Department of Computer Science & Engineering (Artificial Intelligence and Machine Learning)
The Emerging Field of AI and ML EngineeringArtificial Intelligence (AI) and Machine Learning (ML) engineering represent a cutting-edge branch of engineering focused on the creation, design, development, and support of intelligent systems.
This discipline encompasses a wide range of topics and tasks throughout the lifecycle of AI applications, requiring engineers to be well-versed in best practices and the unique needs of their organizations.As more digital leaders recognize the transformative potential of AI and ML, this field is becoming increasingly vital to business operations. It's essential for vendors, IT professionals, and even non-IT departments to understand how AI and ML are influencing nearly every aspect of daily business activities. AI and ML engineers are invaluable because they develop systems that didn't previously exist, pushing the boundaries of what's possible.
The unique blend of creativity and science defines AI and ML engineering. Engineers must envision the end product and work methodically to bring it to life. Meeting user requirements through innovative software solutions is a key driver in this field. Investing in AI and ML engineering now promises substantial long-term benefits, including numerous exciting career opportunities across various industries.By pursuing a BTech in AI and ML, students can position themselves at the forefront of technological innovation, ready to contribute to and lead the development of intelligent systems that will shape the future.
Email – hodaiml@mitaoe.ac.in
A future-focused academic environment that empowers students through inclusive education, responsible innovation, and a commitment to driving societal progress professional engineers, to cater to the changing needs of techno-society.
- Innovation & Research: To advance AI through quality education and research, foster innovation, and prepare ethical, industry-ready professionals to solve real-world challenges.
- Academia-Industry Collaboration: To empower students with industry-relevant AI skills through industry collaboration.
- Ethical Solutions: To Develop ethical and transformative AI solutions for the betterment of global society.
- Calculus and Differential Equations
- Science of Nature
- Foundations of Computing
- Applied Mechanics
- Design Thinking
- Data Driven Modeling
- Liberal Learning
- Indian Knowledge System (Vedic Mathematics)
- Statistics and Integral Calculus
- Engineering Physics
- Electrical and Electronics Engineering
- Essentials of Data Science
- Data Visualization/li>
- Discrete Structure
- Communication Skills (English/ German/Japanese/French)
- Creative Technologies
- Data Structures & Algorithms
- Artificial Intelligence
- Operating System
- Problem Solving Using OOP(C++)
- Problem Solving Using OOP (Java)
- Universal Human Values-II
- Applied Mathematics
- Open Elective Course
- Prototyping
- Project Design
- Database Management System
- Machine Learning
- Computer Network
- Discipline Skill Develop. Course - Core Java
- Discipline Skill Develop. Course - Advance Java
- Multi-Disciplinary Minor Course-I
- Environmental Science
- Entrepreneurship Skills
- Project Implementation
- Internship (Life And Soft Skills)
- Indian Constitution
- Design and Analysis of Algorithms
- Deep Learning
- Program Elective Courses
- Python Automation
- Full Stack Development
- Mobile Application Development
- UI/UX Design
- Multi-Disciplinary Minor Course-II
- Major Project – I
- Internship (Technical)
- Computational Linguistics and Compiler Theory
- Generative AI
- Program Elective Courses
- Automation Testing
- Agentic AI
- Robotic Process Automation
- Multi-Disciplinary Minor Course-III
- Employability and Career Development
- Major Project - II
- System Design
- Program Elective Courses
- MLOPs for AI Practitioner
- Multi-Disciplinary Minor Course-IV
- Project Management
- Major Project – III
- Research Methodology
- Summer Internship (Technical)
- Cyber Security
- Program Elective Course
- Swayam Course (PEC)
- Multi-Disciplinary Minor Course-V
- Swayam Course (MDM)
- Professional Certification Course
- Semester-Long Internship
- Semester Exchange
- Capstone Portfolio
- AI Engineer
- Machine Learning Specialist
- Data Analyst
- Deep Learning Engineer
- Computer Vision Specialist
- Robotics Engineer
- Cloud AI Architect
- Healthcare AI Specialist
- Financial Analyst with AI Expertise
- E-commerce Optimization Engineer
- Launch Your AI Startup
- Innovate Solutions to Global Challenges
Students gain industrial exposure through various internship programs which are as follow:
Summer Internship Program (SIP): Students compulsorily need to undergo SIP after completing their semester VI.
Semester Long Internship Program (SLIP): Selected students undergo SLIP during their semester VIII.
During these internship programs, students are getting internships in renowned industries like industries like Schlumberger India Technology Centre Pvt. Ltd. Tridiagonal solutions Pvt. Ltd. Equinox Software and Services Pvt. Ltd. Anukoolan Solutions Pvt. Ltd. SteepGraph Systems Pvt. Ltd. Genrich Membranes Pvt. Ltd. Henkel Adhesives India Pvt. Ltd. Cognizant Technology Solutions, FluiDimensions Pune, BDB India Pvt. Ltd. etc.
Artificial intelligence evokes images of supercomputer assistants, machines that can think creatively, and, to some, scenes from their favorite sci-fi movie. The reality, despite not being as futuristic, is not far off from this. AI refers to the ability of a computer or machine to mimic the competencies of the human mind, which often learns from previous experiences to understand and respond to
Artificial intelligence evokes images of supercomputer assistants, machines that can think creatively, and, to some, scenes from their favorite sci-fi movie. The reality, despite not being as futuristic, is not far off from this. AI refers to the ability of a computer or machine to mimic the competencies of the human mind, which often learns from previous experiences to understand and respond to language, decisions, and problems. The market for AI technologies is vast, amounting to around 200 billion U.S. dollars in 2023 and is expected to grow well beyond that to over 1.8 trillion U.S. dollars by 2030.
AI comes in many forms
AI is broadly divided into machine learning and deep learning. These then have further subcategories such as natural language processing, computer vision, robotics, and more. Machine learning constitutes the most basic and simple AI form. Programs operating on machine learning are given a very clear set of parameters to use in interactions with humans and are limited in scope. It is also the most common form of AI, used in basic chat assistants, apps, voice commands, and other limited engagements.Deep learning is closer to what a person would imagine from AI. In deep learning programs, AI has initial parameters and datasets but can integrate user information as it interacts with humans. In this way, the AI learns as it is used, becoming more sophisticated in the process. Recent examples of advanced deep learning programs are OpenAI’s ChatGPT and Google’s Bard.
Generative AI has entered the field
A new trend in AI development surged into the limelight at the end of 2022 in the form of generative AI. Although not being strictly new, with such programs already appearing over the last five years, advancement in this field have been staggering. Generative AI refers to programs that can, as the name suggests, generate text, images, music, and more. Driven by the release of ChatGPT-3 in late 2022, the field has drawn in Google, Microsoft, Amazon, and recently, Elon Musk’s X as well. All are competing in the development of the most advanced generative AI through a variety of startup companies. The advancement in this case is not without its flaws as generative AI companies have been accused of training their AI models on copyrighted texts and images, snubbing writers and artists.
The AI train steams ahead
With the advancements in deep learning and machine learning, coupled with the immense effect such programs may have on the global economy, it is to be expected that AI will be in continuous competitive development in all advanced economies. Any company looking to leverage an advantage on its competitors would do well to engage early so as not to be left behind.
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