Degree Program offered

B. E.  in Artificial Intelligence and Data Science

Program Duration

4 years

Year of Establishment

2020

Intake

180

Approved by

AICTE, New Delhi

Affiliated to

Savitribai Phule Pune University, Pune

Class: SE                                                  Discrete Mathematics

1

Formulate problems precisely, solve the problems, apply formal proof techniques, and explain the reasoning clearly.

2

Apply appropriate mathematical concepts and skills to solve problems in both familiar and unfamiliar situations including those in real-life contexts.

3

Design and analyze real world engineering problems by applying set theory, propositional logic and to construct proofs using mathematical induction.

4

Specify, manipulate and apply equivalence relations; construct and use functions and apply these concepts to solve new problems.

5

Calculate numbers of possible outcomes using permutations and combinations; to model and analyze computational processes using combinatorics.

6

Model and solve computing problem using tree and graph and solve problems using appropriate algorithms

7

Analyze the properties of binary operations, apply abstract algebra in coding theory and evaluate the algebraic structures.

Class: SE                      Fundamentals of Data Structures

1

Design the algorithms to solve the programming problems, identify appropriate algorithmic strategy for specific application, and analyze the time and space complexity.

2

Discriminate the usage of various structures, Design/Program/Implement the appropriate data structures; use them in implementations of abstract data types and Identity the appropriate data structure in approaching the problem solution.

3

Demonstrate use of sequential data structures- Array and Linked lists to store and process data.

4

Understand the computational efficiency of the principal algorithms for searching and sorting and choose the most efficient one for the application.

5

Compare and contrast different implementations of data structures (dynamic and static)

6

Understand, Implement and apply principles of data structures-stack and queue to solve computational problems.

Class: SE                                   Object Oriented Programming

1

Apply constructs- sequence, selection and iteration; classes and objects, inheritance, use of predefined classes from libraries while developing software.

2

Design object-oriented solutions for small systems involving multiple objects.

3

Use virtual and pure virtual function and complex programming situations.

4

Apply object-oriented software principles in problem solving.

5

Analyze the strengths of object-oriented programming.

6

Develop the application using object oriented programming language (C++).

7

Build object models and design software solutions using object-oriented principles and strategies

Class: SE                      Computer Graphics

1

Identify the basic terminologies of Computer Graphics and interpret the mathematical foundation of the concepts of computer graphics.

2

Apply mathematics to develop Computer programs for elementary graphic operations.

3

Illustrate the concepts of windowing and clipping and apply various algorithms to fill and clip polygons.

4

Understand and apply the core concepts of computer graphics, including transformation in two and three dimensions, viewing and projection.

5

Understand the concepts of color models, lighting, shading models and hidden surface elimination.

6

Create effective programs using concepts of curves, fractals, animation and gaming.

Class: SE                                                           Operating Systems

1

Enlist functions of OS and types of system calls

2

Implement basic C program

3

Apply process scheduling algorithms to solve a given problem

4

Illustrate deadlock prevention, avoidance and recovery

5

Explain memory management technique

6

Illustrate I/O and file management policies

7

Describe Linux process management

Class: SE                                                           Statistics

1

Identify the use of appropriate statistical terms to describe data.

2

Use appropriate statistical methods to collect, organize, display, and analyze relevant data.

3

Use distribution functions for random variables.

4

Distinguish between correlation coefficient and regression.

5

Understand tests for hypothesis and its significance.

Class: SE                                                    Internet of Things

1

Design a simple IoT system comprising sensors by analyzing the requirements of IoT Application.

2

Develop the skill set to build IoT systems and sensor interfacing.

3

Explain the concept of Internet of Things and identify the technologies that make up the internet of things.

4

Analyze trade-offs in interconnected wireless embedded device networks. Select Appropriate Protocols for IoT Solutions.

5

Have a thorough understanding of the structure, function and characteristics of computer systems and Understand the structure of various number systems and its application in digital design.

Class: SE                                  Data Structures and Algorithms

1

Identify and articulate the complexity goals and benefits of a good hashing scheme for real- world applications.

2

Apply non-linear data structures for solving problems of various domain.

3

Design and specify the operations of a nonlinear-based abstract data type and implement them in a high-level programming language.

4

Analyze the algorithmic solutions for resource requirements and optimization.

5

Use efficient indexing methods and multiway search techniques to store and maintain data..

6

Use appropriate modern tools to understand and analyze the functionalities confined to the secondary storage.

Class: SE                                                      Software Engineering

1

Analyze software requirements and formulate design solution for a software.

2

Design applicable solutions in one or more application domains using software engineering approaches that integrate ethical, social, legal and economic concerns.

3

Apply new software models, techniques and technologies to bring out innovative and novelistic solutions for the growth of the society in all aspects and evolving into their continuous professional development.

4

Model and design User interface and component-level.

5

Identify and handle risk management and software configuration management.

