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Artificial Intelligence & Machine Learning Engineering

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Department of Artificial Intelligence & Machine Learning engineering

Machine learning (ML) is a subfield of AI that deals with creating algorithms that can learn from data and make predictions based on that data. This allows them to make decisions based on what they've seen before, rather than being given explicit instructions on what to do. This programme discusses AI and Machine Learning methods based in different fields, including neural networks, machine Intelligence, Deep Learning, Devops, Cyber security, Natural language processing and data mining etc, in order to present a unified treatment of machine learning problems and solutions.

The scope and significance of AI and ML are enormous. They have the ability to change our lives in ways we can't even imagine right now.

The biggest difference between these two technologies is that artificial intelligence involves programming machines so that they can think like humans do, while machine learning does not require programming; instead, it uses algorithms to analyze data and make predictions based on those analyses. Both AI and ML are great at making decisions quickly and accurately, which means they're perfect for everything from medicine (diagnosing diseases) to finance (making stock predictions).

Ultimately, the goal is to develop an AI or ML system that's as close as possible to being human-like in its abilities: being able to understand context, convey emotion, etc. And although there's still a long way to go before achieving this goal (and it might never actually be reached!), these technologies are already having a huge impact on our lives today -- especially when it comes to making our lives easier!

VISION

To develop globally competent and ethical professionals in the field of Artificial Intelligence and Machine Learning for noteworthy contribution in research, innovation and sustainable development.

Mission

Impart rigorous training to generate knowledge through the hands on experience on latest tools and technologies in Artificial Intelligence and Machine Learning.

Inculcate problem solving and team building skills and promote lifelong learning with a sense of societal and ethical responsibilities.

Mould students to be technically competent through innovation and leadership with collaboration of industry experts.

Provide a conducive environment for faculty to engage in and train students in progressive and convergent research themes by establishing Centre of Excellence.

Program Outcomes (POs)

Students are expected to know and be able to
PO1 Engineering knowledge An ability to apply knowledge of mathematics, computing, science, engineering and technology.
PO2 Problem analysis An ability to define a problem and provide a systematic solution with the help of conducting experiments, analyzing the problem and interpreting the data.
PO3 Design/Development of Solutions An ability to design, implement, and evaluate a software or a software/hardware system, component, or process to meet desired needs within realistic constraints.
PO4 Conduct Investigation of Complex Problems An ability to identify, formulates, and provides systematic solutions to complex engineering/Technology problems.
PO5 Modern Tool Usage Modern Tool Usage An ability to use the techniques, skills, and modern engineering technology tools, standard processes necessary for practice as an IT professional.
PO6 The Engineer and Society An ability to apply mathematical foundations, algorithmic principles, and computer science theory in the modelling and design of computer-based systems with necessary constraints and assumptions.
PO7 Environment and Sustainability An ability to analyze and provide solution for the local and global impact of information technology on individuals, organizations and society.
PO8 Ethics An ability to understand professional, ethical, legal, security and social issues and responsibilities.
PO9 Individual and TeamWork An ability to function effectively as an individual or as a team member to accomplish a desired goal(s).
PO10 Communication Skills An ability to engage in life-long learning and continuing professional development to cope up with fast changes in the technologies/tools with the help of electives, professional organizations and extra- curricular activities.
PO11 Project Management and Finance An ability to communicate effectively in engineering community at large by means of effective presentations, report writing, paper publications, demonstrations.
PO12 Life-long Learning An ability to understand engineering, management, financial aspects, performance, optimizations and time complexity necessary for professional practice.

Program Specific Outcomes of AIML Engineering

PSO No. Program Specific Outcomes of AIML Engineering
PSO 1 An ability to apply the theoretical concepts and practical knowledge of Artificial Intelligence & Machine Learning in analysis, design, development and management of information processing systems and applications in the interdisciplinary domain. An ability to understand the computational fundamentals and computing resources.
PSO 2 An ability to analyze a problem, and identify and define the computing infrastructure and operations requirements appropriate to its solution. AI & ML graduates should be able to work on large-scale computing systems.
PSO 3 An understanding of professional, business and business processes, ethical, legal, security and social issues and responsibilities.
PSO 4 Practice communication and decision-making skills through the use of appropriate technology and be ready for professional responsibilities.

This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this course will introduce you to problem definition and data preparation in a machine learning project. By the end of the course, you will be able to clearly define a machine learning problem using two approaches. You will learn to survey available data resources and identify potential ML applications. You will learn to take a business need and turn it into a machine learning application. You will prepare data for effective machine learning applications.

The laboratory activities aim towards

Identify innovative research directions in Artificial Intelligence, Machine Learning and Big Data analytics.

Integrating and reasoning with information from disparate data sources.

Designing and implementing distributed systems for information exploitation, collaboration and decision making.

Data-intensive agent-based tools Providing quality education and practical skills to the students and faculty.

