understand the working of the union executive, parliament and judiciary.
• Understand the working of the state executive, legislature and judiciary.
• Utilize the special provisions and statutory institutions.
• Explain the background of the present constitution of India and features.
• Utilize the fundamental rights and duties.
• Understand the working of the union executive, parliament and judiciary.
• Understand the working of the state executive, legislature and judiciary.
• Utilize the special provisions and statutory institutions.

Course Overview

This course introduces students to operating system concepts, including process management, memory management, file systems, and device management. The accompanying lab focuses on Unix-based systems, providing hands-on experience in system administration and shell scripting.

Course Outcomes

• Explain the basic concepts of Operating Systems and related concepts
• Demonstrate the concepts of processes and threads, process scheduling including Throughput, Turnaround Time, Waiting Time, Response Time.
• Identify the concept for optimally allocating memory to processes by increasing memory utilization and improving the access time.
• Demonstrate and implement the concepts of deadlocks and reated concepts
• Implement various techniques of memory and file management.

Course Overview

This course covers the principles of database management, including relational database design, SQL querying, transaction management, and database security. The lab component offers practical exercises in database creation, querying, and optimization.

Course Outcomes

• Infer the basic concepts of database management system.
• Discover the basic fundamentals of creating a database by using data definition, data manipulation and control languages.
• Develop a database application and retrieve the values with the help of queries using SQL.
• Design, analyze and evaluate the project developed for an application.
• Demonstrate the concepts of database security, distributed database systems and object oriented databases

Course Overview

Students learn software design principles and techniques using Unified Modeling Language (UML). The lab sessions provide opportunities to apply UML diagrams for modeling software requirements, architecture, and behavior.

Course Outcomes

• Describe basic concept of UML, design, implementation of test cases and OOP concep
• Discuss and Analyses how to develop software requirements specifications for a given problem.
• Explain and build DFD models
• Develop various structure and behavior UML diagrams.
• Explain the knowledge of project management tool Demonstrate how to manage file using Project Libre project management tool.

Course Overview

This course introduces students to innovation processes, intellectual property (IP) management, and entrepreneurial concepts. Topics include idea generation, patenting, licensing, business models, and startup strategies.

Course Outcomes

• Discuss intellectual property strategy to protect inventions and innovations of new ventures.
• Develop skills of commercial appreciation by allocating knowledge about substantive aspects of management, strategy and legal literature.
• Support participants to recognize the various applications and methods of IP, as well as its nature, scope, and distinctions.
• Appraise participants to manage and strategize IP lifecycle effectively throughout the journey of start-up, in a time when it is aspired highly by the economy and society.
• Understand the fundamentals and advanced strategies of IP. Provide opportunity for understanding the same in MSME sector. Provide brief exposure about the valuation techniques and audits of IP.
• Discuss intellectual property strategy to protect inventions and innovations of new ventures.
• Develop skills of commercial appreciation by allocating knowledge about substantive aspects of management, strategy and legal literature.
• Support participants to recognize the various applications and methods of IP, as well as its nature, scope, and distinctions.
• Appraise participants to manage and strategize IP lifecycle effectively throughout the journey of start-up, in a time when it is aspired highly by the economy and society.
• Understand the fundamentals and advanced strategies of IP. Provide opportunity for understanding the same in MSME sector. Provide brief exposure about the valuation techniques and audits of IP.

Course Overview

This course explores the principles and methodologies of design thinking, emphasizing user-centered problem-solving and iterative prototyping. Students learn to empathize with users, define problem statements, ideate solutions, prototype concepts, and test and iterate designs.

Course Outcomes

• Compare and select problems suitable for DT projects and use techniques for empathetic research
• Identify and document insights, user habits and identify user needs Visualise solutions, evaluate solution concepts
• Create rough prototypes, gather feedback
• Create high-fidelity prototypes. Test user experience
• Identify a business model for a solution concept.Estimate financial results

Course Overview

This course covers mathematical modeling and optimization techniques for decision-making in business and engineering. Topics include linear programming, network optimization, integer programming, and simulation modeling. The lab component involves solving optimization problems using software tools.

Course Outcomes

• Solve linear programming problems using appropriate techniques and optimization solvers, interpret the results obtained.
• Determine optimal strategy for Minimization of Cost of shipping of products from source to Destination/ Maximization of profits of shipping products using various methods, Finding initial basic feasible and optimal solution of the Transportation problems
• Optimize the allocation of resources to Demand points in the best possible way using various techniques and minimize the cost or time of completion of number of jobs by number of persons.
• Model competitive real-world phenomena using concepts from game theory. Analyse pure and mixed strategy games
• Formulate Network models for service and manufacturing systems, and apply operations research techniques and algorithms to solve these Network problems

Course Overview

This course provides an overview of traditional Indian knowledge systems, including Ayurveda, yoga, Vedic mathematics, and indigenous sciences. Students explore the philosophical, scientific, and cultural aspects of Indian traditional knowledge for holistic learning.