6

Utilize knowledge of software testing approaches, approaches to verification and validation.

Class: SE                                                      Management Information System

1

To understand concepts of Management Information System and Business intelligence for MIS

2

To recognize the need of an information system in today’s global business with tools and technologies.

3

To identify IT infrastructure components and to study security in the Information System.

4

To understand the importance of project management and the international information system.

5

To understand the concepts of decision support systems for business applications.

6

To understand artificial intelligence and data science for Management Information System

Class: TE                                              Database Management Systems

1

Analyze and design Database Management System using ER model

2

Implement database queries using database languages

3

Normalize the database design using normal forms

4

Apply Transaction Management concepts in real-time situations

5

Use NoSQL databases for processing unstructured data

6

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

Class: TE                                              Computer Networks

1

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

2

Analyze the working of physical layer protocols.

3

Analyze the working of different routing protocols and mechanisms

4

Implement client-server applications using sockets

5

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

6

Summarize concepts of MAC and ethernet.

Class: TE                                              Web Technology

1

Implement and analyze behavior of web pages using HTML and CSS

2

Apply the client side technologies for web development

3

Analyze the concepts of Servlet and JSP

4

Analyze the Web services and frameworks

5

Apply the server side technologies for web development

6

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

Class: TE                                             EL - I : Pattern Recognition

1

Distinguish a variety of pattern recognition, classification, and combination techniques.

2

Apply statistical pattern recognition approaches in a variety of problems.

3

Elaborate on different approaches of syntactic pattern recognition.

4

Differentiate graphical approach and grammatical inferences in syntactic pattern recognition.

5

Illustrate the artificial neural network-based pattern recognition

6

Apply unsupervised learning in pattern recognition.

Class: TE                                          EL - I : Human Computer Interface

1

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

2

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

3

Analyze and evaluate the effectiveness of a user-interface design

4

Implement the interactive designs for feasible data search and retrieval

5

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

6

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

Class: TE                                              Data Science

1

To understand the need of Data Science

2

To understand computational statistics in Data Science

3

To study and understand the different technologies used for Data processing

4

To understand and apply data modeling strategies

5

To learn Data Analytics using Python programming

6

To be conversant with advances in analytics 

Class: TE                                  Cyber Security

1

To understand threats/vulnerabilities to networks and countermeasures.

2

To provide understanding of cryptography and its applications.

3

To explain various approaches to Encryption techniques

4

Implement the interactive designs for feasible data search and retrieval

5

To understand working of firewall and IDs

Class: TE                              Artificial Neural Network

1

To provide students with a basic understanding of the fundamentals and applications of artificial neural networks

2

To identify the learning algorithms and to know the issues of various feed forward and feedback neural networks.

3

To Understand the basic concepts of Associative Learning and pattern classification.

4

To solve real world problems using the concept of Artificial Neural Networks

5

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

6

Analyze and identify user models, user support, and stakeholder requirements

Class: TE                             EL-II   Cloud Computing

1

To study fundamental concepts of cloud computing

2

To learn various data storage methods on cloud.

3

To understand the implementation of Virtualization in Cloud Computing

4

To learn the application and security on cloud computing

5

To study risk management in cloud computing

6

To understand the advanced technologies in cloud computing

Class: TE                             EL-II : Natural Language Processing

1

To understand the basic concepts of Natural Language Processing (NLP)

2

To understand use of morphological aspect in NLP

3

To learn and implement syntax parsing techniques

4

To learn and implement semantics parsing techniques

5

To learn and implement Machine Translation techniques

6

To design and develop different application using NLP

Class: BE                                              Machine Learning

1

To get acquainted with the principles of quantum computing and the usage of Linear algebra in Quantum Computing

2

To understand the Architecture of Quantum computing and solve examples of Quantum Fourier Transforms

3

To understand the concepts of basic and advanced Quantum Algorithms and apply them to various problems

4

To study quantum machine learning and apply these to develop hybrid solutions

5

To study the Quantum Theory with Fault-Tolerant Quantum techniques

6

To understand Problem-Solving using various peculiar search strategies for AI  

Class: BE                              Data Modeling and Visualization

1

Creating an emerging data model for the data to be stored in a database

2

Conceptualized representation of Data objects

3

Create associations between different data objects, and the rules

4

Organize data description, data semantics, and consistency constraints of data

5

Identifying data trends

6

Incorporate data visualization tools and reap transformative benefits in their critical areas of operations

Class: BE                         EL-IV :   Quantum Artificial Intelligence

1

To get acquainted with the principles of quantum computing and the usage of Linear algebra in Quantum Computing

2

To understand the Architecture of Quantum computing and solve examples of Quantum Fourier Transforms

3

To understand the concepts of basic and advanced Quantum Algorithms and apply them to various problems.

