AI & DS Engineering

AI & Data Science PO & PSO

Program Outcomes (PO) :
1. Apply the knowledge of mathematics, science, engineering fundamentals, and engineering specialization to the solution of complex engineering problems.
2. Identify, formulate, research literature, and analyze engineering problems to arrive at substantiated conclusions using first principles of mathematics, natural, and engineering sciences.
3. Design solutions for complex engineering problems and design system components, processes to meet the specifications with consideration for the public health and safety, and the cultural, societal, and environmental considerations.
4. Use research-based knowledge including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
5. Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
6. Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
7. Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
8. Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
9. Function effectively as an individual, and as a member or leader in teams, and in multidisciplinary settings.
10. Communicate effectively with the engineering community and with society at large. Write effective reports documentation.

PO & PSO

Program Specific Outcome (PSOs) :
1. The ability to analyse, design and develop software systems applying the knowledge acquired in core courses such as data science, database, machine learning cloud computing big data and software engineering.
2. The utilization of skills assimilated in basic Data Science Courses to build up expertise in advanced areas of deep learning, NLP, Cloud security, Image & Vision processing etc.
3. Oneself as a global standard Data Science professional with good morals, ethics and sensitivity towards mankind and as a responsible team member.

Course Outcomes

SEM

Subject

Sub Code

Course Outcome

Course Outcome

SEM I

Database Management Systems

317523

CO1

Analyze and design Database Management System using ER model

CO2

Implement database queries using database languages

CO3

Normalize the database design using normal forms

CO4

Apply Transaction Management concepts in real-time situations

CO5

Use NoSQL databases for processing unstructured data

CO6

Differentiate between Complex Data Types and analyze the use of appropriate data types

SEM I

Computer Networks

317527

CO1

Summarize fundamental concepts of Computer Networks, architectures, protocols and technologies

CO2

Analyze the working of physical layer protocols.

CO3

Analyze the working of different routing protocols and mechanisms

CO4

Implementclient-server applications using sockets

CO5

Illustrate role of application layer with its protocols, client-server architectures

 

 

CO6

Summarizeconcepts of MAC and ethernet.

SEM I

Web Technology

310252

CO1

Implement and analyze behavior of web pages using HTML and CSS

CO2

Apply the client side technologies for web development

CO3

Analyze the concepts of Servlet and JSP

CO4

Analyze the Web services and frameworks

CO5

Apply the server side technologies for web development

CO6

Create the effective web applications for business functionalities using latest web development platforms

 

 

 

 

 

 

 

 

 

 

 

  SEM I

 

 

 

 

 

 

 

 

 

 

Artificial Intelligence

 

 

 

 

 

 

 

 

 

 

 

317523

 

CO7

 

 

CO1

 

Create the Effective Mini Project

 

 

Identify and apply suitable Intelligent agents for various AI applications

CO2

Build smart system using different informed search / uninformed search or heuristic approaches

CO3

Identify knowledge associated and represent it by ontological engineering to plan a strategy to solve given problem

CO4

Apply the suitable algorithms to solve AI problems

 

 

CO5

Implement ideas underlying modern logical inference systems

 

 

CO6

Represent complex problems with expressive yet carefully constrained language of representation

SEM I

Human Computer Interface

317525

CO1

Design effective Human-Computer-Interfaces for all kinds of users

CO2

Apply and analyze the user-interface with respect to golden rules of interface

CO3

Analyze and evaluate the effectiveness of a user-interface design

CO4

Implement the interactive designs for feasible data search and retrieval

CO5

Analyze the scope of HCI in various paradigms like ubiquitous computing, virtual reality ,multi-media, World wide web related environments

CO6

Analyze and identify user models, user support, and stakeholder requirements of HCI systems

SEM II

Data Science

317529

CO1

Analyze needs and challenges for Data Science

CO2

Apply statistics for Data Analytics

CO3

Apply the lifecycle of Data analytics to real world problems

CO4

Implement Data Analytics using Python programming

CO5

 

Implement data visualization using visualization tools in Python programming

CO6

 

Design and implement Big Databases using the Hadoop ecosystem

SEM II

Cyber Security

317530

CO1

Gauge the security protections and limitations provided by today's technology.

CO2

Identify cyber security threats.

CO3

Analyze threats in order to protect or defend it in cyberspace from cyber-attacks.

 

CO4

 

Build appropriate security solutions against cyber-attacks

SEM II

Artificial Neural Network

317531

CO1

Understand the basic features of neural systems and be able to build the neural model.

CO2

Perform the training of neural networks using various learning rules.

CO3

Grasping the use of Associative learning Neural Network

CO4

Describe the concept of Competitive Neural Networks

CO5

Implement the concept of Convolutional Neural Networks and its models

CO6

Use a new tool /tools to solve a wide variety of real-world problems

SEM II

Cloud Computing

310254(C)

CO1

Understand the different Cloud Computing environment

CO2

Use appropriate data storage technique on Cloud, based on Cloud application

CO3

Analyze virtualization technology and install virtualization software

CO4

Develop and deploy applications on Cloud

CO5

Apply security in cloud applications

 

 

 

CO6

Use advance techniques in Cloud Computing