About the Course


Degree Program offered

B. E.  in Artificial Intelligence and Data Science

Program Duration

4 years

Year of Establishment




Approved by

AICTE, New Delhi

Affiliated to

Savitribai Phule Pune University, Pune


DEPARTMENT INFORMATION                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  

When we hear the word “Artificial Intelligence”, digital assistants, chatbots, robots, and self- driving cars is what strikes our mind. These are some real examples of artificial intelligence, powerful and interesting. Unlike other technologies, we will continue to see the advancements of AI and Data science.

India is rising and shining bright when it comes to adopting new and emerging technologies. Enterprises from almost all major industry verticals are hiring AI and data science experts to help them garner actionable insights from big data. The analytics sector has witnessed a sharp increase in demand for highly-skilled professionals who understand both the business world as well as the tech world. Organizations today are on a constant lookout for such professionals who can fill this ever-growing dearth in talent.


Career Prospects

AI and Data Science domain is considered one of the most lucrative jobs in the industry right now. With numerous openings spanning across all sectors, data science jobs are showing only the signs of growth.

According to Gartner, AI is heralded to create 2.3 million jobs by the end of Year, leading a net gain of 500,000 potentially new jobs. And in the light of COVID-19 crisis, job opportunities for AI workers are bound to see a sharp rise.


The global economic status is not the same, but AI talents can remain positive. 

  • According to International Data Corporation (IDC), the number of AI jobs is expected to globally grow 16 percent this
  • Gartner‟s report also mentions 85 percent of AI professionals believe the industry has become more diversified in recent 

Stating that organizations across all sectors have started to embrace AI and ML, it is evident that professionals skilled in these technologies will be in huge demand beyond 2020.


2020 is indeed an open door for professionals who are already engaged in AI. 

  • Gartner says, about 30 percent of all the B2B companies will be employing AI to boost at least one of their sales 
  • According to Demand base, 80 percent of B2B marketing executives proclaimed AI will revolutionize the marketing industry by the end of 2022 
  • IDC predicts 75 percent of commercial apps will use AI by


Roles and Job Descriptions

Data Scientist: A Data Scientist will be responsible for modeling complex problems, discovering insights and identifying opportunities through the use of statistical, machine learning, algorithmic, data mining, and visualization techniques. The person will need to collaborate effectively with internal stakeholders and cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. As a data scientist, you might be asked to assess how a change in marketing strategy could affect your company‟s bottom line. 

Machine Learning Engineer: Research new data approaches and algorithms to be used in adaptive systems including supervised, unsupervised, and deep learning techniques. Machine learning engineers often go by titles like Research Scientist or Research Engineer. 

Data Analyst: Data analysts sift through data and provide reports and visualizations to explain what insights the data is hiding. Transform and manipulate large data sets to suit the desired analysis for companies. 

Statistician: „Statistician‟  is  what  data  scientists  were  called  before  the  term  „data  scientist‟ existed. At a high level, statisticians are professionals who apply statistical methods and models to real-world problems. They gather, analyze, and interpret data to aid in many business decision-making processes. Statisticians are valuable employees in a range of industries, and often seek roles in areas such as business, health and medicine, government, physical sciences, and environmental sciences.

Data Architect: A Data Architect ensures data solutions are built for performance and design analytics applications for multiple platforms. In addition to creating new database systems, data architects often find ways to improve the performance and functionality of existing systems, as well as working to provide access to database administrators and analysts. 

Business Intelligence Developer: Business intelligence (BI) is a set of technologies and practices for transforming business information into actionable reports and visualizations. A business intelligence developer is an engineer that‟s in charge of developing, deploying, and  maintaining BI interfaces. 

Enterprise Architect: An enterprise architect is responsible for aligning an organization‟s strategy with the technology needed to execute its objectives. Enterprise architects are key in establishing an organization‟s IT infrastructure and maintaining and updating IT hardware, software, and services to ensure it supports established enterprise goals. 

Big Data Engineer/Data Engineer: A Big Data Engineer is a person who creates and manages a company‟s Big Data infrastructure and tools, and is someone that knows how to get results from vast amounts of data quickly.


Tools and Skills 



Statistics & Mathematics

Descriptive Statistics, Inferential Statistics, Linear Algebra, Differential Calculus, Discrete Mathematics

Programming in R/Python

Getting Data In/Out, Managing Data frames, Loop Functions, Regular Expressions, Control Structures, Implementing

Machine Learning algorithms

Big Data

Hadoop Ecosystem(Hive, Pig, Sqoop, Flume), Big Data Lakes,

No SQL, Apache Spark, Spark MLLib

Business Intelligence

SQL, Microsoft Power BI, SAP BI, Tableau, Oracle Fusion

Machine Learning

ScikitLearn: Regression, Classification, Segmentation, Feature

Engineering, Dimensionality Reduction, Training and Deploying Models

Advanced Machine Learning(Deep Learning)

TensorFlow, Keras, Artificial Neural Networks, Deep NeuralNets, Convolution Neural Networks, Auto encoders,

Reinforcement Learning


The top companies make use of AI and Data Science

  • Amazon
  • Apple
  • Google
  • Facebook
  • DJI
  • Deepmind
  • Casetext
  • DataVisor and many mo


