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.
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 -
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.
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.
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.”
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.
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.