Course Outcomes

• Illustrate the concept of Traditional knowledge and its importance.
• Identify the need and importance of protecting traditional knowledge.
• Outline the various enactments related to the protection of traditional knowledge.
• Demonstrate the concepts of Intellectual property to protect the traditional knowledge.
• Apply the traditional knowledge in different sectors.

Course Overview

This course provides an overview of key management principles and practices, including planning, organizing, leading, and controlling. Topics include organizational structure, decision-making processes, leadership styles, and strategic management concepts.

Course Outcomes

• Illustrate the circumstances that lead to management evolution that affect future managers and analyze the influence of historical forces on the current practice of management
• Identify and evaluate social responsibility and ethical issues involved in business situations and Adapt to an uncertain environment and identify techniques managers use to influence and control the internal environment.
• Develop the process of management's four functions: planning, organizing, leading, and controlling
• Evaluate leadership styles to anticipate the consequences of each leadership style.
• Identify the areas to control and Selecting the Appropriate controlling methods/Techniques

Course Overview

This course covers the principles of algorithm design and analysis, focusing on topics such as algorithm complexity, sorting algorithms, graph algorithms, and dynamic programming. Labs provide hands-on experience in implementing and analyzing algorithms.

Course Outcomes

• Classify worst-case running time based on asymptotic analysis and justify the correctness of algorithm for a given problem.
• Explain the greedy paradigm, dynamic-programming paradigm and divide-and-conquer paradigm.
• Design a given model engineering problem using graph and write the corresponding algorithm to solve the problems.
• Identify NP completeness and different NP complete problems.
• Illustrate various advanced topics on algorithms

Course Overview

This course introduces the fundamentals of machine learning algorithms and techniques, covering topics such as supervised and unsupervised learning, neural networks, and model evaluation. Labs offer practical experience in applying machine learning algorithms to real-world datasets.

Course Outcomes

• Outline the basic concepts of machine learning and Artificial Intelligence
• Analyze various AI and ML techniques in expert systems and other machine learning models.
• Illustration and application of supervised learning in different domains.
• Applicaiton of un-supervised learning in expert systems.
• Implementation of advanced concepts of AI and ML in emerging filed like Medical and Agricultural sciences.

Course Overview

This course explores cloud computing concepts, architectures, and technologies, covering topics such as virtualization, cloud service models, deployment models, and cloud security. Students learn to design, deploy, and manage cloud-based solutions for various applications and workloads.

Course Outcomes

• Recall and summarize the basic concepts of cloud computing
• Discuss the architectural design of cloud and illustrate various programming models.
• Outline the virtualization technology and determine their uses.
• Explain the basic threats and security mechanism in cloud
• Summarize the cloud available platforms for business and industry perspective

Course Overview

This course focuses on enhancing communication skills for business contexts, including written, verbal, and interpersonal communication. Additionally, students learn about value science principles and their application in business decision-making and problem-solving.

Course Outcomes

• Recognize the need for life skills and values
• Identify own strengths and opportunities
• Recognize the importance of vocabulary enrichment
• Understand the basic tenets of communication and apply the basic communication practices in different types of communication
• Apply the life skills to different situations

Course Overview

This course explores the principles and protocols of computer networks, covering topics such as network architectures, transmission media, routing algorithms, and network security. The lab component provides hands-on experience in configuring and troubleshooting network devices and protocols.

Course Outcomes

• Demonstrate computer network basics, network architecture, TCP/IP and OSI reference models.
• Examine various techniques and modes of transmission. Describe data link protocols, multi-channel access protocols and IEEE 802 standards for LAN
• Describe routing and congestion in network layer with routing algorithms and classify IPV4 addressing scheme
• Discuss the elements and protocols of transport layer
• Analyse the different protocols used at application layer i.e. HTTP, SNMP, SMTP, FTP, TELNET and VPN

Course Overview

Students study the principles of information security, including encryption algorithms, access control mechanisms, network security protocols, and security policies. The lab component focuses on practical implementation and evaluation of security measures to protect data and systems from threats.

Course Outcomes

• Formulate information security governance, and related legal and regulatory issues.
• Devices how threats to an organization are discovered, analyzed, and dealt with.
• Evaluate network security threats and countermeasures.
• Construct network security designs using available secure solutions (such as PGP, SSL, IPSec, etc)
• Acquire the knowledge of advanced security issues and technologies (such as DDoS attack detection and containment, and anonymous communications)

Course Overview

This course introduces students to artificial intelligence techniques, including machine learning, natural language processing, and computer vision. The lab component offers hands-on experience in developing AI applications, such as chatbots, image recognition systems, and recommendation engines.

Course Outcomes

• Demonstrate the basic concepts of machine learning techniques and basic principles of Artificial Intelligence.
• Explain the process of data pre-processing and feature extraction
• Explore the philosophical and ethical implications of AI and its potential applications in society.
• Outline the core machine learning algorithms, including supervised and unsupervised learning techniques.
• Illustrate the metrics for evaluating the performance of machine learning models

Course Overview

Students learn the fundamentals of financial and cost accounting, including financial statement analysis, budgeting, cost allocation methods, and managerial accounting techniques. The course emphasizes the role of accounting information in decision-making and financial management.