Applications of AI 

  • Healthcare: Proper diagnosis and treatment are facilitated by introducing AI in
  • Education: A suitable learning environment is furnished to the students by utilizing
  • Sports: With advanced AI technologies, athletes can expand their
  • Agriculture: Maximum yield is possible by AI as it helps in developing the perfect farming environment.
  • Construction: Buildings can be constructed more safely and efficiently by the incorporation of AI.
  • Banking: Chat-bot assistance, fraud detection, and enhanced payment methods are some of the positive outcomes of
  • Marketing: The sales target can be effectively achieved by making use of predictive intelligence along with machine
  • E-commerce: Effective warehouse operations, good product recommendations, and fraud prevention are some of the fruits of


AI and Data Science in D. Y. Patil College of Engineering, Akurdi 

  1. Strong Industry Collaborations, Technical Workshops, Events, Training through Industry experts.
  2. Center of Excellence in AI in collaboration with Industry
  3. Best in class infrastructural
  4. Specialized lab in AI, ML and Data
  5. Strong placement
  6. Teacher Guardian system for student mentoring and personalize
  7. Employability enhancement course for all around
  8. Exposure for project based learning, Support and Encouragement for Industrial Internship.
  9. Strong Support for Innovation, product development and



Strength at DYPCOE:

  • DYPCOE has TWO state of art infrastructure for Data Science Centre of Excellence in the Department of Information Technology and AI and Cloud Centre of Excellence in association with ESDS, Nashik in the Department of Computer Engineering.
  • These Centres of Excellence has a team of faculty members certified in Data Science from IBM and in Artificial Intelligence Technologies.
  • Students from the Departments of Computer Engineering and Information Technology are currently getting skilled up under these Centres of Excellence on various concepts of Artificial Intelligence and Data Science.



Developing highly skilled and competent IT professional for sustainable growth in the field of Artificial Intelligence and Data science 


  1. To empower students for developing intelligent systems and innovative products for societal problems.
  2. To build strong foundation in Data computation, Intelligent Systems that enables self-development entrepreneurship and Intellectual property.
  3. To develop competent and skilled IT professional by imparting global skills and technologies for serving society. 


Course Structure


Course Structure of Artificial Intelligence and Data Science is as attached below:

AIDS Structure



Course Outcome for Semester I:

Sr. No.

Subjects of Sem I

Class: SE                                   Discrete Mathematics


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


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


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


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


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


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


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

Class: SE                      Fundamentals of Data Structures


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


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.


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


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


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


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

Class: SE                                     Object Oriented Programming


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


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


Use virtual and pure virtual function and complex programming situations.


Apply object-oriented software principles in problem solving.


Analyze the strengths of object-oriented programming.


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


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

Class: SE                                          Computer Graphics


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


Apply mathematics to develop Computer programs for elementary graphic operations.


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


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


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


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

Class: SE                                               Operating Systems


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


Identify the use of appropriate statistical terms to describe data.


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


Use distribution functions for random variables.


Distinguish between correlation coefficient and regression.


Understand tests for hypothesis and its significance.

Class: SE                                         Internet of Things


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


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


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


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


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


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


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


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


Analyze the algorithmic solutions for resource requirements and optimization.


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


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

Class: SE                                        Data Structures and Algorithms


Analyze software requirements and formulate design solution for a software.


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


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.


Model and design User interface and component-level.


Identify and handle risk management and software configuration management.


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


Graduate Attributes and Program Outcomes

Graduate Attributes

Program Outcomes

1. Engineering Knowledge

a. Apply the knowledge of mathematics, science, Engineering fundamentals, and an Engineering specialization to the solution of complex Engineering problems.

2. Problem Analysis

b. Identify, formulate, review research literature and analyze complex Engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences and Engineering sciences.

3. Design & Development of Solutions

c. Design solutions for complex Engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and Environmental considerations.

4. Conduct Investigations of Complex Problems

d. Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

5. Modern Tools Usage

e. 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. The Engineer and Society

f. 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 practices.

7. Environment & Sustainability

g. Understand the impact of the professional Engineering solutions in societal and Environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

8. Ethics

h. Apply ethical principles and commit to professional ethics and responsibilities and norms of Engineering practice.

9. Individual & Team work

i. Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

10. Communication Skills

j. Communicate effectively on complex Engineering activities with the Engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

11. Lifelong Learning

k. Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

12. Project management & Finance

l. An ability to Demonstrate knowledge and understanding of Engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary Environments.



Programme Educational Objectives

1. To prepare globally competent graduates having strong fundamentals and domain knowledge to provide effective solutions for engineering problems.

2. To prepare the graduates to work as a committed professional with strong professional ethics and values, sense of responsibilities, understanding of legal, safety, health, societal, cultural and environmental issues.

3. To prepare committed and motivated graduates with research attitude, lifelong learning, investigative approach, and multidisciplinary thinking.

4. To prepare the graduates with strong managerial and communication skills to work effectively as individual as well as in teams.


Program Specific Outcomes

1. Professional Skills: The ability to understand, analyze and develop computer programs in the areas related to algorithms, system software’s, multimedia web design networking and artificial intelligence for efficient design of computer based systems for varying complexity.

2. Problem solving skills: The ability to apply standard practices and strategies in software project development using open ended programming environment to deliver a quality product for business success.

3 Successful career and Entrepreneurship: The ability to employ modern computer languages, environments and platforms in creating innovative career paths to be entrepreneur and to have zest for higher studies.</p

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