4

To study quantum machine learning and apply these to develop hybrid solutions

5

To study the Quantum Theory with Fault-Tolerant Quantum techniques

6

To understand Problem-Solving using various peculiar search strategies for AI

Class: BE                                             EL - III : Information Retrieval

1

To understand the basics of Information Retrieval

2

To understand the concepts of Indexing & Query Processing for Information Retrieval .

3

To provide comprehensive details about various Evaluation methods

4

To understand the different methods of Text Classification and Clustering .

5

To understand various search engine system operations and web structures

6

To understand various applications of Information Retrieval

Class: BE                                          EL - III : Enterprise Architecture and Components

1

To understand the concept of the enterprise information architecture

2

To understand different Enterprise architecture frameworks

3

To develop skills in designing and implementing enterprise architectures

4

To discuss component model and Discuss the operational characteristics of the EIA Reference Architecture

5

To describe the strategy for Metadata Management within information-centric use case scenarios

6

To Analyze tools of Enterprise Architecture in Modern Organizations

Class: BE                                          EL - IV : UI/UX Design

1

To learn the factors that determine how people use technology

2

To study the usable software-enabled user-interfaces

3

To achieve efficient, effective, and safe interaction

4

To Explore various models and factors that affect response time

5

To explore the challenges associated with information visualization and its societal and individual impacts.

6

To learn Usability evaluation methods

Class: BE                                              Computational Intelligence

1

To provide students with a comprehensive understanding of the fundamental concepts, theories, and techniques in the field of computational intelligence

2

To understand, explain, and apply the fuzzy set and fuzzy logic in real life application

3

To familiarize with various evolutionary algorithms and optimization techniques inspired by natural evolution processes

4

To understand the principles, techniques, and applications of genetic algorithm

5

To apply computational intelligence techniques to solve complex NLP problems

6

To introduce the concepts inspired by the human immune system and their application in problem-solving and optimization

Class: BE                           Distributed Computing

1

To understand the fundamentals and knowledge of the architectures of distributed systems

2

To gain knowledge of working components and fault tolerance of distributed systems

3

To make students aware about security issues and protection mechanisms for distributed environments

4

Implement the interactive designs for feasible data search and retrieval

5

To understand working of firewall and IDs

6

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

Class: BE                             EL-V : Deep Learning

1

To understand the basics of neural networks

2

Comparing different deep learning models

3

To understand the Recurrent and Recursive nets in Deep Learning

4

To understand the basics of deep reinforcement learning models

5

To analyze Types of Networks

6

To Describe Reinforcement Learning

Class: BE                             EL-V   Big Data Analytics

1

To introduce students to basic concepts, terms, applications of big data

2

To apprehend Advanced Analytical Methods in Data Science

3

To acquaint with the tools like Hadoop, NoSQL, MapReduce which are required to manage and analyze big data

4

To program various issues related to Industry standards using Big Data Analytics

5

To visualize Big Data using different tools

Class: BE                             EL-VI : Business Intelligence

1

To Gain knowledge of the basic concepts of BI, principles, and components of BI, including data warehousing, data mining, analytics, and reporting

2

To learn techniques for data visualization and reporting to facilitate effective decision making

3

To explain different data pre-processing techniques

4

To Explore emerging trends and machine learning models in Business Intelligence

5

To understand the BI Applications in various industries

Class: BE                             EL-VI : Reinforcement Learning

1

To provide students with a basic understanding of RL and its connection with other related field.

2

Familiarize with five main components of reinforcement learning.

3

To make optimal decisions for dynamic systems using Markov decision process

4

To solve real world problems using the concept of Reinforcement Learning

5

To understand the BI Applications in various industries

Sr. No.

Name of Faculty Member

Designation

1

Dilip Bhonde (Vice President –Productivity and Quality Capgemini)

Industry Experts

2

Piyush Nikam (Data Scientist II Swiggy India)

3

Dr. Prashant Kumbharkar(Professor, Dean Planning and Ddevelopment, RSCOE Pune)

External Academicians

4

Dr. Sachin Babar (BOS member (Computer Engineering) SPPU, Professor & Head, SIT Lonavala)

5

Dr. Vinayak Kottawar (Associate Professor & Head- Department of AI & DS)

Department faculty representatives  

6

Mrs. Manasi Dnyanesh Karajgar (Assistant Professor, PAQIC Member)

7

Dr. Bhagyashree Tingare(Assistant Professor, PAQIC Member)

8

Mr. Pratik Chopade(Assistant Professor, Program Coordinator

9

Arya Gaikawad

Student representative  (Third year -AI & DS)

10

Shrawan Saproo

Student representative (Second Year- AI & DS)

Sr. No.

Name of Faculty Member

1

Dr. Vinayak Kottawar

2

Mrs. Manasi Dnyanesh Karajgar

3

Dr. Bhagyashree Tingare

4

Mr. Pratik Chopade

5

Prof. Pranjali Sameer Bahalkar