UG Programs | 4 years

B.Tech in Computer Science & Artificial Intelligence

Increasing access to computing power and explosion of digital data coupled with advances in AI are transforming every aspect of human life. The Computer Science & Artificial Intelligence program is not a traditional Computer Science degree, but combines a Computer Science core with artificial intelligence, machine learning and human intelligence with a long term view that computing systems will be pervasive and that the interface of human and artificial intelligence will be a source of future grand challenges and opportunities for innovation.

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8 Semester Curriculum The curriculum at Plaksha is dynamic and continuously evolving, based on inputs from faculty, latest research and industry insights. B.Tech in Computer Science & Artificial Intelligence syllabus outline is given below.
  • Semester 1
  • Semester 2
  • Semester 3
  • Semester 4
  • Semester 5
  • Semester 6
  • Semester 7
  • Semester 8
Introduction to AI

Instructor: Dr. Kanchi Gopinath


Fundamentals of Computational Thinking

This course is aimed to provide students with an understanding of the role that computational thinking plays in problem solving. They will be exposed to programming concepts and how to use them to design solutions using C language, starting from simple problems to interesting ones using ideas such as recursion and backtracking. In addition to learning key computing concepts and skills, the course will focus on laying necessary foundations in computational thinking going forward. For example, paradigms such as 'divide and conquer' and dynamic programming will be introduced through examples.


Instructors: Dr. Deepan M., Dr. Manoj Kannan


Design & Innovation

Instructor: Prof. Amit Sheth


Engineering Math in Action

Nature's Machines

Entangled Worlds: Technology and the Anthropocene (Part - 1)

What do we mean when we say Entangled Worlds? Entanglement as such implies a state of intertwining, of interpenetration, deep connectivity, interlocking and irreducible, fundamental interdependency and interrelationship. Although it would seem obvious that we live in a profoundly interconnected world in which both processes initiated by humans and non-human biological and non-biological entities continuously impact one another, our actions as organic, conscious and sentient beings do not reflect the obvious fact of interconnectedness.

Human beings by and large continue to operate as though their actions are isolated events that do not impact the rest of the world including other human beings, plant and animal species. Environmental degradation, climate change, species extinction, economic inequality, various forms of injustice, war and so on perhaps point towards a fundamental flaw in the way we think and act. In fact, we could claim the way we think and act is no longer commensurate with the kinds of immense global challenges we are facing. This seems to be the critical question of the Anthropocene.

How does one begin to return to a fundamental understanding of the embeddedness of all forms of life as well as so-called inorganic material in a web of interdependence, of inexorable entanglement? Is it even possible for us to engender a radical shift in the way we think about ourselves and planet Earth? Or have we already gone too far in our quest for creating a solely human-centric world?

In this course we will explore and reflect on the question of entanglements from a variety of transdisciplinary perspectives including those of art, music, imagination, biological systems, quantum mechanics, language, mathematics, design, thought, time, space, history, philosophy and technology. In particular, we will be experimenting with the idea of contrapuntal music as a model from which to think about ways of interconnecting different, independent melodies (read: concepts) in a dynamic, lattice-like structure through which a new emergent harmony is created. 


Instructors: Dr. Aditya Malik, Dr. Brainerd Prince, Dr. Saikat Chakraborty


Communication Lab - 1

Some of you might wonder about the value of spending so much time and effort on this writing course while having signed up for a professional degree – an engineering program. While this course covers foundational skills that are central to an academic writing course, these skills are also of critical value for any engineer or technology enthusiast. They will give you an edge over other engineering and technology students in terms of language and presentation. Reading skills are important tools, necessary to procuring relevant information and data on the latest technology and acquiring new knowledge in a rapidly evolving world of engineering and technology.

Finally, the writing skills you develop here will enable you to identify debates, put forth your viewpoints, and argue effectively in order to produce a clear and coherent academic paper. The writing skills are transferable and will enable you to argue for your case/point of view and empower the decisions you take in any professional situation. This course follows a transdisciplinary approach. The two main writing assignments are done in collaboration with two other first-semester courses – Nature's Machines and ILGC. 