Assist in the development of partnerships with Industry regarding Internships, Summer Jobs, Publications and students’ Placements.

Establish, refine and implement strategies to take the idea in to students and faculty fraternity.

Create sustainable funding models for societal and ACE related efforts.

Encouraging students to publish research articles, patents and starting their start-ups in the campus.

Artificial Intelligence & Machine Learning Labs:

1. Artificial Intelligence Lab.

2. Deep learning Lab.

3. Data structures and Algorithms Lab.

4. Robotics Lab.

5. Advanced Machine Learning Lab.

Major Components Of AI & Ml Are:

Cognitive Abilities

Database

Hardware

Framework

Application Program Interfaces (APIs)

Few of the AI & ML applications (direct and indirect, partial list) are

Speech Recognition

Natural Language Generation

Machine Learning

Deep Learning

Robotic Process Automation

Cyborg Technology

Education

Healthcare

Businesses

Autonomous Vehicles

Finance and Economics

Video Games

Advertising

E-Commerce

Military

Computer Networks etc

Few of the major companies which needs AI & ML Engineers are : IBM, Amazon, Cognizant, Pivotchain Solutions, Airtel, Google, Dell, Tata Health, Honeywell International Inc., Siemens, Xilinx, Uber, Unisys, Tata AIG, Toyota, PTC Software, Acculogix, HCL, Tempus, DataRobot, CloudMinds, Nauto, OpenAI, Sift Science, SoundHound, Vicarious, VideoTap, Zoom etc.

Some of the major job profiles related to AI & ML are: Innovations Engineers, Machine Learning Engineers, Applied AI Engineers, Data Engineers, Text Programmer, Data Science Engineer, Data Scientist, AI ML Engineer, Head (Analytics) e-Commerce, Senior Developer Machine Learning, Data Modeler, Machine Learning Expert, and Artificial Intelligence Expert etc.

Prof. Kirti Randhe

HOD(Artificial Intelligence and Machine Learning)& Assistant Professor

ME(Comp), BE(Comp)

MESSAGE FROM HOD DESK

Welcome to the Department of Artificial Intelligence and Machine Learning at ISBM College of Engineering, Nande , Pune.

The department of Artificial Intelligence & Machine Learning (AI & ML) is established in the academic year 2020-2021. This is a 4-year degree course approved by AICTE, New Delhi under Savitribai Phule Pune University (SPPU). The Department has experienced faculty members/staff and the state of art research laboratories. The curriculum of AI & ML is prescribed by SPPU.

Artificial Intelligence and Machine Learning is the most flourishing discipline with advanced learning solutions imparting knowledge of advanced innovations. Artificial intelligence (AI) is the science and engineering of making intelligent machines, including intelligent computer programs. It is related to the concepts of computer science and cognitive science, but it can be considered as an autonomous field because it incorporates elements from all of these areas, plus many more. AI researchers typically try to create machines that are able to perform tasks that require human intelligence, such as visual recognition or natural language processing.

This specialization is designed to enable students to build intelligent machines, software, or applications with a cutting-edge combination of machine learning, analytics and visualization technologies. The main goal of artificial intelligence (AI) and machine learning (ML) is to program computers to use example data or experience to solve a given problem. Many successful applications based on machine learning exist already, including systems that analyze past sales data to predict customer behaviour (financial management), recognize faces or spoken speech, optimize robot behaviour so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data.

The Department emphasizes on all round development of the students, to make them competent engineers. The Department has well qualified and experienced faculty members and technically competent supporting staff. We motivate the students to achieve not only excellence in academics but also on their overall personality development.

Prof.Kirti Randhe
Assistant Professor and HOD, AI&ML Dept.
Experience : 9 Years
BE (CSE), ME (CE)
Dr. Reshma Sonar
Associate Professor
Experience : 20 Years
B.E (CSE), M. Tech (IT), PhD (CSE)
Prof. Darshana A. Bhamare
Assistant Professor
Experience : 9 years
M.E(Computer), Mumbai University
Prof. Prajkta A. Puranik
Assistant Professor
Experience : 9 Years
ME(CS) From UVCE COE, Bangalore University
Prof.Kailash Nath Tripathi
Assistant Professor
Experience : 17 years
B. Tech (CSE), M. Tech (CSE) PhD (Pursuing)
Mr. Nikhil D. Kumthekar
Assistant Professor
Experience : 8 Years
MCA
Mr. D. S. Sisodiya
Assistant Professor
Experience :12 Years
Mtech(CSE)
Prof.Sujata Jogdand
Assistant Professor
Experience : 9 Years
B. Tech (E&TC), , M. Tech (E&TC), MBA in BA pursuing
Ms Manisha Salunkhe
Technical Assistant
Experience : 2.5 Years
BE (CSE)

Second Year of Artificial Intelligence and Machine Learning Syllabus 2022

SE Computer

Course Outcome