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UG Programs | 4 years

B.Tech in Biological Systems Engineering

The Biological Systems Engineering program combines the power of biology, computing & engineering to tackle some of the greatest challenges for human & planetary health. Our population’s health is dominated by various diseases, & are exacerbated by major risk factors such as air pollution, malnutrition & vast regional differences in health care services. The vision for the BSE program is to transform health outcomes for the world, by leveraging the powerful convergence of data, digital health, biologics manufacturing & biology. Final Application Deadline - Sept 09, 2021
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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.
  • Semester 1
  • Semester 2
  • Semester 3
  • Semester 4
  • Semester 5
  • Semester 6
  • Semester 7
  • Semester 8
Innovation Lab & Grand Challenge Studio I

This course, referred to as ILGC, introduces the Grand Challenges at the interface of societal needs and technological capabilities. It will offer the opportunity for students to develop an interdisciplinary appreciation for engineering from a technical perspective as well as from a global and historical perspective. Students will embark on this integrated, project-based journey in the 1st semester and work on different projects throughout the four-year program. First semester topics include - Exposure to different Grand Challenges and project areas, design cycle, grand challenge thinking, geopolitics and global awareness, and entrepreneurial mindset.


Critical Thinking & Scientific Reasoning

What are the assumptions and beliefs that we have not examined in the modern age? How do we become aware of our implicit beliefs? What possibilities open up if we investigate and examine our presuppositions? How can we respond to the Grand Challenges of our time, if we don’t know how to think and reason critically? In this course, you will learn to meticulously develop the skill of thinking and enquiring critically, and being able to reason in a scientific, evidence-based manner. The course will focus on sharpening your intellectual abilities so that thinking critically and scientifically becomes a natural way of approaching the world. You will learn how to carefully analyze texts, structure arguments, develop technical reading and writing skills, and communicate your ideas in a coherent and logical manner to different audiences. Additionally, you will also learn to evaluate hypotheses and causal claims, observe and analyze data and patterns, construct reason-based arguments, and draw logical conclusions.


Engineering Mathematics in Action

In this course, students will be introduced to foundational aspects of engineering mathematics, specifically linear algebra, matrices, and ordinary differential equations. The course is divided into four modules, two modules each on linear algebra and ordinary differential equations. The topics included under the linear algebra modules are definition of vector spaces, concepts on linear independence of vectors, bases, rank of a matrix, solutions to linear systems, definition and interpretation of eigenvalue problems, and singular value decomposition and their applications. The topics under ordinary differential equations are methods to solve simple linear differential equations using both analytical (method of undetermined coefficients, variation of parameters) and numerical techniques (Runge-Kutta methods), basics of phase plane analysis, stability of solutions based on eigenvalue analysis, fixed points, and elementary concepts on bifurcation and chaos. Each module will comprise a computer-based laboratory project.


Fundamentals of Computational Thinking

This course provides students with an understanding of the role that computational thinking can play in solving problems. Students will be exposed to varied real-world problems and be taught how to approach them and design solutions using Python. In addition to learning key computing skills and concepts, the course will focus on how existing features in programming languages can be used to implement different concepts efficiently and how one can analyze different solutions. After taking the course students are expected to work on real-world projects that require building logical thinking processes that break down complex problems into smaller parts.


Foundations of Physical World

In this course, students will be introduced to classical mechanics, quantum mechanics, statistical mechanics, and connections to engineering thermodynamics. Molecular origin of macroscopic descriptions and constitutive relations for equilibrium and non-equilibrium behavior; fluctuations, kinetics, and limitations of macroscopic descriptions. Macroscale continuum origin of lumped models: ‘through’ and ‘across’ variables for analysis of electrical, mechanical, structural, thermal, acoustic, and fluidic systems.


Design Thinking

This course introduces students to harness the power of design thinking to develop innovative solutions to complex human-centered problems. The design thinking methodology will help students learn about the underlying context and the innovation need, brainstorming and developing prototypes, testing potential solutions, improving them, and developing new insights. Students will be exposed to core technology and design themes including principles, modes of thinking and analysis, and social and cultural aspects of design. They will learn how to use the ideation process to generate new ideas and select promising solutions, use prototyping tools to visualize and communicate ideas and develop the implementation plan for an effective solution.