Instructor: Dr. Brainerd Prince


Innovation Lab & Grand Challenge Studio - 1

Programming & Data Structures

Mathematics of Uncertainty

Instructor: Dr. Amrik Sen


Foundations of Physical World

Nature's Machines Lab

Fundamentals of Microeconomics



Communication Lab

Instructor: Dr. Brainerd Prince


The Art of Thinking & Reasoning



Innovation Lab and Grand Challenge Studio - 2

Universal Human Values



Electronics Systems Engineering

The objective of the course is to train the students in the field of basic and applied electronics, which forms the backbone of the modern semiconductor and telecommunication industry. The course covers the fundamental and applied aspects of the subject aligned toward the design and development of novel electronic devices and systems. The course starts with an introduction to the broader field of electronics engineering and its relevance for other industry verticals against the framework of significant inventions and innovations. It will cover the essential aspects of circuit theory and evolves towards encompassing the operation of semiconductor devices which form the backbone of computational and communication systems.

A special focus of the course is on how simple devices and circuits get interconnected to form complex units which play a defining role in the operation of sophisticated gadgets. Towards the completion of the course, the students would be able to conceive and prototype new artifacts, systems, and gadgets, while using the foundation of analog and digital electronics. 


Instructors: Dr. Sanjay Kumar Bose, Dr. Dhiraj Sinha


The Philosophy and Foundations of Computing and AI

This course explores philosophical and foundational issues concerning computers, computing, and artificial intelligence. It addresses a range of fundamental questions, including: What is a computer? Could a computer be conscious? How could you test whether a computer is thinking? Are thinking and consciousness the same or different? Is the human brain a computer? Are there limits to what is computable?

The course also describes the work of Alan Turing, and his revolutionary ideas and legacy. While a graduate student, Turing invented the fundamental logical principles of the modern computer. He is responsible for the model of computability that underlies modern computer science—the universal Turing machine. The course investigates this important model and the scope and limits of the universal machine. It also includes an introduction to the early years of the computer revolution, covering the secret origins of electronic computers during World War II and the earliest work on artificial intelligence.


Instructor: Dr. Jack Copeland


Universal Human Values - II

Instructor: Dr. Shalini Sharma


Intelligent Machines

This course provides a comprehensive introduction to robotics and cyber-physical systems. Through hands-on lab activities, assignments, projects, as well as through guest lectures spanning research and practice the students learn about topics such as- sensors & actuators, system modeling, kinematics, dynamics, and controls, perception, planning, and navigation, cyber-physical systems, communication, and hardware. These are all the ingredients for designing intelligent machines. At the end of this course the students will be able to gain the skills to design, build and evaluate simple robotic and cyber-physical systems that will give them the confidence to pursue more complex projects in their future endeavors. 


Instructors: Dr. Sandeep Manjanna, Dr. Shashank Tamaskar


Innovation Lab & Grand Challenge Studio - 03

Instructor: Dr. Rucha Joshi


Communication Lab - 3

Instructors: Dr. Brainerd Prince, Dr. Sumita Ambasta


Intro to Data Science



Computational Methods & Optimization



Entangled Worlds: Technology and the Anthropocene (Part - 2)

What do we mean when we say Entangled Worlds? Entanglement as such implies a state of intertwining, of interpenetration, deep connectivity, interlocking and irreducible, fundamental interdependency and interrelationship. Although it would seem obvious that we live in a profoundly interconnected world in which both processes initiated by humans and non-human biological and non-biological entities continuously impact one another, our actions as organic, conscious and sentient beings do not reflect the obvious fact of interconnectedness.

Human beings by and large continue to operate as though their actions are isolated events that do not impact the rest of the world including other human beings, plant and animal species. Environmental degradation, climate change, species extinction, economic inequality, various forms of injustice, war and so on perhaps point towards a fundamental flaw in the way we think and act. In fact, we could claim the way we think and act is no longer commensurate with the kinds of immense global challenges we are facing. This seems to be the critical question of the Anthropocene.

How does one begin to return to a fundamental understanding of the embeddedness of all forms of life as well as so-called inorganic material in a web of interdependence, of inexorable entanglement? Is it even possible for us to engender a radical shift in the way we think about ourselves and planet Earth? Or have we already gone too far in our quest for creating a solely human-centric world?