Course Outcomes

• Creating financial statements in accordance with appropriate standards. Interpret the business implications of financial statement information.
• Apply critical thinking skills to analyze financial data as well as the effects of differing financial accounting methods on the financial statements
• Define the needs of the various users of accounting data and demonstrate the ability to communicate such data effectively, as well as the ability to provide knowledgeable recommendations.
• Apply cost accounting methods to evaluate and project business performance. To make allocation of cost of product, apportionment of cost of product.
• Evaluate total cost of the product for fixing selling price.

Course Overview

This course focuses on effective business communication strategies and the application of value science principles in organizational settings. Topics include professional writing, presentation skills, negotiation techniques, and ethical considerations in business communication.

Course Outcomes

• Recognize the need for life skills and values
• Identify own strengths and opportunities
• Recognize the importance of vocabulary enrichment
• Understand the basic tenets of communication and apply the basic communication practices in different types of communication
• Apply the life skills to different situations

Course Overview

This course explores principles of usability design in software applications, covering user interface design, interaction design, and user experience evaluation. Students learn to create intuitive and efficient software interfaces through practical labs.

Course Outcomes

• Apply the fundamentals of User Centered Design and User Experience their relevance and contribution to businesses
• Apply the facets of User Experience (UX) Design, particularly to the digital artefacts
• Examine the user research, solution conceptualization and validation as interwoven activities in the design and development lifecycle
• Acquire the ability to constructively engage with the Design professionals they would work with in the future
• Analyse and identify the methods to offer a better UI experience for the applications. Gain expertise in redesigning an existing Application or website for better user experience

Course Overview

This workshop introduces students to Scilab or Matlab software, focusing on numerical computation, data analysis, and visualization techniques. Labs provide hands-on experience in solving engineering problems.

Course Outcomes

• Creating fundamental programs in Matlab, creating variables and mathematical functions
• Programming the fundamentals concepts of basic Plotting consisting of simple and multiple data sets in one plot
• Understand how to program matrix operations, array operations and how to solve the system of linear equations
• Understand how to program M-file scripts , M- file functions, Input –output Arguments
• Program control flow operators, loops, flow structures and debugging M-files

Course Overview

This course covers principles and practices of financial management, including financial analysis, budgeting, investment decisions, and risk management. Students gain insights into financial planning and decision-making processes in organizations.

Course Outcomes

• Have a deeper understanding in objectives of financial management and enable the students to access the proper sources of finance for the business.
• Enable the students to evaluate the finance plans on the basis of cost of capital and to acquaint a deeper knowledge in leverages in order to arrive a better finance decision.
• Equip the students to construct an optimal capital structure through the conceptual knowledge on capital structure theories and enable them to take better dividend decisions.
• Impart deeper understanding in working capital management to avail the adequate working capital for business functions.
• Enable the students to evaluate the capital budgets through capital budgeting techniques.

Course Overview

This course explores key concepts and practices in human resource management, including recruitment, training, performance appraisal, and employee relations. Students learn strategies for managing human capital effectively.

Course Outcomes

• Integrated perspective on role of HRM in modern business.
• Ability to plan human resources and implement techniques of job design
• Competency to recruit, train, and appraise the performance of employees
• Rational design of compensation and salary administration
• Ability to handle employee issues and evaluate the new trends in HRM

Course Overview

This course explores techniques for representing data visually to facilitate analysis and communication. Students learn to create effective visualizations using tools like charts, graphs, and dashboards to convey insights from data.

Course Outcomes

• Understand the fundamental design principles and different types of data visualization
• Identify both positive and negative impacts of data-informed decision across a variety of domains
• Apply the fundamental concepts of data visualization to define a project in your field of study.
• Practice the core principles using widely available tools (e.g. Tableau)
• Demonstrate the best practice that presents your story in the process of creating data visualization including connecting to different data sources, assessing to the quality of the data, and converting raw data into data visualizations that provide actionable information.

Course Overview

This course covers fundamental concepts and techniques in marketing research and marketing management. Topics include market analysis, consumer behavior, product development, branding, pricing strategies, and promotional tactics.

Course Outcomes

• Illustrate the different market research methods such as surveys, focus groups, interviews, observational studies, and data analysis techniques.
• Develop skills in collecting, organizing, and analyzing marketing data using both qualitative and quantitative techniques.
• Learn how to segment markets based on demographics, psychographics, behavior, and other factors.
• Develop comprehensive marketing plans and strategies based on market research insights.
• learn how to evaluate marketing performance using key performance indicators (KPIs), metrics, and marketing analytics tools. They should be able to assess the effectiveness of marketing campaigns, make data-driven recommendations, and adjust strategies based on performance feedback.