Innovation Lab & Grand Challenge Studio II

Building on the ILGC journey from Semester 1, ILGC II will introduce students to starting their team projects, implementing principles of Design Thinking, embarking on a campus-wide project, and interacting with real-world stakeholders. Students will also learn how to work with various tools and build skills in machining, programming, instrumentation, among others.


Reimagining Technology & Society

In this course, we will rigorously enquire into the different meanings of the idea of technology and its relationship to society from the perspectives of philosophy, history, social anthropology, human evolution, and civilizational studies. We will look at examples from the past and present, but more importantly, also start imagining what the relationship between technology and society could be in the future. We will ask a number of questions pertinent to this inquiry: Does technology influence society, or, does society influence technology? What indeed is technology? Is technology perhaps first and foremost an ‘idea’? Or, is technology a particular way of knowing the world around us? If it is an idea then it must involve thinking of some kind. But clearly it also involves making something – usually an object that does something or has a particular function. In this course we will begin to understand technology from the standpoint of the threefold matrix of thinking, knowing, and making.


Mathematics of Uncertainty

This is an introductory level UG course on probability and statistics. Topics include conceptual introduction to probability axioms, conditional probability, Bayes' theorem, law of total probability and expectation, measures on central tendency and dispersion, probability distributions, simple discrete and continuous probability distribution models, elementary concepts on discrete and continuous time Markov processes, least squares regression analysis, sampling distributions and elementary ideas on hypothesis tests. Students will have to complete an end-of-term project on a topic of their choice.


Programming & Data Structures

Building on the Python course taught in the previous semester, students will be introduced to the Object Oriented Programming (OOP) paradigm and the associated benefits. They will learn to write structured and efficient programs in the OOP style. Besides testing and debugging programs, students will learn about common data structures, and where and how to apply them to solve computational problems.


Nature’s Machines

This course introduces students to how nature’s machines work. It covers various aspects that relate the design of living matter/things to engineering. We will discover how to think about: a) the human cell as a factory, the circulatory system as a transport network, musco-skeletal system as a structural network for load-bearing, magnetoreception in animals as a communication system, among other topics. b) Aspects of biomedicine such as the design of impedimetric sensors, digital health, and tissue and genetic engineering. c) Diversity and dynamics of nature pertinent to engineering through several demo examples and recent state-of-the-art applications.


Fundamentals of Microeconomics

The course introduces core microeconomic models of consumers, firms, and markets, and develops their application to a broad range of economic and social issues in the real world. It will cover concepts of equilibrium, markets and competition, market demand and market supply, behavior of consumers and producers, consumer and producer theory, pricing, tax incidence, making choices under uncertainty, economic efficiency, etc., in the context of contemporary real-world applications around us such as Uber surge pricing, telecom price wars, e-commerce models, recent ed-tech acquisitions, etc.


Innovation Lab & Grand Challenge Studio III

In this course, students continue to build on their IL/GC projects, with an eye for expansion at the city level. They will be able to develop multidisciplinary approaches and interdisciplinary perspectives by interacting with and making connections between disciplines; analyzing the humanistic, social, historical, economic, and technical contexts of problems. In addition, they will continue to iterate their designs and work on skills such as developing innovation and entrepreneurial mindset, becoming a better communicator and leader, and understanding the social and human consequences of actions and responsibilities to others in local, national, and global communities.


The Ethics of Technological Innovation

The advent of technology since the turn of the century has led to many advancements in the way that humans live and operate. This progress, however, also comes with apprehensions, uncertainty, and questions regarding the ethical considerations associated with the owners, regulators, and users of the technology. In this course, we will examine the manifold ethical issues surrounding the use and development of AI, Robotics, Biology, and Business based technologies in the contemporary world. Students will be introduced to ideas of safety, privacy, regulations, and related consequences of bias, manipulation, and fairness, from a multidisciplinary perspective. Students will be introduced to ideas from traditional philosophical ethics texts before delving into real world case studies focussing on contemporary issues.


Mathematics for Continuous Systems

This course will introduce foundational ideas on mathematical transforms like Laplace and Fourier transforms. Additionally, there will be a two month long module on partial differential equations and vector calculus. In addition to lectures, students will participate in a semester long, state of the art physical laboratory immersion program which will involve training and tinkering with experimental mathematics, such as profiling heat conduction through a metallic rod to understand the mechanics of the heat equation and its solutions, performing fluid mechanics experiments using a rotating tank of water and high-speed camera to collect data and understand the solution states of the Navier Stokes equation, using wavemaker and wave guides to calculate wave velocity and comparing the data with theoretical calculations, performing laboratory experiments with spectrometers to estimate power spectral density of signals and compare the results with mathematical calculations in Fourier space, etc.


