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For detailed syllabus of all the other subjects of EIE 6th Sem, 2021 curriculum do visit EIE 6th Sem subject syllabuses for 2021 regulation. For Electronics & Instrumentation Engineering 6th Sem semesters scheme and subjects, refer to EIE 6th Sem 2021 regulation scheme. The scheme details of Professional Elective-VIII for EIE 6th Sem is as follows.

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For the results of Electronics & Instrumentation Engineering 6th Sem, kindly visit EIE 6th Sem direct results link.

For exam time table of Electronics & Instrumentation Engineering (EIE), kindly visit Anna University exam timetables.

For Electronics & Instrumentation Engineering (EIE) notices, kindly visit Anna University notices.

Download the iStudy App for all syllabus and other updates.

For updated syllabus of Electronics & Instrumentation Engineering (EIE) 2021, kindly visit EIE updated syllabus.

Wishing you great luck ahead.

For Electronics & Instrumentation Engineering 6th Sem scheme and its subjects, do visit EIE 6th Sem 2021 regulation scheme. For Professional Elective-VIII scheme and its subjects refer to EIE Professional Elective-VIII syllabus scheme. The detailed syllabus of java programming is as follows.

Course Objectives:

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Unit I

JAVA BASCIS
Object oriented programming concepts – objects – classes – methods and messages -abstraction and encapsulation – inheritance – abstract classes – polymorphism.- Objects and classes in Java – defining classes – methods – access specifiers – static members – constructors – finalize method.

Unit II

ARRAYS
Arrays – Strings – Packages – Java-Doc comments — Inheritance – class hierarchy -polymorphism – dynamic binding – final keyword – abstract classes.

Unit III

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Unit IV

EVENT, EXCEPTION HANDLING
Basics of event handling – event handlers – adapter classes – actions – mouse events – AWT event hierarchy – introduction to Swing – Model-View-Controller design pattern – buttons – layout management – Swing Components – exception handling – exception hierarchy – throwing and catching exceptions.

Unit V

GENERIC PROGRAMMING
Motivation for generic programming – generic classes – generic methods – generic code and virtual machine – inheritance and generics – reflection and generics – Multi-threaded programming – interrupting threads – thread states – thread properties – thread synchronization – Executors -synchronizers.

Skill Development Activities

(Group Seminar/Mini Project/Assignment/Content Preparation / Quiz/ Surprise Test / Solving GATE questions/ etc)

1. Fundamentals of java
2. Concepts of array
3. Basics of programming
4. Handling of unexpected error
5. Introduction to generic programming

Course Outcomes:

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Text Books:

1. Cay S. Horstmann and Gary Cornell, �Core Java: Volume I – Fundamentals�, 8th Edition, Sun Microsystems Press, 2008.

Reference Books:

1. K. Arnold and J. Gosling, �The JAVA programming language�, Third edition, PearsonEducation, 2000.
2. Timothy Budd, �Understanding Object-oriented programming with Java�, UpdatedEdition, Pearson Education, 2000.

List of Open Source Software/ Learning Website:

1. https://www.w3schools.com/java/
2. https://www.geeksforgeeks.org/string-arrays-in-java/
3. https://www.edureka.co/blog/string-array-in-java/
4. https://www.javatpoint.com/generics-in-java

For detailed syllabus of all the other subjects of Electronics & Instrumentation Engineering 6th Sem, visit EIE 6th Sem subject syllabuses for 2021 regulation.

For all Electronics & Instrumentation Engineering results, visit Anna University EIE all semester results direct link.

For Electronics & Instrumentation Engineering 6th Sem scheme and its subjects, do visit EIE 6th Sem 2021 regulation scheme. For Professional Elective-VIII scheme and its subjects refer to EIE Professional Elective-VIII syllabus scheme. The detailed syllabus of deep and reinforcement learning is as follows.

Course Objectives:

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Unit I

MACHINE LEARNING BASICS
Learning algorithms, Maximum likelihood estimation, Building machine learning algorithm, Neural Networks Multilayer Perceptron, Back-propagation algorithm and its variants Stochastic gradient decent, Curse of Dimensionality.

Unit II

INTRODUCTION TO DEEP LEARNING & ARCHITECTURES
Machine Learning Vs. Deep Learning, Representation Learning, Width Vs. Depth of Neural Networks, Activation Functions: RELU, LRELU, ERELU, Unsupervised Training of Neural Networks, Restricted Boltzmann Machines, Auto Encoders.

