CSE (Artificial Intelligence & Machine Learning)
Welcome to CSE (Artificial Intelligence & Machine Learning)
Highlights of the Department
- Well qualified and experienced faculty in diversified domains.
- Nine computer centers with state-of-the-art-facilities.
- An Exclusive Department Library
- FAME – The CSE (AI&ML) Students Association.
- ANURAG-CSI Chapter
- The Department entered into MOUs with Infosys, TASK, Redhat, Microsoft, Co-Cubes,Oracle, IEG, Nucleus Vision LLC, Radiant Technologies, SAP, Birla Soft, Aspiring Minds, Globarena, NIS and Campus Classle & etc.,to provide high quality training in latest cutting edge technologies.
Programs Offered
- B.Tech (CSE(AI&ML))
Intake – 120
About Department
- The department of B.Tech (CSE(AI&ML)) was established in 2022 with an intake of 60 students in the UG Programme. Right from its inception it is continuously striving to impart quality education and competitive spirit among students for academic excellence. The present intake in B. Tech (CSE(AI&ML)) is 120.
- The department is equipped with state of the art computing facilities and experienced staff members and is known for its academic excellence proved by its performances since its inception. The Department also has audio-visual facilities with LCD Projectors and Digital Boards and Seminar Hall for effective teaching. The staff members are deputed to participate in workshops, Conferences and refreshers courses to keep in place with recent developments in the field of Artificial Intelligence & Machine Learning.
- Apart from the regular academic work, the department organizes guest lectures, seminars, workshops by inviting domain experts from industry and other reputed academic institutions.
Vision
To become a center of excellence for technically proficient, creative computer engineers.
Mission
- To impart quality education and share professional & technical knowledge, leading to a career as computer professional in different domains of industry, governance and academia.
- To impart hands on training in latest methodologies and technologies.
- To provide state-of-art environment for learning and practices.
Long Term Goals
- To encourage research activities in the department. To establish centre-of-excellence for research in Artificial Intelligence and Machine Learning.
- To establish and strengthen Industry-Institute interaction and be industry solution providers.
- To take up sponsored projects from private and government organizations.
- To have more number of publications and patents in the emerging areas of Artificial Intelligence and Machine Learning.
- To create better entrepreneurs in the area of Artificial Intelligence and Machine Learning.
Short Term Goals
- To improve the department’s human resources and infrastructure.
- To frequently carry out skill-enhancing faculty development activities.
- To run programmes that help students develop their hard and soft skills as well as their leadership potential, curiosity, and technical proficiency.
- To conduct conferences, workshops, and continuing education programmes to share information with the outside world.
- To increase students’ academic performance through the use of cutting-edge and creative teaching techniques.
Quality Policy
Faculty
Staff
Head of the Department
Indira Priyadarshini. T
M. Tech(Ph.D)
Indira Priyadarshini T awarded her B.Tech Degree in the year 2008 and M.Tech Degree in the year 2010 in Computer Science & Engineering from Acharya Nagarjuna University. Presently she is pursuing her Doctoral Degree from NIT Warangal in the area of Data Mining. She is the member of IE (I), CSTA, ACM, IAENG. She has published several research articles in reputed journals and conferences. Her areas of interest include Artificial Intelligence, Data Mining. Prior to joining AEC, she has worked with reputed organizations like Mallareddy University, Gokaraju Rangaraju Institute of Engineering & Technology and Vishnu Institute of Technology. She is certified in Agile and also possess industrial experience.
Infrastructure
Information Communication Technology (ICT) has the potential to transform the nature and process of teaching and learning environment / culture. Interactivity, flexibility, and convenience in an ICT supported environment enable both teachers and students to access and share ideas and information in diverse communication styles and formats. Class rooms are equipped with smart boards & LCD projectors to enhance ICT enabled teaching and learning.
Benefits with ICT enabled teaching:
- Improves student-teacher collaboration and interaction
- Encourages teachers to teach in real-time with audio and video lessons, visual multimedia & PPT presentations, 2D & 3D virtual space, etc.
- Paperless advantages
- Enhances Real-time blended teaching and learning methods
- Creates Web and Internet-based teaching and learning platform for teacher and students respectively
- Facilitates mobile integration facility.
- The implementation of ICT in OBE can effectively accomplish the goals of quality education which is a process that reduces consumption of resources and increases learning outcomes.
The Department Library occupies a unique place in academic and research activities of the Department. The Library maintains an excellent collection of data books, occasional papers and other documents/materials. The Library has a well equipped facility for reading. It also has one copy each of all B.Tech n & M.Tech projects carried out in the department in recent years. All these cater to the needs of students and faculty. Most of the books are of recent edition with the facility of issuing these for a specified time period. The library serves to provide a calm and comfortable ambience conductive to long hours of study. The library opens on all working days of the Institute from 9 AM to 4:30 PM.
