Artificial Intelligence & Data Science

  • UG INTAKE

    60

  • DURATION

    4 Years

Bachelor of Technology in Artificial Intelligence and Data Science (AI & DS), is a new engineering program aiming to create experts in the domain of data science. It enables the students to acquire technical skills to perform data processing, analysis and visualization in multiple real-time applications. The courses studied in this branch relate with methodologies, processes, techniques and tools drawn from different domains of computing and information science to extract knowledge from structured and unstructured data.

The concepts studied in AI & DS cover the applications of mathematical concepts for data handling, study of various methods followed for data handling and analysis, applications of data analysis in the domain of artificial intelligence.

The knowledge acquired could be applied in designing the software systems facilitating intelligent decisions in business applications. It is a specialized branch that deals with the development of data-driven solutions, data visualization tools and techniques to analyze big data. It also incorporates the concepts of machine learning and deep learning model building for solving various computational and real-world problems.

Vision

Achieving excellence in engineering education by creating a dynamic learning environment, fostering collaboration and interdisciplinary research in Artificial Intelligence and Data science, and empowering our graduates to become leaders in the global AI landscape.


Mission

  • Creating an ecosystem of academic excellence by incorporating the best possible teaching-learning methodology, collaborative research and usage of modern IT infrastructure and tools.
  • Grooming professionals with ethical values and inculcate the ability to solve real-life problems that involves data analytics.
  • Contributing to the innovation of computing, AI system and Data Science to raise satisfaction level of all stakeholders.
  • Preparing professionals for employment in industry, research, higher education, community partnerships, and entrepreneurship to benefit the society.
  • To have a successful professional career with capabilities to build innovative solutions by applying the knowledge of Data Science and using technology as a tool to solve real-world problems.
  • To develop an ethical attitude and exhibit effective skills in communication, management, teamwork, and leadership to lead and work as a team in a professional environment.
  • To develop engineering, problem-solving, and critical thinking skills to create social, economic and sustainable impact and develop an ability to adapt themselves to the dynamically changing technologies catering to the organizational needs.

