Nirmala Foundation - Degree College

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Program Specific Outcome

<ul>
	<li>PSO1: Ability to apply the knowledge of Information Technology with recent trends aligned with research and industry.</li>
	<li>PSO2: Ability to apply IT in the field of Computational Research, Soft Computing, Big Data Analytics, Data Science, Image Processing, Artificial Intelligence, Networking and Cloud Computing.</li>
	<li>PSO3: Ability to provide socially acceptable technical solutions in the domains of Information Security, Machine Learning, Internet of Things and Embedded System, Infrastructure Services as specializations.</li>
	<li>PSO4: Ability to apply the knowledge of Intellectual Property Rights, Cyber Laws and Cyber Forensics and various standards in interest of National Security and Integrity along with IT Industry.</li>
	<li>PSO5: Ability to write effective project reports, research publications and content development and to work in multidisciplinary environment in the context of changing technologies</li>
</ul>

Course Outcome

Semester I

<ol>
	<li>Research in Computing </li>
</ol>

<ul>
	<li>To be able to conduct business research with an understanding of all the latest theories.</li>
	<li>To develop the ability to explore research techniques used for solving any real world or innovate problem.</li>
</ul>

A learner will be able to:

<ul>
	<li>Solve real world problems with scientific approach.ï€ </li>
	<li>Develop analytical skills by applying scientific methods.ï€ </li>
	<li>Recognize, understand and apply the language, theory and models of the field of business analyticsï€  </li>
	<li>Foster an ability to critically analyze, synthesize and solve complex unstructured business problemsï€ </li>
	<li>Understand and critically apply the concepts and methods of business analytics</li>
	<li>Identify, model and solve decision problems in different settingsï€ </li>
	<li>Interpret results/solutions and identify appropriate courses of action for a given managerial situation whether a problem or an opportunityï€ </li>
	<li>Create viable solutions to decision making problemsï€ </li>
</ul>

<ol>
	<li>Data Science </li>
</ol>

<ul>
	<li>Develop in depth understanding of the key technologies in data science and business analytics: data mining, machine learning, visualization techniques, predictive modeling, and statistics.ï€ </li>
	<li>Practice problem analysis and decision-making.ï€ </li>
	<li>Gain practical, hands-on experience with statistics programming languages and big data tools through coursework and applied research experiences.ï€ </li>
	<li>Apply quantitative modeling and data analysis techniques to the solution of real world business problems, communicate findings, and effectively present results using data visualization techniques.</li>
	<li>Recognize and analyze ethical issues in business related to intellectual property, data security, integrity, and privacy.</li>
	<li>Apply ethical practices in everyday business activities and make well-reasoned ethical business and data management decisions.</li>
	<li>Demonstrate knowledge of statistical data analysis techniques utilized in business decision-making.</li>
	<li>Apply principles of Data Science to the analysis of business problems.</li>
	<li>Use data mining software to solve real-world problems.</li>
	<li>Employ cutting edge tools and technologies to analyze Big Data.</li>
	<li>Apply algorithms to build machine intelligence.</li>
	<li>Demonstrate use of teamwork, leadership skills, decision-making and organization theory.</li>
</ul>

<ol>
	<li>Cloud Computing</li>
</ol>

<ul>
	<li>To learn how to use Cloud Services.ï€ </li>
	<li>To implement Virtualization.ï€ </li>
	<li>To implement Task Scheduling algorithms.ï€ </li>
	<li>Apply Map-Reduce concept to applications.ï€ </li>
	<li>To build Private Cloud.ï€ </li>
	<li>Broadly educate to know the impact of engineering on legal and societal issues involved.</li>
</ul>

ï€

Course Outcome :

<ul>
	<li>Analyze the Cloud computing setup with its vulnerabilities and applications using different architectures.</li>
	<li>Design different workflows according to requirements and apply map reduce programming model.</li>
	<li>Apply and design suitable Virtualization concept, Cloud Resource Management and design scheduling algorithms.</li>
	<li>Create combinatorial auctions for cloud resources and design scheduling algorithms for computing clouds</li>
	<li>Assess cloud Storage systems and Cloud security, the risks involved, its impact and develop cloud application</li>
	<li>Broadly educate to know the impact of engineering on legal and societal issues involved in addressing the security issues of cloud computing.</li>
</ul>