Unit III

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Unit IV

SEQUENCE MODELLING – RECURRENT AND RECURSIVE NETS
Recurrent Neural Networks, Bidirectional RNNs – Encoder-decoder sequence to sequence architechures – BPTT for training RNN, Long Short Term Memory Networks.

Unit V

AUTO ENCODERS AND DEEP GENERATIVE MODELS
Deep Belief networks – Boltzmann Machines – Deep Boltzmann Machine – Generative AdversialNetworks.

Skill Development Activities

(Group Seminar/Mini Project/Assignment/Content Preparation / Quiz/ Surprise Test / Solving GATE questions/ etc)

1. Fundamentals of machine learning
2. Fundamentals of deep learning
3. Realization and understanding of CNN
4. Time series forecasting for data
5. Generating of synthetic images

Course Outcomes:

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Text Books:

1. Ian Goodfellow, Yoshua Bengio and Aaron Courville, � Deep Learning�, MIT Press, 2017.
2. Josh Patterson, Adam Gibson “Deep Learning: A Practitioner’s Approach”, O’Reilly Media, 2017.

Reference Books:

1. Umberto Michelucci �Applied Deep Learning. A Case-based Approach to Understanding Deep Neural Networks� Apress, 2018.
2. Kevin P. Murphy “Machine Learning: A Probabilistic Perspective”, The MIT Press, 2012.
3. Ethem Alpaydin,”Introduction to Machine Learning�, MIT Press, Prentice Hall of India, Third Edition 2014.
4. Rezaul Karim, Ahmed Menshawy “Deep Learning with TensorFlow: Explore neural networks with Python”, Packt Publisher, 2017.

List of Open Source Software/ Learning Website:

1. https://www.techtarget.com/searchenterpriseai/definition/machine-learning-ML
2. https://www.techtarget.com/searchenterpriseai/definition/deep-learning-deep-neural-network
3. https://www.simplilearn.com/tutorials/deep-learning-tutorial/rnn
4. https://machinelearningmastery.com/what-are-generative-adversarial-networks-gans/

For detailed syllabus of all the other subjects of Electronics & Instrumentation Engineering 6th Sem, visit EIE 6th Sem subject syllabuses for 2021 regulation.

For all Electronics & Instrumentation Engineering results, visit Anna University EIE all semester results direct link.

For Electronics & Instrumentation Engineering 6th Sem scheme and its subjects, do visit EIE 6th Sem 2021 regulation scheme. For Professional Elective-VIII scheme and its subjects refer to EIE Professional Elective-VIII syllabus scheme. The detailed syllabus of block chain technology is as follows.

Course Objectives:

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Unit I

INTRODUCTION
Basic Cryptographic primitives used in Blockchain -Secure- CollisionResistant hash functions -Digital signature – Public key cryptosystems – Zeroknowledge proof systems – Need for Distributed Record Keeping – Modelling faults and adversaries- Byzantine Generals problem – Briefing of Consensus algorithms and their scalability problems – Why Nakamoto Came up with Blockchain based cryptocurrency.

Unit II

TECHNOLOGIES BORROWED IN BLOCKCHAIN
Technologies Borrowed in Blockchain -hash pointers- Consensus- Byzantine Models of fault tolerance- Digital cash etc.- Bitcoin blockchain – Wallet – Blocks – Merkley Tree – hardness of mining – Transaction verifiability – Anonymity – forks – Double spending – Bitcoin- the challenges and solutions.

Unit III

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Unit IV

ETHEREUM
Ethereum -Ethereum Virtual Machine (EVM) -Wallets for Ethereum -Solidity – Smart Contracts -The Turing Completeness of Smart Contract Languages and verification challenges- Using smart contracts to enforce legal contracts Comparing Bitcoin scripting vs. Ethereum Smart Contracts-Some attacks on smart contracts..

Unit V

HYPERLEDGER FABRIC
Hyperledger fabric- the plug and play platform and mechanisms in permissioned block chain -Beyond Cryptocurrency – applications of block chain in cyber security- integrity of information- EGovernance and other contract enforcement mechanisms – Limitations of block chain as a technology and myths vs reality of blockchain technology.