Engineering Graduates will be able to

  • PO1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  • PO2: Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
  • PO3: Design/development of solutions: 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.
  • PO4: Conduct investigations of complex problems: 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.
  • PO5: Modern tool usage: 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.
  • PO6: The engineer and society: 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.
  • PO7: Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
  • PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • PO9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • PO10: Communication: 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.
  • PO11: Project management and finance: Demonstrate knowledge and understanding of the 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.
  • PO12: Life-long learning: 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.
  • Apply the principles of artificial intelligence and data science to develop the systems that require data analysis, inference, perception, knowledge representation, and learning.
  • Obtain the competencies to excel in Employment, Higher studies and Research in Artificial Intelligence and Data Science while upholding ethical values.
  • Demonstrate proficient professional abilities for seamless collaboration within diverse and interdisciplinary teams, embracing a growth-oriented mindset.
  • SEMESTER 3
  • STATISTICS & PROBABILITY THEORY
  • DATA STRUCTURES
  • OBJECT ORIENTED PROGRAMMING
  • COMPUTER ORGANIZATION AND ARCHITECTURE
  • INTRODUCTION TO DATA SCIENCE
  • PRACTICING DATA SCIENCE WITH MS EXCEL AND PYTHON
  • ENHANCING SELF COMPETENCE
  • KANNADA (BALAKE / SAMSKRITHIKA)
  • ESSENCE OF INDIAN CULTURE
  • SEMESTER 4
  • LINEAR ALGEBRA, STATISTICAL ANALYSIS & COMPUTING
  • DESIGN AND ANALYSIS OF ALGORITHMS
  • MACHINE LEARNING
  • SOFTWARE ENGINEERING AND PROJECT MANAGEMENT
  • DATABASE MANAGEMENT SYSTEMS
  • DATA HANDLING AND VISUALIZATION WITH R
  • UNIVERSAL HUMAN VALUES
  • INNOVATIONS AND DESIGN THINKING
  • BUILDING RESPONSIVE AND ACCESSIBLE WEB INTERFACES
  • INTERNSHIP – I (ACTIVITY-BASED INTERNSHIP)
  • SEMESTER 5
  • CLOUD COMPUTING
  • PRINCIPLES OF ARTIFICIAL INTELLIGENCE
  • OPERATING SYSTEM
  • DATABASE MANAGEMENT SYSTEMS LAB
  • PROFESSIONAL ELECTIVE-I
  • INTRODUCTION TO IPR
  • C++ AND UNIX PROGRAMMING
  • RESEARCH METHODOLOGY
  • SOCIAL CONNECT & RESPONSIBILITY
  • EMPLOYABILITY SKILL DEVELOPMENT
  • SEMESTER 6
  • COMPUTER NETWORKS
  • BIG DATA ANALYTICS
  • FULL STACK DEVELOPMENT
  • PROFESSIONAL ELECTIVE - II
  • PROFESSIONAL ELECTIVE -III
  • OPEN ELECTIVE –I
  • MANAGEMENT & ENTREPRENEURSHIP
  • EMPLOYABILITY SKILL DEVELOPMENT- II
  • SEMESTER 7
  • DATA PRIVACY AND INTERNET SECURITY
  • PRACTICE OF A MODERN TOOL FOR DATA SCIENCE
  • PROFESSIONAL ELECTIVE -IV
  • PROFESSIONAL ELECTIVE - V
  • OPEN ELECTIVE –II
  • FINANCIAL MANAGEMENT
  • INDIAN KNOWLEDGE SYSTEMS
  • MAJOR PROJECT PHASE I
  • SEMESTER 8
  • INTERNSHIP- II (SOCIETAL INTERNSHIP AND RESEARCH/INDUSTRY INTERNSHIP)
  • MAJOR PROJECT PHASE II
  • ELECTIVES - GROUP-I
  • IMAGE AND VIDEO ANALYTICS
  • KNOWLEDGE ENGINEERING
  • RECOMMENDER SYSTEMS
  • BUSINESS ANALYTICS
  • BUSINESS INTELLIGENCE
  • COGNITIVE SCIENCE
  • DATA WRANGLING
  • HIGH-DIMENSIONAL DATA ANALYSIS
  • NATURAL LANGUAGE PROCESSING
  • NEURAL NETWORKS AND DEEP LEARNING
  • SOCIAL WEB ANALYTICS
  • SOFT COMPUTING
  • STATISTICAL INFERENCE FOR DATA SCIENCE
  • STREAM PROCESSING
  • TEXT AND SPEECH ANALYSIS
  • TIME SERIES ANALYSIS
  • ELECTIVES - GROUP-II
  • AUGMENTED AND VIRTUAL REALITY
  • MULTIMEDIA DATA COMPRESSION AND STORAGE
  • OPERATIONS RESEARCH
  • SAS PROGRAMMING
  • ADVANCED JAVA PROGRAMMING
  • MOBILE APP DEVELOPMENT
  • CRYPTOCURRENCY AND BLOCKCHAIN TECHNOLOGIES
  • CYBER SECURITY
  • ETHICS AND AI
  • INTELLIGENT DATABASE SYSTEM
  • INTERNET OF THINGS
  • OBJECT ORIENTED MODELING DESIGN
  • ROBOTIC PROCESS AUTOMATION
  • SOFTWARE TESTING AND AUTOMATION
  • STORAGE TECHNOLOGIES
  • SUPPLY CHAIN MANAGEMENT
  • UI AND UX DESIGN

For any information regarding the admissions,mail us at: info@nitte.edu.in

Faculty

Program

  • Duration - 4 years
  • Semester - 08
  • Intake - 60 Students

Department Activities

A Five-day faculty development program on ‘Data Science - Industry & Academia Perspective’ was organized by the Dept. of Artificial Intelligence & Data Science in association with the Internal Quality Assurance Cell (IQAC) & Nitte Engineering Education Unit (NEEU) from 13 to 17 March 2023. The FDP was inaugurated by Mr. Murali Iyer, Former Partner, Wipfli USA. In his inaugural address, Mr. Murali highlighted the importance of data and the need to analyse the data from the industrial perspective; he emphasized the importance of learning data science as an engineering curriculum. He enlightened the participants with his knowledge of working on projects related to data science and data analytics. He said that data science, artificial intelligence, and machine learning are to be taught to the students with the help of real-time examples.

Guest of Honour Mr. Sumanth Padival, Director & Head of India Operations Bengaluru, during his address, highlighted the need for real-time projects to understand the fundamental concepts. Mr. Sumanth also coordinated the team from Wifli to be the resource persons for this 5-day faculty development program.