In this course we will explore and reflect on the question of entanglements from a variety of transdisciplinary perspectives including those of art, music, imagination, biological systems, quantum mechanics, language, mathematics, design, thought, time, space, history, philosophy and technology. In particular, we will be experimenting with the idea of contrapuntal music as a model from which to think about ways of interconnecting different, independent melodies (read: concepts) in a dynamic, lattice-like structure through which a new emergent harmony is created. 


Instructors: Dr. Aditya Malik, Dr. Brainerd Prince, Dr. Saikat Chakraborty


Optimization

Instructor(s) - Dr. Nitin Upadhyaya


Programming Language Principles and Design

Instructor(s) - Dr. K. Gopinath


Foundations of Computer Systems

Introduction to Data Mining & Pattern Recognition

Design and Analysis of Algorithms

Instructor(s) - Anurag Sahay and Arpita Biswas


Communication Lab - 2

Instructor(s) - Dr. Brainerd Prince


Innovation Lab & Grand Challenge Studio - 04

Machine Learning and Pattern Recognition

Instructor(s) - Dr. Siddharth


Search in AI

Instructor(s) - Dr. Deepak Khemani


Theory of Computation

Instructor(s) - Dr. Tapas Pandit


Program Analysis (E)

Instructor(s) - Dr. Rajeev Barua


Embedded Systems (E)

Instructor(s) - Dr. Anupam Sobti


Innovation Lab & Grand Challenge Studio - 05

Instructor(s) - Dr. Srikant Srinivasan


Innovation Lab & Grand Challenge Studio VI

Continuing their project progress from semester 4, the goal for Semester 5 and 6 will be to implement solutions via projects at the State level, with an eye for expansion at the National level. To achieve this, students will seek validation of concept from various stakeholders, complete the engineering design cycle of their project, while also developing an entrepreneurial spirit from their experiences. Mentored Leadership and Professional Development opportunities will be a constant feature across the 4 year ILGC experience, and will be integrated with project work. These serve to develop the student’s professional skills and also help in creating a more integrated socio-integrated understanding of engineering/design.


Data Mining & Pattern Recognition

This is an introductory course that sits between the domains of statistics, mathematics, machine learning and knowledge discovery. The aim of this course is to give a sweeping exposure to various concepts and mathematical techniques for profiling data sets, analysing them in an open-ended exploratory manner or task-specific targeted manner, building hypotheses and testing them. Along the way, we will cover topics such as data transformation, similarity and dissimilarity indices, data dimensionality reduction, descriptive statistics, predictive modelling, clustering analysis, data visualisation, and evaluation metrics. We will build intuition by working through real world examples. And acquire practical skills by applying our toolkit to reveal patterns and glean insights from wide ranging datasets from the fields of social sciences, medical sciences, natural sciences, financial market, business, etc.


Software Implementation

This course will introduce students to software engineering approaches used in industry, with emphasis on specifying software implementation and testing. Course contents include the Agile software development approach, best practices in coding style, test-case driven development, testing approaches, and software metrics. All through the semester, student teams will participate in a substantial coding project probably catering to the needs of local businesses. In the concluding month, industry speakers will elaborate on the software engineering practices followed in their respective companies.


Natural Language Processing

The course will teach students to build natural language processing systems by processing text, including tokenizing and representing sentences as vectors, RNNs, GRUs, LSTMs and Attention mechanisms for machine translation. Upon completion, the student will be expected to recognize NLP related tasks in day-to-day scenarios and propose approaches that are likely to work well for the scenarios. A brief introduction to Indian NLP will also be part of the course along with a discussion of earlier approaches to NLP.


Technical Elective II

Students may take courses from other majors as part of the free elective. Additionally, faculty may also offer some introductory electives as part of this sequence.


Application Domain Track III

The Application Domain Tracks are a series of 1 credit modules that help students inculcate skills and mindsets related to research and entrepreneurship. Through these tracks, students will contribute to ongoing research projects in Plaksha's flagship grand challenge research centers, and may work with faculty on their research or on approved external projects in industry/government or startups. Across semesters, students will have the option to work across different disciplinary areas or focus on one area but the purpose is for them to appreciate the relevance of their coursework to a variety of challenges and areas.


Security of eSystems

In this course, students will learn about different kinds of security problems, with real-life examples, and how to detect and defend against them. The course will broadly cover the following aspects of systems security - basics of security modelling; security policies and mechanisms; hardware security, security of software at programming language level and at the network and web levels; types of attacks and its prevention and defence; basics of cryptography including encryption and decryption algorithms; case studies of serious security incidents and their root cause analyses.