Skill Development Activities

(Group Seminar/Mini Project/Assignment/Content 10 Preparation / Quiz/ Surprise Test / Solving GATE questions/ etc)

1. Fundamentals of blockchain technology
2. Understanding of technologies in block chain
3. Interpretation of models in block chain
4. Platforms to build decentralized applications
5. Demonstration of hyperledger fabric

Course Outcomes:

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Text Books:

1. S.Shukla,M.Dhawan,S.Sharma,S. Venkatesan �Blockchain Technology: Cryptocurrency and Applications� ,Oxford University Press 2019 .
2. Arvind Narayanan, Joseph Bonneau,Edward Felten,Andrew Miller and Steven Goldfeder, �Bitcoin and cryptocurrency technologies: a comprehensive introduction�,Princeton University Press,2016.

Reference Books:

• Joseph Bonneau et al, SoK: �Research perspectives and challenges for Bitcoin and cryptocurrency�, IEEE Symposium on security and Privacy, 2015
• J.A.Garay et al, �The bitcoin backbone protocol – analysis and applications�, EUROCRYPT 2015,Volume 2.
• R.Pass et al, �Analysis of Blockchain protocol in Asynchronous networks�, EUROCRYPT 2017.
• Passet al,� Fruitchain- a fair blockchain�, PODC 2017

List of Open Source Software/ Learning Website:

1. https://www.cbinsights.com/research/what-is-blockchain-technology/
2. https://101blockchains.com/blockchain-business-models/
3. https://en.wikipedia.org/wiki/Ethereum
4. https://hyperledger-fabric.readthedocs.io/en/release-2.2/whatis.html

For detailed syllabus of all the other subjects of Electronics & Instrumentation Engineering 6th Sem, visit EIE 6th Sem subject syllabuses for 2021 regulation.

For all Electronics & Instrumentation Engineering results, visit Anna University EIE all semester results direct link.

For Electronics & Instrumentation Engineering 6th Sem scheme and its subjects, do visit EIE 6th Sem 2021 regulation scheme. For Professional Elective-VIII scheme and its subjects refer to EIE Professional Elective-VIII syllabus scheme. The detailed syllabus of cloud services management is as follows.

Course Objectives:

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Unit I

CLOUD SERVICE MANAGEMENT FUNDAMENTALS
Cloud Ecosystem, The Essential Characteristics, Basics of Information Technology Service Management and Cloud Service Management, Service Perspectives, Cloud Service Models, Cloud Service Deployment Models

Unit II

CLOUD SERVICES STRATEGY
Cloud Strategy Fundamentals, Cloud Strategy Management Framework, Cloud Policy, Key Driver for Adoption, Risk Management, IT Capacity and Utilization, Demand and Capacity matching, Demand Queueing, Change Management, Cloud Service Architecture

Unit III

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Unit IV

CLOUD SERVICE ECONOMICS
Pricing models for Cloud Services, Freemium, Pay Per Reservation, Pay per User, Subscription based Charging, Procurement of Cloud-based Services, Capex vs Opex Shift, Cloud service Charging, Cloud Cost Models

Unit V

CLOUD SERVICE GOVERNANCE & VALUE
IT Governance Definition, Cloud Governance Definition, Cloud Governance Framework, Cloud Governance Structure, Cloud Governance Considerations, Cloud Service Model Risk Matrix, Understanding Value of Cloud Services, Measuring the value of Cloud Services, Balanced Scorecard, Total Cost of Ownership

Course Outcomes:

1. Exhibit cloud-design skills to build and automate business solutions using cloud technologies.
2. Possess Strong theoretical foundation leading to excellence and excitement towards adoption of cloud-based services
3. Solve the real world problems using Cloud services and technologies

Practical Excercises

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Text Books:

1. Cloud Service Management and Governance: Smart Service Management in Cloud Era by Enamul Haque, Enel Publications
2. Cloud Computing: Concepts, Technology & Architecture by Thomas Erl, Ricardo Puttini, Zaigham Mohammad 2013
3. Cloud Computing Design Patterns by Thomas Erl, Robert Cope, Amin Naserpour

Reference Books:

1. Economics of Cloud Computing by Praveen Ayyappa, LAP Lambert Academic Publishing
2. Mastering Cloud Computing Foundations and Applications Programming Rajkumar Buyya, Christian Vechhiola, S. Thamarai Selvi

For detailed syllabus of all the other subjects of Electronics & Instrumentation Engineering 6th Sem, visit EIE 6th Sem subject syllabuses for 2021 regulation.

For all Electronics & Instrumentation Engineering results, visit Anna University EIE all semester results direct link.

For Electronics & Instrumentation Engineering 6th Sem scheme and its subjects, do visit EIE 6th Sem 2021 regulation scheme. For Professional Elective-VIII scheme and its subjects refer to EIE Professional Elective-VIII syllabus scheme. The detailed syllabus of computer vision is as follows.