Dr. Niranjan N Chiplunkar, Principal, NMAMIT, in his presedential remarks, highlighted the need of industry-academia collaboration in the engineering curriculum. He also emphasised that the faculty must be trained in handling subjects that are in line with industry requirements.

Dr. Venugopala P S, Head, Department of Artificial Intelligence and Data Science welcomed the gathering and presented an overview of the 5-day FDP. Mr. Prajwal Hegde introduced the guests. Ms. Ankita Shetty proposed the vote of thanks.

It may be recalled that NMAM Institute of Technology started a B.Tech program in Artificial Intelligence and Data Science under Nitte (Deemed to be University) from the Academic Year 2022-23. The Institute has academic collaboration with Wipfli India for curriculum development, internships, and placements. The FDP was organised with technical assistance from Wipfli India.

Topics like, Industrial implications of Data Science-Expectations from fresh graduates; R programming for data handling; Customer needs and development process of a DS project by applying engineering fundamentals; Data sources, Data Cleaning, Data modelling, and BI; Demo of an open-source tool for data cleaning and pre-processing; Components of a DS project, roles involved, knowledge expected, and the process followed; Web scraping and UI development; Applications of ML algorithms in real-time projects (Case studies); Data analytics with Excel / UI design; Statistics in application to DS; Python for Data Science- data pre-processing, and visualization libraries were covered during this five day FDP.

The events during the five days of the workshop are as follows -

Day 1

Mr. Murali Iyer, Former partner, Wipfli India, conducted a session on “Industrial implications of Data Science, Expectations from fresh graduates” providing an overview of data science in industry, benefits and challenges of using data science, skills and knowledge required to succeed in data science.

The second session was on “R programming for data handling - hands-on” by Dr. Anisha P R withhands-on exercises for data handling using R.

Day 2

The first session was conducted by Mr. Murali Iyer on “Customer needs and development process of a DS project by applying engineering fundamentals” where an overview of engineering fundamentals in data science, customer needs and requirements for a data science project, and development process for a data science project was discussed.

The next session was handled by Dr. Venugopala P S, on “Data sources, data cleaning, data modeling, and BI”addressing data sources for data science projects, Data cleaning, and pre-processing techniques, and Data modelling techniques.

Mr. Pranesh (Wipfli India), gave a Demo of an open-source tool for data cleaning and preprocessing in the last session.

Day 3

Mr. Santosh Shet & Mr.Praveen Subu (Wipfli India) delivered a detailed session on “Components of a DS project, roles involved, knowledge expected, and the process followed” facilitating the participants to understand the components, Roles and responsibilities of team members, Skills and knowledge expected from team members and Process followed for a data science project.

In the afternoon session Mr. Nabarun Chakravarthy & Mr. Chethan Pagaria (Wipfli India) given an overview on “Web scraping and UI development.”

Day 4

The first session on “ Applications of ML algorithms in real-time projects (Case studies)” Was handled by Mr. Santosh Shet & Mr.Praveen Subu (Wipfli India) with Case studies on real-time projects using machine learning algorithms.

In the second half Mr.Pranesh (Wipfli India), conducted a hands-on session on Data analytics with Excel / UI design.

Day 5

Mr. Shailesh M. S. , Encora Innovation Labs, deliverd a detailed presentation on how statistical concepts are used and applied in data science along with Hands-on exercises for data pre-processing and visualization using Python.

An interaction program with Mr. Murali Iyer, Former Partner, Wipfli USAwas organized for the students of the Department of AI & DS on 15th March 2023 from 1 pm to 2 pm at Shambhavi Seminar Hall.

During the interaction program, Mr. Murali highlighted the importance of data in the present-day world and the need to analyze the data from the industrial and business perspective; The data comes in various forms and from various sources, and he emphasized the importance of learning data science as an engineering curriculum in order to understand the process of handling the data. He enlightened the students with his knowledge of working on projects related to data science and data analytics. He believed data science, artificial intelligence, and machine learning are to be explored with the help of real-time examples. He informed the students to take up internships and work on real-time projects. He highlighted the importance of communication while working oncustomer-centered projects. Students are advised to develop communication skills during their course of study in college. The institutions will provide an ample number of opportunities to work as a team during projects and co-curricular activities. These activities are to be used to build leadership and communication skills. Technical competitions and hackathons are to be used as a platform to learn coding and project-building skills. Mr. Muraliinformed the students that a skilled person will always be in demand in the industry. Hence the students need to work for improving their technical and inter personals skills during the study of their engineering course. Students clarified their questions about the future of data science and possible career opportunities. Mr. Murali has explained the idea of career paths for the students. 65 students from the second semester of the AI&DS branch participated in the program.