The entire campus is Wi-Fi enabled with high speed internet connection to allow the students to access the internet no-matter wherever they are. The coverage is not just limited to the classrooms; instead it extends to all the facilities within the campus premises. Staff and Students can utilize the Wi-Fi Facility by registering their devices for the active usage of the facility.
Laboratories
(CS109ES) Programming for Problem Solving
Course Outcomes:
Upon the successful completion of this course, the student will be able to:
- Apply fundamental programming concepts and Exercise control statements to solve simple problems
- Represent and manipulate data with arrays and strings
- Modularize the code with functions so that they can be reused.
- Develop applications using user defined data types
- Implement various searching and sorting techniques
(CS207ES) Python Programming Laboratory
Course Outcomes:
Upon the successful completion of this course, the student will be able to:
- Able to develop programs using control statements.
- Able to code programs using modular approach.
- Read and write data from/to files in Python Programs
- To write GUI program to create window wizard using various buttons.
- Implement digital systems using python and to install and use various libraries.
(CS209ES) IT Workshop
Course Outcomes:
Upon the successful completion of this course, the student will be able to:
- Perform Hardware troubleshooting
- Understand Hardware components and inter dependencies
- Safeguard computer systems from viruses/worms
- Document/ Presentation preparation
- Perform calculations using spreadsheets
(CS306PC) Data Structures Laboratory
Course Outcomes:
Upon the successful completion of this course, the student will be able to:
- Ability to develop C programs for computing and real-life applications using basic elements like control statements, functions, pointers and structures and various linked lists.
- Ability to develop data structures like stacks and queues using arrays and pointers.
- Ability to implements the sorting methods like Quick sort, Heap sort and Merge sort.
- Ability to implement various trees and tree traversal techniques in recursive and non-recursive manner.
- Gain knowledge on implementing the graph traversal techniques and Pattern matching algorithms like Boyer- Moore, Knuth-Morris-Pratt.
(AM307PC) Operating Systems Laboratory
Course Outcomes:
Upon the successful completion of this course, the student will be able to:
- Simulate and implement operating system concepts such as scheduling,
- Able to implement C programs using Unix system calls
- Implement the deadlock avoidance using banker’s algorithm
- Implement the producer and consumer problem and Page Replacement algorithms
- Exercise inter-process communication.
(AM308PC) Software Engineering Laboratory
Course Outcomes:
Upon the successful completion of this course, the student will be able to:
- Understand and analyse problem domain of the applications
- Create software requirements documents for the applications to be developed
- Define software design documents for applications to be developed
- Build various models to represent software design using modeling tools
- Design different types of test cases to test the applications.
(CS407PC) Database Management Systems Laboratory
Course Outcomes:
- Develop ER data model and Relational data model for a database.
- Design database schema for a given application and apply normalization.
- Apply SQL commands for data definition and data manipulation.
- Apply the basics of SQL for retrieval and management of data.
- Develop solutions for database applications using procedures, cursors and triggers.
(AM408PC) Java Programming Laboratory
Course Outcomes:
- Able to write programs using OOP principles.
- Able to write programs using abstract classes.
- Able to write multithreaded programs.
- Able to write programs for solving real world problems using the java collection framework.
- Able to write GUI programs using swing controls in Java.
(AM505PC) Machine Learning Lab
Course Outcomes:
- Understand modern notions in predictive data analysis.
- Select data, model selection, model complexity and identify the trends.
- Understand a range of machine learning algorithms along with their strengths and weaknesses.
- Build predictive models from data and analyse their performance.
- Understand the Performance Analysis of Classification Algorithms.
(CS504PC) Computer Networks Lab
Course Outcomes
- Implement data link layer farming methods
- Analyze error detection and error correction codes.
- Implement and analyze routing and congestion issues in network design.
- Implement Encoding and Decoding techniques used in presentation layer
- To be able to work with different network tools
(AM604PC) Natural Language Processing Lab
Course Outcomes:
- Apply Knowledge of Word Analysis & Word Generation.
- Implement Ambiguous sense & WSD.
- Knowledge on Morphological Analysis NLTK tool Kit
- Understand the Morphological Analysis using NLTK library
- Explore N- Grams Smoothing &NLTK Package.
(AM605PC) Data Analytics Lab
Course Outcomes:
- Understand linear regression and logistic regression
- Understand the functionality of different classifiers
- Implement visualization techniques using different graphs
- Apply descriptive and predictive analytics for different types of data
- Design various classification techniques.
Contact Us
Head of the Department
9553996388
hod.cseaiml@anurag.ac.in