Course Objectives:

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Unit I

INTRODUCTION TO IMAGE FORMATION AND PROCESSING
Computer Vision – Geometric primitives and transformations – Photometric image formation – The digital camera – Point operators – Linear filtering – More neighborhood operators – Fourier transforms – Pyramids and wavelets – Geometric transformations – Global optimization.

Unit II

FEATURE DETECTION, MATCHING AND SEGMENTATION
Points and patches – Edges – Lines – Segmentation – Active contours – Split and merge – Mean shift and mode finding – Normalized cuts – Graph cuts and energy-based methods.

Unit III

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Unit IV

3D RECONSTRUCTION
Shape from X – Active rangefinding – Surface representations – Point-based representations-Volumetric representations – Model-based reconstruction – Recovering texture maps and albedosos.

Unit V

IMAGE-BASED RENDERING AND RECOGNITION
View interpolation Layered depth images – Light fields and Lumigraphs – Environment mattes -Video-based rendering-Object detection – Face recognition – Instance recognition – Category recognition – Context and scene understanding- Recognition databases and test sets.

Laboratory Experiments:

Software needed:
OpenCV computer vision Library for OpenCV in Python / PyCharm or C++ / Visual Studio or or equivalent

• OpenCV Installation and working with Python
• Basic Image Processing – loading images, Cropping, Resizing, Thresholding, Contour analysis, Bolb detection
• Image Annotation – Drawing lines, text circle, rectangle, ellipse on images
• Image Enhancement – Understanding Color spaces, color space conversion, Histogram equialization, Convolution, Image smoothing, Gradients, Edge Detection
• Image Features and Image Alignment – Image transforms – Fourier, Hough, Extract ORB Image features, Feature matching, cloning, Feature matching based image alignment
• Image segmentation using Graphcut / Grabcut
• Camera Calibration with circular grid
• Pose Estimation
• 3D Reconstruction – Creating Depth map from stereo images
• Object Detection and Tracking using Kalman Filter, Camshift
1. docs.opencv.org
2. https://opencv.org/opencv-free-course/

Course Outcomes:

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Text Books:

1. Richard Szeliski, “Computer Vision: Algorithms and Applications”, Springer- Texts in Computer Science, Second Edition, 2022.
2. Computer Vision: A Modern Approach, D. A. Forsyth, J. Ponce, Pearson Education, Second Edition, 2015.

Reference Books:

1. Richard Hartley and Andrew Zisserman, Multiple View Geometry in Computer Vision, Second Edition, Cambridge University Press, March 2004.
2. Christopher M. Bishop; Pattern Recognition and Machine Learning, Springer, 2006
3. E. R. Davies, Computer and Machine Vision, Fourth Edition, Academic Press, 2012.

For detailed syllabus of all the other subjects of Electronics & Instrumentation Engineering 6th Sem, visit EIE 6th Sem subject syllabuses for 2021 regulation.

For all Electronics & Instrumentation Engineering results, visit Anna University EIE all semester results direct link.

For Electronics & Instrumentation Engineering 6th Sem scheme and its subjects, do visit EIE 6th Sem 2021 regulation scheme. For Professional Elective-VIII scheme and its subjects refer to EIE Professional Elective-VIII syllabus scheme. The detailed syllabus of computer architecture is as follows.

Course Objectives:

Download the iStudy App for all syllabus and other updates.

Unit I

BASIC STRUCTURE OF A COMPUTER SYSTEM
Functional Units – Basic Operational Concepts – Performance – Instructions: Language of the Computer – Operations, Operands – Instruction representation – Logical operations – decision making – MIPS Addressing.

Unit II

ARITHMETIC FOR COMPUTERS
Addition and Subtraction – Multiplication – Division – Floating Point Representation – Floating Point Operations – Subword Parallelism

Unit III

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Unit IV

PARALLELISIM
Parallel processing challenges – Flynn�s classification – SISD, MIMD, SIMD, SPMD, and Vector Architectures – Hardware multithreading – Multi-core processors and other Shared Memory Multiprocessors – Introduction to Graphics Processing Units, Clusters, Warehouse Scale Computers and other Message-Passing Multiprocessors.

Unit V

MEMORY & I/O SYSTEMS
Memory Hierarchy – memory technologies – cache memory – measuring and improving cache performance – virtual memory, TLB�s – Accessing I/O Devices – Interrupts – Direct Memory Access – Bus structure – Bus operation – Arbitration – Interface circuits – USB.