Session Date: August 7, 2023 - August 11, 2023

Session Speakers:

Mr. Murali S Iyer, Professor of Practice, Department of AI & DS, NMAMIT, Nitte, Former partner, Wipfli

Mr. Sumanth Padival, Director and Head of India Operation, Wipfli India

Mr. Rajesh Suryanarayan, Business Analysst, Wipfli India

Mr. Pradhan Iyer, Custom Software Manager, Wipfli India

Mr. Raveesha, Head of Talent and Culture, Wipfli India

Branches (7th semester):

  • Artificial Intelligence and Machine Learning
  • Computer and Communication Engineering
  • Computer Science and Engineering
  • Electronics and Communications
  • Information Science and Engineering

Session Report: Team from Wipfli Inida had conducted sessions for the final year students to enable them for the placements. During the session, the speakers addressed the following key points.

Team Building: The session emphasized the significance of team dynamics and how to build strong working relationships among team members. Mr. Murali S Iyer highlighted the importance of understanding individual strengths and weaknesses to create a harmonious and efficient team.

Curiosity on the Project: Mr. Sumanth Padival discussed the role of curiosity in driving successful project outcomes. He encouraged participants to cultivate a curious mindset, fostering innovation and deeper problem-solving. Self-Accountability: Mr. Rajesh Suryanarayan focused on personal responsibility within a team setting. He underscored how individual accountability contributes to the collective success of the team and the project as a whole.

Teamwork: Mr. Pradhan Iyer explored the intricacies of effective teamwork, including active listening, conflict resolution, and leveraging diverse skills to achieve common goals.

Communication: Mr. Raveesha delved into the art of communication within teams. He provided insights on clear and transparent communication, promoting a collaborative and inclusive work environment.

Leadership: Throughout the sessions, the speakers collectively touched upon leadership qualities that empower team members to take initiative, guide others, and navigate challenges confidently.

Agile Methodology: An integral part of the sessions was dedicated to discussing the Agile methodology. The speakers elaborated on its iterative approach, adaptability, and its relevance in modern project management.

In the session, insights were provided by Dr. Venugopala P S, Professor and Head of AI & DS, regarding the current state of teamwork within the project. This encompassed equitable project distribution, student comprehension of project aspects, and the methodology of student collaboration in teamwork.

Mr. Bharath G Kumar, Head, the department of counselling, welfare, training and placement, elaborated on the positive and negative aspects that students may encounter during the placement process.

The above topics were repeated in each sessions, where each batch was consisting of 60 students.

The sessions were organized as per the following time table.

Date Time Branch Room No.
07 August 2023 11.00AM to 1.00PM ECE LH006, S Ramanujan Block
07 August 2023 9.00AM to 11.00AM ECE + AIML NC 32, SMV Block
08 August 2023 9.00AM to 11.00AM ECE LH002, S Ramanujan Block
08 August 2023 11.00AM to 1.00PM AIML+ CCM SMV52, SMV Block
08 August 2023 2.00PM to 4.00PM CSE LH104, S Ramanujan Block
09 August 2023 11.00AM to 1.00PM ISE NC 26, SMV Block
09 August 2023 11.00AM to 1.00PM ISE NC 26, SMV Block
09 August 2023 2.00PM to 4.00PM CSE LH108, S Ramanujan Block
10 August 2023 9.00AM to 11.00AM CSE + ISE ELH104, Atal Block
10 August 2023 11.00AM to 1.00PM ECE + ISE LH112, S Ramanujan Block
11 August 2023 9.00AM to 11.00PM CSE LH005, S Ramanujan Block
11 August 2023 11.00AM to 1.00PM ISE ELH001, Atal Block

The sessions were well-received by participants from various engineering branches, fostering a rich exchange of ideas and experiences. Attendees gained insights into practical techniques for enhancing team dynamics, effective communication, and project management strategies. The comprehensive coverage of topics ranging from individual accountability to larger project frameworks left participants with a well-rounded understanding of successful project execution. Overall, the sessions greatly contributed to the development of valuable skills required for future engineers and leaders in the ever-evolving landscape of technology and engineering.

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