Data Science & Artificial Intelligence

This course offers an introduction to the areas of Data Science, Artificial Intelligence, and Machine Learning (DS/AI/ML), combining philosophical, biological, and psychological perspectives with computational design concerns. Students will begin the course by understanding the principles underlying learning and how it translates to various applications and categories of AI. Besides multiple classes of models, students will be introduced to fundamental concepts in data science that will help them identify, compare and implement solutions to problems. Internal critiques and external perspectives of AI solutions will also be discussed to ensure students obtain a holistic view of the challenges and opportunities in this field.


Intelligent Machines

This course introduces the students to the idea of intelligence and how intelligent machines are transforming the world around us. Students will learn about the concept of cyber-physical systems and how intelligence stems from the ‘perception, reasoning, and action loop’. Students will explore several examples of cyber-physical systems in the real world in areas such as robotics, smart grids, and autonomous cars. They will learn about mathematical techniques for modeling cyber-physical systems, how to build intelligent machines by combining sensors, actuators, and embedded devices. Through hands-on lab activities, assignments, projects, as well as through guest lectures spanning research and practice, students will be able to gain the skills to design, build and evaluate simple cyber-physical systems that will give them the confidence to pursue more complex projects in their future endeavors.


Foundations of Optimization

This course offers a multidisciplinary overview of the field of optimization. Students will learn how to formulate an optimization problem, apply different optimization techniques, translate problems into Python and Matlab code, and identify conditions under which each one works best. Students will be introduced to numerical, constrained, unconstrained, univariate and multivariate optimization methods and techniques, while also being introduced to topics such as Pareto optimality, multiobjective and global optimization. The final project will allow students to apply their knowledge to real-world engineering and business problems.


Innovation Lab & Grand Challenge Studio IV

In Semester 4 students will decide the IL/GC project (coincides with choosing their major) and team they will be part of, and initiate the first steps of the project that will culminate with their capstone. Projects chosen by students will be connected and coherent in design, looping in a wide range of technology such as sensors, IoT, automation, robots, AI/ML, data science, biosystems design, etc. The core focus would be on implementing the engineering design cycle and reflecting on progress, to create solutions implementable at a city level, with an eye for expansion at state level. Mentored Leadership and Professional Development opportunities will be a constant feature across the 4 year IL/GC 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.


Materials Science for Bioengineering

The properties of a material are determined by its structure. Processing can alter that structure in specific and predictable ways. The behaviour of materials is grounded in science. The properties of all materials change over time with use and exposure to environmental conditions. When selecting a material, sufficient and appropriate testing must be performed to ensure that the material will remain suitable throughout the reasonable life of the product. This course assumes that the students are familiar with basic chemical bonding and the periodic table. The course is designed as an introduction to the field, not a comprehensive guide to all materials science knowledge. Instead of going into great detail in many areas, the course provides key concepts and fundamentals students need to understand materials science and make informed decisions.


Biochemistry & Molecular Biology

The students will be introduced to molecular basis of life and gain understanding of biomolecules, metabolic pathways, genomes, gene structure, expression and regulation, transcription, translation, post-translational modifications, cell-signalling that constitutes the molecular and biochemical functions of a living organism. The course will also dwell into Genomics, Proteomics and Metabolomics and understand the defects in these processes to elucidate the molecular basis of human diseases. Recombinant DNA technology and gene editing technologies (CRISPR Cas) along with current avenues of therapeutic interventions, precision and personalized medicine will be discussed. Laboratory activities will include hands-on experience with molecular characterization of biomolecules, gene regulation and recombinant DNA expression.