Skill Development Activities

(Group Seminar/Mini Project/Assignment/Content 10 Preparation / Quiz/ Surprise Test / Solving GATE questions/ etc)

1. Fundamentals of computer architecture
2. Basic arithmetical operations
3. Organization of computer system
4. Analysis of challenges parallel processing
5. Interfacing and storage systems in the computer

Course Outcomes:

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Text Books:

1. David A. Patterson and John L. Hennessy, Computer Organization and Design: The Hardware/Software Interface, Fifth Edition, Morgan Kaufmann / Elsevier, 2014.
2. Carl Hamacher, Zvonko Vranesic, Safwat Zaky and Naraig Manjikian, Computer Organization and Embedded Systems, Sixth Edition, Tata McGraw Hill, 2012.

Reference Books:

1. William Stallings, Computer Organization and Architecture – Designing for Performance, Eighth Edition, Pearson Education, 2010.
2. John P. Hayes, Computer Architecture and Organization, Third Edition, Tata McGraw Hill, 2012.
3. John L. Hennessey and David A. Patterson, Computer Architecture – A Quantitative Approachll, Morgan Kaufmann / Elsevier Publishers, Fifth Edition, 2012.

List of Open Source Software/ Learning Website:

1. https://exploringbits.com/basic-structure-of-computer-system/
2. https://web.ece.ucsb.edu/~parhami/pubs_folder/parh02-arith-encycl-infosys.pdf
3. https://www.heavy.ai/technical-glossary/parallel
4. https://www.srividyaengg.ac.in/coursematerial/CSE/104425.pdf

For detailed syllabus of all the other subjects of Electronics & Instrumentation Engineering 6th Sem, visit EIE 6th Sem subject syllabuses for 2021 regulation.

For all Electronics & Instrumentation Engineering results, visit Anna University EIE all semester results direct link.

For Electronics & Instrumentation Engineering 6th Sem scheme and its subjects, do visit EIE 6th Sem 2021 regulation scheme. For Professional Elective-VIII scheme and its subjects refer to EIE Professional Elective-VIII syllabus scheme. The detailed syllabus of augmented reality or virtual reality is as follows.

Course Objectives:

Download the iStudy App for all syllabus and other updates.

Unit I

INTRODUCTION
Introduction to Virtual Reality and Augmented Reality – Definition – Introduction to Trajectories and Hybrid Space-Three I’s of Virtual Reality – Virtual Reality Vs 3D Computer Graphics – Benefits of Virtual Reality – Components of VR System – Introduction to AR-AR Technologies-Input Devices -3D Position Trackers – Types of Trackers – Navigation and Manipulation Interfaces – Gesture Interfaces – Types of Gesture Input Devices – Output Devices – Graphics Display – Human Visual System – Personal Graphics Displays – Large Volume Displays – Sound Displays – Human Auditory System.

Unit II

VR MODELING
Modeling – Geometric Modeling – Virtual Object Shape – Object Visual Appearance – Kinematics Modeling – Transformation Matrices – Object Position – Transformation Invariants -Object Hierarchies – Viewing the 3D World – Physical Modeling – Collision Detection – Surface Deformation – Force Computation – Force Smoothing and Mapping – Behavior Modeling – Model Management.

Unit III

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Unit IV

APPLICATIONS
Human Factors in VR – Methodology and Terminology – VR Health and Safety Issues – VR and Society-Medical Applications of VR – Education, Arts and Entertainment – Military VR Applications – Emerging Applications of VR – VR Applications in Manufacturing – Applications of VR in Robotics – Information Visualization – VR in Business – VR in Entertainment – VR in Education.

Unit V

AUGMENTED REALITY
Introduction to Augmented Reality-Computer vision for AR-Interaction-Modelling and AnnotationNavigation-Wearable devices

Practical Excercises

1. Study of tools like Unity, Maya, 3DS MAX, AR toolkit, Vuforia and Blender.
2. Use the primitive objects and apply various projection types by handling camera.
3. Download objects from asset store and apply various lighting and shading effects.
4. Model three dimensional objects using various modelling techniques and apply textures over them.
5. Create three dimensional realistic scenes and develop simple virtual reality enabled mobile applications which have limited interactivity.
6. Add audio and text special effects to the developed application.
7. Develop VR enabled applications using motion trackers and sensors incorporating full haptic interactivity.
8. Develop AR enabled applications with interactivity like E learning environment, Virtual walkthroughs and visualization of historic places.
9. Develop AR enabled simple applications like human anatomy visualization, DNA/RNA structure visualization and surgery simulation.
10. Develop simple MR enabled gaming applications.