<ol>
	<li>Soft Computing Techniques</li>
</ol>

<ul>
	<li>Soft computing concepts like fuzzy logic, neural networks and genetic algorithm, where Artificial Intelligence is mother branch of all.</li>
	<li>All these techniques will be more effective to solve the problem efficiently</li>
</ul>

Course Outcome :

<ul>
	<li>Identify and describe soft computing techniques and their roles in building intelligent machines</li>
	<li>Recognize the feasibility of applying a soft computing methodology for a particular problem</li>
	<li>Apply fuzzy logic and reasoning to handle uncertainty and solve engineering problems</li>
	<li>Apply genetic algorithms to combinatorial optimization problems</li>
	<li>Apply neural networks for classification and regression problems</li>
	<li>Effectively use existing software tools to solve real problems using a soft computing approach</li>
	<li>Evaluate and compare solutions by various soft computing approaches for a given problem.</li>
</ul>

Semester II

<ol>
	<li>BigData Analytics</li>
</ol>

Course Objectives:

<ul>
	<li>To provide an overview of an exciting growing field of big data analytics.</li>
	<li>To introduce the tools required managing and analyzing big data like Hadoop, NoSql MapReduce.</li>
	<li>To teach the fundamental techniques and principles in achieving big data analytics with scalability and streaming capability.</li>
	<li>To enable students to have skills that will help them to solve complex realworld problems in for decision support</li>
</ul>

Course Objectives:

<ul>
	<li>Understand the key issues in big data management and its associated applications in intelligent business and scientific computing.</li>
	<li>Acquire fundamental enabling techniques and scalable algorithms like Hadoop, Map Reduce and NO SQL in big data analytics.</li>
	<li>Interpret business models and scientific computing paradigms, and apply software tools for big data analytics.</li>
	<li>Achieve adequate perspectives of big data analytics in various applications like recommender systems, social media applications etc.</li>
</ul>

<ol>
	<li>Modern Networking</li>
</ol>

Course Objectives

<ul>
	<li>To understand the state-of-the-art in network protocols, architectures and applications.</li>
	<li>Analyze existing network protocols and networks.</li>
	<li>Develop new protocols in networking</li>
	<li>To understand how networking research is done</li>
	<li>To investigate novel ideas in the area of Networking via term-long research projects.</li>
</ul>

Course Objectives

<ul>
	<li>Demonstrate in-depth knowledge in the area of Computer Networking.</li>
	<li>To demonstrate scholarship of knowledge through performing in a group to identify, formulate and solve a problem related to Computer Networks</li>
	<li>Prepare a technical document for the identified Networking System Conducting experiments to analyze the identified research work in building Computer Networks</li>
</ul>

<ol>
	<li>Microservice Architecture</li>
</ol>

Course Objectives

<ul>
	<li>Gain a thorough understanding of the philosophy and architecture of</li>
	<li>Web applications using ASP.NET Core MVC;ï€ </li>
	<li>Gain a practical understanding of.NET Core;ï€ </li>
	<li>Acquire a working knowledge of Web application development using</li>
	<li>ASP.NET Core MVC 6 and Visual Studioï€ </li>
	<li>Persist data with XML Serialization and ADO.NET with SQL Serverï€ </li>
	<li>Create HTTP services using ASP.NET Core Web API;ï€ </li>
	<li>Deploy ASP.NET Core MVC applications to the Windows Azure cloud.ï€ </li>
</ul>

Course Outcome

<ul>
	<li>Develop web applications using Model View Control.ï€ </li>
	<li>Create MVC Models and write code that implements business logic within Model methods, properties, and events.ï€ </li>
	<li>Create Views in an MVC application that display and edit data and interact with Models and Controllers.ï€ </li>
	<li>Boost your hire ability through innovative and independent learning.ï€ </li>
	<li>Gaining a thorough understanding of the philosophy and architecture of .NET Coreï€ </li>
	<li>Understanding packages, meta packages and frameworksï€ </li>
	<li>Acquiring a working knowledge of the .NET programming modelï€ </li>
	<li>Implementing multi-threading effectively in .NET applications</li>
</ul>

<ol>
	<li>Image Processing</li>
</ol>

<ul>
	<li>Review the fundamental concepts of a digital image processing system.</li>
	<li>Analyze images in the frequency domain using various transforms.</li>
	<li>Evaluate the techniques for image enhancement and image restoration.</li>
	<li>Categorize various compression techniques.</li>
	<li>Interpret Image compression standards.</li>
	<li>Interpret image segmentation and representation techniques.</li>
</ul>