Bioinformatics & Computational Molecular Biology

This course will cover essential topics related to bioinformatics and computational biology. Students will be introduced to the sequencing analysis, a short introduction to ‘omics’ approaches, and they will know about various biological sequence databases. The course includes biostatistical analysis techniques such as ANOVA, hypothesis testing, distributions; phylogenetic analysis for comparative biology such as speciation, predicting infectious diseases; and gene prediction analysis such as prokaryotes versus eukaryotes, horizontal gene transfer, promoters, splice sites, and repetitive elements. Other topics include next-generation sequencing technology linking with genome manipulation using genome editing and the CRISPR Cas toolbox. Structural bioinformatics will introduce the structural prediction of proteins, nucleic acids, membranes, and hybrid structures. The students will explore concepts of homology modelling, threading/Fold recognition, and ab initio structure prediction. The computational biology portion intends to understand the computation of the network of genes, proteins, and protein-protein interactions, thus linking the information processing by biomolecules with the biochemical pathways in cellular processes. A short introduction to the control theory and network analysis of biochemical pathways. Other topics include applying different sampling techniques to simulate spatiotemporal phenomena linking conformational heterogeneity of biomolecules with the underlying molecular mechanism of the biological function and exploiting the relation to employing computer-assisted drug designing techniques.


Stochastic Modeling in Biology & Physiology

Randomness is an intrinsic property of intracellular environments and its effects are observed in organization of living matters such as cells, tissues, organs and organisms. This course introduces stochastic modelling of biological systems and processes elucidating various applications in predictive behaviours to solve biological problems. The course will cover properties of diffusion and Poisson processes. In addition, diffusion models based on position-jump processes and velocity-jump processes will also be covered. Examples will be discussed to demonstrate the need for stochastic models and probability in characterization and understanding of physiological systems.


Application Domain Track I

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.


Innovation Lab & Grand Challenge Studio V

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 IL/GC 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.


Quantitative Biology

This course combines understanding of biological systems comprising of interacting biomolecules, cells, organelles, organs and living organisms with quantitative and statistical analysis, computational simulations and mathematical models to predict behaviour of complex biological systems. The students will be introduced to current understanding in gene control networks, signalling networks, developmental and evolutionary biology. Real-life application of predictive models will be discussed in context of human and planetary health.


Cell Biology for Engineers

This course will cover essential topics in understanding of cell and tissue biology, biomechanics of cells and subcellular elements (flow, hydrostatic pressure, tension, torsion, flexure, and combined loads), receptor ligand interactions, cellular responses and cell differentiation. The cell biology techniques such as cell culture and banking, phase contrast, fluorescence and confocal microscopy, cell Imaging systems, flow cytometry along with their applications in cellular engineering and clinical diagnostics will be discussed. Genetic engineering of cells, differentiation of stem cells and induced pluripotent cells, measurement of cellular responses, interaction of cells with biomaterials to understand cell adherence, signalling and movement will be covered. This course will introduce tissue engineering and regenerative medicine and the current limitations. In addition, students will gain understanding of laboratory safety practices and appropriate use of Biosafety levels. Laboratory activities will have hands-on experience with culturing of cells, growth kinetics, cell differentiation, cell imaging, engineering of cells, receptor ligand interactions and measurement of cellular responses.


Genetics & Genetic Engineering

This course introduces the principles of Genetics, Mendelian and non-Mendelian inheritance, elucidates nucleic acids as genetic material of living organisms and role of epigenetics in conjunction with structure and function of genes, chromatin, chromosomes and genomes. The concept and health implications of population genetics will be discussed. Topics on genetic disorders and cancer genetics will be covered to exemplify the role of genetic mutations in human disease and susceptibility. Evolution of recombinant DNA technologies Next Gen sequencing technology and their applications in multiple avenues related to human and planetary health will be covered. The students will be introduced to DNA and RNA modifying enzymes, and how they are used in PCR (end-point and real time), cloning, and gene editing technologies and other modifications to engineer recombinant DNA molecule, genomic/cDNA and engineered libraries and their applications in human and planetary health. The evolution of recombinant proteins, monoclonal antibodies, vaccines, cell and gene therapies will be discussed in the current context and opportunities for enhancements and improved access and affordability.


Biosensing & Human Interface

Wearable biosensor technology platforms provides insights into electric signals and biochemical processes in biofluids enabling continuous real time monitoring of biomarkers through non-invasive means with huge implications in patient-centric health care. The course is designed to understand fundamentals of bioelectricity, biometrics, concept of biosensor technology in conjunction with understanding of biochemical composition of body fluids, bioreceptors and physico-chemical transducers. The students will be introduced to the design, function and limitation of wearable biosensors such as wearable electrocardiograms and blood glucose monitors. The course will also explore the applications of wearable biosensors in management of chronic diseases such as diabetes. Laboratory activity will include hands-on experience with design of wearable biosensors.