Course Outcomes:

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Text Books:

1. Charles Palmer, John Williamson, “Virtual Reality Blueprints: Create compelling VR experiences for mobile”, Packt Publisher, 2018
2. Dieter Schmalstieg, Tobias Hollerer, “Augmented Reality: Principles & Practice”, Addison Wesley, 2016
3. John Vince, “Introduction to Virtual Reality”, Springer-Verlag, 2004.
4. William R. Sherman, Alan B. Craig: Understanding Virtual Reality – Interface, Application, Design”, Morgan Kaufmann, 2003

For detailed syllabus of all the other subjects of Electronics & Instrumentation Engineering 6th Sem, visit EIE 6th Sem subject syllabuses for 2021 regulation.

For all Electronics & Instrumentation Engineering results, visit Anna University EIE all semester results direct link.

For Electronics & Instrumentation Engineering 6th Sem scheme and its subjects, do visit EIE 6th Sem 2021 regulation scheme. For Professional Elective-VIII scheme and its subjects refer to EIE Professional Elective-VIII syllabus scheme. The detailed syllabus of foundations of data science is as follows.

Course Objectives:

Download the iStudy App for all syllabus and other updates.

Unit I

INTRODUCTION
Data Science: Benefits and uses – facets of data – Data Science Process: Overview – Defining research goals – Retrieving data – Data preparation – Exploratory Data analysis – build the model- presenting findings and building applications – Data Mining – Data Warehousing – Basic Statistical descriptions of Data

Unit II

DESCRIBING DATA
Types of Data – Types of Variables -Describing Data with Tables and Graphs -Describing Data with Averages – Describing Variability – Normal Distributions and Standard (z) Scores

Unit III

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Unit IV

PYTHON LIBRARIES FOR DATA WRANGLING
Basics of Numpy arrays -aggregations -computations on arrays -comparisons, masks, boolean logic – fancy indexing – structured arrays – Data manipulation with Pandas – data indexing and selection – operating on data – missing data – Hierarchical indexing – combining datasets -aggregation and grouping – pivot tables

Unit V

DATA VISUALIZATION
Importing Matplotlib – Line plots – Scatter plots – visualizing errors – density and contour plots -Histograms – legends – colors – subplots – text and annotation – customization – three dimensional plotting – Geographic Data with Basemap – Visualization with Seaborn.

Course Outcomes:

At the end of this course, the students will be able to:

1. Define the data science process
2. Understand different types of data description for data science process
3. Gain knowledge on relationships between data
4. Use the Python Libraries for Data Wrangling
5. Apply visualization Libraries in Python to interpret and explore data

Text Books:

Download the iStudy App for all syllabus and other updates.

Reference Books:

1. Allen B. Downey, “Think Stats: Exploratory Data Analysis in Python”, Green Tea Press,2014.

For detailed syllabus of all the other subjects of Electronics & Instrumentation Engineering 6th Sem, visit EIE 6th Sem subject syllabuses for 2021 regulation.

For all Electronics & Instrumentation Engineering results, visit Anna University EIE all semester results direct link.

Download the iStudy App for all syllabus and other updates.

For detailed syllabus of all the other subjects of EIE 6th Sem, 2021 curriculum do visit EIE 6th Sem subject syllabuses for 2021 regulation. For Electronics & Instrumentation Engineering 6th Sem semesters scheme and subjects, refer to EIE 6th Sem 2021 regulation scheme. The scheme details of Professional Elective-VII for EIE 6th Sem is as follows.

Don’t forget to download iStudy App for the latest syllabus, results, class timetable and many more features. In case of questions, don’t feel shy to leave a comment or leave feedback in the iStudy app for faster response.

For the results of Electronics & Instrumentation Engineering 6th Sem, kindly visit EIE 6th Sem direct results link.

For exam time table of Electronics & Instrumentation Engineering (EIE), kindly visit Anna University exam timetables.

For Electronics & Instrumentation Engineering (EIE) notices, kindly visit Anna University notices.

Download the iStudy App for all syllabus and other updates.

For updated syllabus of Electronics & Instrumentation Engineering (EIE) 2021, kindly visit EIE updated syllabus.

Wishing you great luck ahead.