JNNCE | Jawaharlal Nehru National College of Engineering, Shivamogga

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

AI and ML is one of the most disruptive technologies impacting the future of every industry and mankind. AI driven technology has been instrumental in reinventing human lifestyle and demand for engineers trained in these technologies is rapidly growing. This program produces skilled engineers which could open the doors to an exciting career. In this program, we shall equip the students to build novel applications using technologies like Full Stack, Semantic web, Neural Networks, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision etc. Students will get good foundations of all AI and ML techniques and at the same time ample oppurtunity for developing projects and applications. Center of Excellences with reputed companies shall create industrial internships for students and make them industry ready

Dr. Chetan K R,
Professor and Head,
Dept. of AIML,
Contact No: 9900923050,
Email: hod_aiml@jnnce.ac.in

Vision

To be a premier center of excellence with research in artificial intelligence through unique interdisciplinary partnerships and positive contribution to the community, organizations and society as a whole.

Mission

To impart knowledge in cutting edge Artificial Intelligence technologies in par with industrial standards.
To collaborate with industry to uplift innovative research and development in Artificial Intelligence and Machine Learning and its allied fields to serve the needs of society.
To produce successful Computer Science and Engineering graduates with a specialization in AI/ML with personal and professional responsibilities and commitment to lifelong learning.

#	Program Educational Objectives : Graduates of the Program will :
PEO - 1	Develop and excel in their chosen profession on technical front and progress towards advanced continuing education or Inter-disciplinary Research and Entrepreneurship.
PEO - 2	Become a reputed innovative solution provider- to complex system problems or towards research or challenges relevant to Artificial Intelligence and Machine learning.
PEO - 3	Progress as skilled team members achieving leadership qualities with trust and professional ethics, proactive citizens for progress and overall welfare of the society.

#	Program Specific Outcomes : Engineering Graduates will be able to :
PSO - 1	The ability to understand, analyse and demonstrate the knowledge of human cognition, Artificial Intelligence, Machine Learning and data engineering in terms of real world problems to meet the challenges of the future.
PSO - 2	The ability to develop computational knowledge and project development skills using innovative tools and techniques to solve problems in the areas related to Deep Learning, Machine learning and Artificial Intelligence

#	Program Outcomes
PO - 1	Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
PO - 2	Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
PO - 3	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.
PO - 4	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.
PO - 5	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.
PO - 6	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.
PO - 7	Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
PO - 8	Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO - 9	Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO - 10	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.
PO - 11	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.
PO - 12	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.

The world is progressing towards new technology. The adaptation rate of new AI and ML technologies are high. Artificial intelligence (AI) hopes to produce some of this century’s most important and revolutionary inventions. The products of the new AI revolution are self-driven vehicles, robot assistance and digital disease diagnostics that will affect how we live and function. And as demand for qualified engineers has more than doubled in recent years, professionals who want to take a lead in research and development in AI are providing endless opportunities. AI & ML engineering will produce an immense amount of career opportunities for the future.

Gartner’s study is expected to clear the way for up to 2.3 million job prospects in next 5 years. And, in the last three years, vacancies in artificial intelligence have duplicated. A related study from Indeed also shows that Machine Learning developers, software technologists, and data scientists play the most demanded role in artificial intelligence.

Here is the list of the possible job roles for AI and ML engineering from where they can elevate their knowledge, experience and art of living.

1. Data Scientist:

They focus on the collection, analysis, interpretation of the data for inferences and observations and the development of successful solutions for market issues. Machine learning and artificial intelligence are central components of data science where insight generating approaches are applied from both, regression, predictive analysis and more.

2. Machine Learning Engineer:

Machine learning engineers come with applications, language analysis, statistics, math and more. In the creation and management of self-operating applications that promote machine learning projects, engineers are involved. The requisite technology stacks are Python, R, Scala and Java. The companies are always in demand and their job is rarely empty. They are involved in the fields of identification and speech acknowledgement, theft detection, client insight and risk control. An engineer’s median wage is more than $1000.

3. Research Scientist:

Researchers are working on detailed studies into machine learning and computational intelligence systems. A research scientist’s salary is very high, and companies are recruiting individuals with a strong AI background. It is quite clear that in the next decade, the value of researchers won’t decrease.

4. Business Intelligence Developer:

The market acumen of the Business Intelligence Developer must be considered in addition to AI. They identify various market patterns by analysing large data sets. The work pays well, and the market for it isn ‘t going anywhere anytime soon.

5. Big data engineering:

A Big Data Engineer’s job is to build an environment that allows business processes to communicate effectively. The role is ideal for those who enjoy experimenting with modern technological tools. To develop a career in AI, you’ll need to learn programming languages like Python, R, and Java. Big data engineers would pay well like any other AI roles. It is self-evident that becoming a Big data engineer will help one advance in one career.

6. AI engineer:

AI engineers are problem solvers who create, test and implement various Artificial Intelligence models. Programming skills in languages such as Python, R, or C++ are required. Because of the increasing need for AI engineers, the pay scale is very good. Starting personal tasks is an excellent way to bring these talents to the test — and to learn new ones.

Don’t be intimidated if these criteria sound overwhelming at first. Artificial intelligence is a mansion with several spaces, and gaining the skills and specialisations needed to succeed will take time and maturity. Rather than anything, prospective careers would necessitate a desire to be interested and take risks.