Home » Department of CSE- ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

Department of CSE- ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

Vision:

A Center of excellence in education and research, providing quality learning through the integration of AI and ML, fostering innovation, collaboration between academia and global industry, and empowering women to drive societal advancement.

Mission:

To inculcate professional and personal growth with a strong academic and practical background in the area of artificial intelligence, with an emphasis on current trends in software development, making them industry-ready professionals with social ethics
To empower the students in attaining sound technical knowledge with necessitated trainings and certifications in the area of AI & ML.

About the Department

The B.Tech program in Computer Science and Engineering (Artificial Intelligence and Machine Learning) at Malla Reddy Engineering College for Women (Autonomous) was introduced under the New Age Programs in the academic year 2020–21 with an initial intake of 60 students. Due to its increasing demand and academic significance, the intake was enhanced to 180 in the academic year 2022–23 and further expanded to 300 from the academic year 2023–24 onwards.
The department is well-equipped with state-of-the-art infrastructure and advanced computing facilities, supported by high-speed internet and comprehensive wireless networks. This enables a highly conducive environment for learning, research, and innovation in the domains of Artificial Intelligence and Machine Learning.
In the B.Tech CSE (Artificial Intelligence and Machine Learning) program, students are introduced to essential concepts such as computational thinking, programming for problem-solving using Python, data structures, algorithms, and databases. The curriculum further covers advanced topics including artificial intelligence (search techniques and knowledge representation), machine learning, deep learning, and natural language processing.
Students gain in-depth knowledge by working on real-world problems across diverse application domains such as cognitive sciences, computer vision, speech processing, and natural language processing. The program also provides hands-on experience in key areas like machine learning, computer vision, speech technologies, data analytics, and other AI-driven domains. A wide range of professional electives is offered to help students specialize in their areas of interest and align with industry requirements.

DEPARTMENT GOALS

To provide a strong foundation in Computer Science, Artificial Intelligence, and Machine Learning principles.
To equip students with problem-solving skills, computational thinking, and programming expertise.
To promote innovation and research in emerging areas such as Machine Learning, Deep Learning, Computer Vision, and Natural Language Processing.
To develop the ability to design and implement intelligent systems for real-world applications.
To prepare students for successful careers in industry, academia, and entrepreneurship.
To encourage lifelong learning and adaptability to rapidly evolving technologies.
To foster ethical practices and social responsibility in the development and deployment of AI technologies.
To enhance collaboration with industry and research organizations for practical exposure and skill development.

CAREER OPPORTUNITIES AFTER COMPLETION OF THE COURSE

Artificial Intelligence Engineer – designing intelligent systems and automation solutions
Machine Learning Engineer – building predictive models and data-driven applications
Data Scientist – analyzing complex data to extract insights and support decision-making
Software Developer/Engineer – developing scalable applications using modern technologies
Deep Learning Engineer – working on neural networks for advanced AI applications
Computer Vision Engineer – developing image and video analysis systems
NLP Engineer – building language-based AI systems like chatbots and translators
Business Intelligence Analyst – transforming data into actionable business strategies
Robotics Engineer – integrating AI with robotics for automation and smart systems
Research Scientist – contributing to innovation in AI and emerging technologies

Programmable Educational Objectives - PEOs

PEO1 - Professional Enhancement

To gain familiar knowledge and to contribute theoretical, mathematical, scientific foundation and logical learning to the students with well-structured course outline by anticipating changing trends in Artificial Intelligence & Machine Learning.

PEO2 - Core Competence

To develop students with in-depth knowledge of Artificial Intelligence and exhibit high standards with regard to applications of AI techniques in intelligent agents, expert systems, artificial neural networks, and other machine learning models to meet the agile industrial requirements extensively.

PEO3 - Technical Accomplishments

To provide a strong foundation in embracing students learning to meet the ever-changing developments in artificial intelligence and machine learning.

PEO4 - Professionalism

To pursue their professional careers for self-advancement while meeting the requirements for professional developers, entrepreneurs, research, and development in order to meet the societal needs.

PEO5 - Learning Environment

To promote collaborative learning and the spirit of teamwork, interpersonal skills, and projects through multidisciplinary AI-based innovative product development and diverse professional ethics.

Program Outcomes

PO1

Engineering knowledge

Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop to the solution of complex engineering problems.

PO2

Problem analysis

Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)

PO3

Design / development of solutions

Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required. (WK5)

PO4

Conduct investigations of complex problems

Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions. (WK8).

PO5

Engineering Tool Usage

Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6)

PO6

The Engineer and The World

Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment. (WK1, WK5, and WK7).

PO7

Ethics

Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)

PO8

Individual and Collaborative Team work

Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.

PO9

Communication

Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences

PO10

Project Management and Finance

Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one’s own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.

PO11

Life-long learning

Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change. (WK8)

Program Specific Outcomes - PEOs

PSO1

Understand a range of analytical, logical - Programming languages, architecture, construction, and design underlying the field of AI and ML and its related disciplinary areas.

PSO2

Ability to acquire knowledge in analysis, design, and development of human perception, Artificial Intelligence, Machine Learning, and data analytics in terms of real-world problems to meet future challenges.

PSO3

Develop computational knowledge and project development skills using innovative tools and practices related to optimization techniques, pattern analysis, and speech recognition for the efficient design of computer-based systems of varying complexity to solve problems in the areas related to deep learning, machine learning, and artificial intelligence.

EAPCET/ICET CODE: MRCW