Technical Elective I

Sample Electives include: Cloud Computing, Design of AI Products, Human Computer Interaction, Neural Computing, Data Analytics and Visualisation, Deep Reinforcement Learning, Quantum Computing


Technical Elective II

Sample Electives include: Cloud Computing, Design of AI Products, Human Computer Interaction, Neural Computing, Data Analytics and Visualisation, Deep Reinforcement Learning, Quantum Computing


Human Sciences - Elective I

Sample electives include: Neuroscience, Brain Science, Human Cognition Perception and Memory, Cognitive Psychology, Language and Thought


Innovation Lab & Grand Challenge Studio Capstone

ILGC transforms and culminates as a two semester capstone design project. By the end of the seventh semester a detailed design of the final product (this could be a device, system, process, software, etc. that results from this design experience) needs to be completed. This includes but not limited to the following: Description of the overall project, including a description of the customer and their requirements, the purpose, specifications, and a summary of the approach. Description of the different design approaches considered and evaluation of each design approach. Detailed description of the final proposed design.


Advanced Topics in AI

This course is envisioned to be offered in a seminar format where the instructor will provide motivating elements to spur student-led investigative research in contemporary and emerging topics in the fields of machine learning, artificial intelligence, and data science. Students will learn to engage in scientific investigation and report their findings in seminar format.


Technical Elective III

Sample Electives include: Cloud Computing, Design of AI Products, Human Computer Interaction, Neural Computing, Data Analytics and Visualisation, Deep Reinforcement Learning, Quantum Computing


Human Sciences - Elective II

Sample electives include: Neuroscience, Brain Science, Human Cognition Perception and Memory, Cognitive Psychology, Language and Thought


Humanities & Social Science Elective

Sample electives include: AI for Social Good, Technology, Policy and Law, Decision Making Under Uncertainty, Fairness, Transparency, Accountability, and Ethics in Data Science


Innovation Lab & Grand Challenge Studio Capstone

ILGC transforms and culminates as a two semester capstone design project. By the end of the eighth semester, students will have a working product (this could be a device, system, process, software, etc. that results from this design experience). Therefore, the focus of this semester is to implement, test and evaluate the design approach chosen in your first semester. The following are the expected requirements and deliverables for this semester: Working final product Testing and evaluation of product design Demo of the final product Completed Project Description, Final Reflection and Completed Outcomes Matrix


Learning Experiences

Experiential Learning

Integrated learning experience across 4 years of B.Tech in computer science with artificial intelligence. You will work on authentic, real world projects through industry and community engagement or by research with faculty.

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By having access to state-of-the-art makerspaces and coding cafes and incorporating them in the curriculum, students will become more context-aware, develop critical thinking abilities, and learn by creating. This will help foster a tinkering and problem solving mindset, immersing students in experiential learning from day one. These areas will be open to students to explore, create, prototype and design, while also housing equipment and technologies like 3D printers, sensors, etc.

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The core curriculum will not just be limited to engineering and sciences, but bring in exposure to entrepreneurship and design which will enable humane and empathetic outcomes through technology. Each student will undertake multiple different experiences to develop skills like finding opportunities, creating value, and embracing risks. Students will be mentored and supported by Plaksha founders and professionals from industry.

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At Plaksha, learning and skill development do not stop in the classroom. Students will have the opportunity to create and immerse themselves in pursuing their academic and creative interests. Student led clubs will be autonomous bodies that operate under the purview of the Office of Student Life. Being the founding batch, students will be encouraged to help establish a vibrant culture through clubs and societies on campus.

Hear about the course from the experts

Watch Srikanth Velamakanni, Founder and Trustee, Plaksha University as he explains the relevance and scope of this B.Tech. degree.

Find the answers to your questions in some of our frequently asked questions by students
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Dates to Remember

Dec 5, 2023

Round 1 Deadline

Jan 17, 2024

Round 2 Deadline

Feb 28, 2024

Round 3 Deadline

Apr 30 , 2024

Round 4 Deadline

Jun 17, 2024

Round 5 Deadline

*Round deadlines are subject to change.

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