Specializations Offered by CSE

Specializations

• Artificial Intelligence
  • Core Courses
  • Elective Courses
  • Semester Wise Plan
• Visual Computing
  • Core Courses
  • Elective Courses
  • Semester Wise Plan
• Socio-Digital Reality
  • Core Courses
  • Elective Courses
  • Semester Wise Plan
• Engineering Innovation

• Artificial Intelligence
  • Core Courses
  • Elective Courses
  • Semester Wise Plan

• Eligible Branches
  • Eligible Branches

Artificial Intelligence

Core Courses

Total 8 credits need to be taken for core courses

• AI [3-0-0]
• Deep Learning [3-0-0] [BB must take elective in place of this course]
• ML-Ops [0-0-2]
• DL-Ops [0-0-2]

* Since DL is a core for BB students, they can take any other course from SE as part of SC.

Elective Courses

Total 12 credits need to be taken for elective courses

• Algorithms for big data [3-0-0]
• Computer Vision [3-0-0]
• NLU [3-0-0]
• machine learning with big data
• edge and fog computing
• GPU Programming [3-0-0]
• Data Visualization [3-0-0]
• Introduction to AR and VR [3-0-0]
• Dependable AI [3-0-0]
• Resource constrained AI [3-0-0]
• Social Network Analysis [3-0-0]
• Optimization [3-0-0]
• Computer Graphics [3-0-0]
• Advanced AI [3-0-0]
• Advanced ML [3-0-0]
• Project [0-0-6]
• Autonomous Systems [3-0-0]
• ML for Communications [3-0-0]
• Planning and Decision Making for Robots [3-0-0]

Semester Wise Plan

Visual Computing

Core Courses

Total 8 credits need to be taken for core courses

• Computer Vision [3-0-0]
• Computer Graphics [3-0-0]
• Visual Computing Lab [0-0-4]

Elective Courses

Total 12 credits need to be taken for elective courses

• Computational Imaging [3-0-0]
• 3D Shape Analysis [3-0-0]
• Introduction to Haptics [3-0-0]
• Advance Machine Learning  [3-0-0]
• Computational Photography  [3-0-0]
• Video Processing  [3-0-0]
• Bio-imaging  [3-0-0]
• Medical Image Analysis  [3-0-0]
• Image Synthesis  [3-0-0]
• Animations  [3-0-0]
• Digital Image Processing  [3-0-0]
• Visual Perception  [3-0-0]
• Introduction to AR and VR  [3-0-0]
• Real-Time Vision Architectures  [3-0-0]
• Scalable Machine Learning  [3-0-0]
• Compressive Sensing  [3-0-0]
• Image and Video Forensics  [3-0-0]
• Special Topics: Advancements in Computer Vision [3-0-0]
• Selected Topics in Computer Vision [3-0-0]
• Specialization Project [0-0-6]
• Principles of Biological Vision [3-0-0]

Semester Wise Plan

Socio-Digital Reality

Core Courses

Total 8 credits need to be taken for core courses

• Introduction to AR and VR  [3-0-0]
• Social Networks  [3-0-0]
• Multimodal Interface  [0-0-4]

Elective Courses

Total 12 credits need to be taken for elective courses

• Computer Graphics [3-0-0]
• Natural Language Understanding [3-0-0]
• Introduction to Haptics [3-0-0]
• Speech Understanding  [3-0-0]
• Human Computer Interface
• Computer Vision [3-0-0]
• Image and Video Forensics [3-0-0]
• Design Process
• Specialization Project [0-0-3]

Semester Wise Plan

Engineering Innovation

Department Area Specialization in Engineering Innovation is aimed at making students Industry Ready by offering five months Practical Project in an Industry or R & D organization. It focuses on the use of technical knowledge to create products and processes which have usability value. The objective of this specialisation is to recognise such creative engineering endeavours. This activity is not expected to aim only publication of papers. It must happen in collaboration with an IIT J faculty member and is expected to have an industrial or User agency as a partner with MoU. Each project carried out by students will have both a company supervisor and an institute supervisor. Students get real-world experience working for an industry or R & D organization on a project that complements their academic experience. Projects are aimed to enable them for meaningful careers and provide them with an opportunity to engage with industry before graduation.

Engineering Innovation will be a full semester 20 credit engagement. 10 Credits out of 20 will be taken up as a part of Open electives, whereas the student is required to opt for an additional 10 credits in the form of course overload in other semesters. A student would be required to complete a minimum of five months in industries or R & D organization or Institute for Department Area Specialization in Engineering Innovation. Students can opt for it in either the 7th or 8th Semester.

Note: Keeping this in view, Environmental science will be offered in both semesters.

Artificial Intelligence

B.Tech. + M.Tech. Dual Degree in Artificial Intelligence. Students who opt for the Specialization in AI can opt for dual degree in AI.

Core Courses

• Optimization [2-0-0]
• Artificial Intelligence [3-0-0]
• Advanced data structure and algorithms [2-0-0]
• ML-Ops [0-0-2]
• Deep Learning [3-0-0]#
• DL-Ops [0-0-2]
• Core bouquet: Advanced AI / Autonomous systems [3-0-0]

List of Electives will be as per M.Tech. curriculum

* For all students, ML course is a preparatory course and should be replaced with any of the PEs.

# Since DL is a core for BB students, they can take any other course from PE as part of PC.

Semester Wise Plan

Eligible Branches

* Details available with EE department