Application Domain Track II

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.


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 IL/GC 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.


Engineering One Planet

Human activities over a period has profoundly altered the balance of planetary health which in turn is directly linked to human health. In recent times there is a global recognition that a balance is needed among global systems of land, air, water and biodiversity to sustain and preserve life. This has been the genesis of studying the interdependencies of human and planetary health. This course will introduce the concept of planetary health, what are the current impacts due to human activities and the solutions to mitigate the risks at local and global levels. The solutions that will help populations with sustainable ways of living will be discussed and exemplified.


Biomedical Imaging & Analysis

Advances in medical technologies for visualization are supported by the growing field of biomedical imaging technologies and analysis. This course will introduce the imaging methods in biomedicine and clinical diagnostics such as microscopy, ultrasound, MRI, CT, and their application to enable better decision support. The course will cover topics on digital signal processing, data acquisition, enhancements and visualization. Early diagnosis and targeted therapeutic interventions are key in medical treatment of patients. How Computer-aided diagnosis (CADx) using AI and ML algorithms is leading to improved detection diagnosis and decision support will be covered in this course. Imaging informatics and integration of image data with genomics/biomarkers and clinical data are becoming increasingly important to improve efficiency of drug development and therapy regimen. This will be discussed to understand the field and relevance. Case studies will be used to explain the impact of advanced tools for analysis of biomedical imaging data in biomedicine.


Network & Systems Biology

Biological systems and processes are inherently complex and require an integrative approach at molecular level to decipher what keeps us healthy or causes disease. This course is designed to understand this complex network of interactions through an integrative “omics” approach (transcriptomics, proteomics, metabolomics, lipidomics) and effects on a global scale involving numerous different biological molecules in the same time scale. The course includes topics on high-throughput data acquisition, statistical analysis, normalization, differential expression, clustering, enrichment analysis and network construction. The course will introduce the concept of ‘virtual patient’ model and its application in discovery and development of precision and personalized medicine. Case studies on specific diseases e.g., oncology will be discussed.


Free Elective I

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.


Physiological Systems & Digital Twins

This course will focus on bioengineering tools used and needed to model physiological systems and how the models and simulations help understand the system design, plasticity, diseases and preventive and therapeutic interventions. The efforts in development of digital twin models of human organs and how AI can be used to model physiological systems e.g., patient heart will be discussed. The impact on drug discovery, development and personalized medicine will be covered and discussed in the context of current solutions and unmet needs.


Technical Elective I

Sample Electives include: Microbiome in Human & Planetary Health, Gene Editing and Personalized Theranostics, Diagnostic Technologies, Multi-Modal Sensors, Biomanufacturing, Protein and Antibody Engineering, Engineering Biology, Epidemiology and Public Health


Technical Elective II

Sample Electives include: Microbiome in Human & Planetary Health, Gene Editing and Personalized Theranostics, Diagnostic Technologies, Multi-Modal Sensors, Biomanufacturing, Protein and Antibody Engineering, Engineering Biology, Epidemiology and Public Health


Humanities & Social Science Elective I

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 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.


Technical Elective III

Sample Electives include: Microbiome in Human & Planetary Health, Gene Editing and Personalized Theranostics, Diagnostic Technologies, Multi-Modal Sensors, Biomanufacturing, Protein and Antibody Engineering, Engineering Biology, Epidemiology and Public Health


Technical Elective IV

Sample Electives include: Microbiome in Human & Planetary Health, Gene Editing and Personalized Theranostics, Diagnostic Technologies, Multi-Modal Sensors, Biomanufacturing, Protein and Antibody Engineering, Engineering Biology, Epidemiology and Public Health


Technical Elective V

Sample Electives include: Microbiome in Human & Planetary Health, Gene Editing and Personalized Theranostics, Diagnostic Technologies, Multi-Modal Sensors, Biomanufacturing, Protein and Antibody Engineering, Engineering Biology, Epidemiology and Public Health


Humanities & Social Science Elective II

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. 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 Ursheet Parikh, Co-lead of the Engineering Biology Investment Practice at Mayfield Ventures talk about this major. He has been closely involved in the design of this degree
Find the answers to your questions in some of our frequently asked questions by students

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