Course Outcome :

<ul>
	<li>Understand the relevant aspects of digital image representation and their practical implications.</li>
	<li>Have the ability to design pointwise intensity transformations to meet stated specifications.</li>
	<li>Understand 2-D convolution, the 2-D DFT, and have the abitilty to design systems using these concepts.</li>
	<li>Have a command of basic image restoration techniques.</li>
	<li>Understand the role of alternative color spaces, and the design requirements leading to choices of color space.</li>
	<li>Appreciate the utility of wavelet decompositions and their role in image processing systems.</li>
	<li>Have an understanding of the underlying mechanisms of image compression, and the ability to design systems using standard algorithms to meet design specifications.</li>
</ul>

Semester III

<ol>
	<li>Technical Writing</li>
</ol>

Course Objectives:

<ul>
	<li>This course aims to provide conceptual understanding of developing strong foundation in general writing, including research proposal and reports.</li>
	<li>It covers the technological developing skills for writing Article, Blog, E-Book, Commercial web Page design, Business Listing Press Release, E-Listing and Product Description.</li>
	<li>This course aims to provide conceptual understanding of innovation and entrepreneurship development.</li>
</ul>

Course Outcomes:

After completion of the course, a student should be able to:

<ul>
	<li>CO1: Develop technical documents that meet the requirements with standard guidelines. Understanding the essentials and hands-on learning about effective Website Development. </li>
	<li>CO2: Write better quality content which ranks faster at Search Engines. Build effective Social Media Pages. </li>
	<li>CO3: Evaluate the essentials parameters of effective Social Media Pages. </li>
	<li>CO4: Understand importance of innovation and entrepreneurship. </li>
	<li>CO5: Analyze research and development projects.</li>
</ul>

<ol>
	<li>Applied AI</li>
</ol>

Course Objectives: -

<ul>
	<li>To explore the applied branches of artificial intelligence – </li>
	<li>To enable the learner to understand applications of artificial intelligence – </li>
	<li>To enable the student to solve the problem aligned with derived branches of artificial intelligence.</li>
</ul>

Course Outcomes:

After completion of course the learner will:

<ul>
	<li>CO1: be able to understand the fundamentals concepts of expert system and its applications.</li>
	<li>CO2: be able to use probability and concept of fuzzy sets for solving AI based problems.</li>
	<li>CO3: be able to understand the applications of Machine Learning. The learner can also apply fuzzy system for solving problems.</li>
	<li>CO4: learner will be able to apply to understand the applications of genetic algorithms in different problems related to artificial intelligence.</li>
	<li>CO5: A learner can use knowledge representation techniques in natural language processing.</li>
</ul>

<ol>
	<li>Machine Learning</li>
</ol>

Course Objectives:

<ul>
	<li>Understanding Human learning aspects. </li>
	<li>Understanding primitives in learning process by computer. </li>
	<li>Understanding nature of problems solved with Machine Learning</li>
</ul>

Course Outcomes:

After completion of the course, a student should be able to:

<ul>
	<li>CO1: Understand the key issues in Machine Learning and its associated applications in intelligent business and scientific computing. </li>
	<li>CO2: Acquire the knowledge about classification and regression techniques where a learner will be able to explore his skill to generate data base knowledge using the prescribed techniques. </li>
	<li>CO3: Understand and implement the techniques for extracting the knowledge using machine learning methods. </li>
	<li>CO4: Achieve adequate perspectives of big data analytics in various applications like recommender systems, social media applications etc. </li>
	<li>CO5: Understand the statistical approach related to machine learning. He will also Apply the algorithms to a real-world problem, optimize the models learned and report on the expected accuracy that can be achieved by applying the models.</li>
</ul>

<ol>
	<li>Robotic Process Automation</li>
</ol>

Course Objectives:

<ul>
	<li>To make the students aware about the automation today in the industry. </li>
	<li>To make the students aware about the tools used for automation. </li>
	<li>To help the students automate a complete process</li>
</ul>

Course Outcomes: After completing the course, a learner will be able to:

<ul>
	<li>CO1: Understand the mechanism of business process and can provide the solution in an optimize way. </li>
	<li>CO2: Understand the features use for interacting with database plugins. </li>
	<li>CO3: Use the plug-ins and other controls used for process automation. </li>
	<li>CO4: Use and handle the different events, debugging and managing the errors. </li>
	<li>CO5: Test and deploy the automated process.</li>
</ul>

Program Outcome

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