The Poly Project Mac OS

. Runs on any Mac with Yosemite or above. Looks and feels just like MS Project, but on your Mac!. Supports files created in versions of MS Project, going all the way back to Microsoft Project 98. Integrated with all major cloud providers, such as Google Drive, iCloud, One Drive, Box, Dropbox, SharePoint Online and Project Online. Ready for large corporate Mac deployments. Chrome OS is partially developed under the open-source Chromium OS project. As with other open-source projects, developers can modify the code from Chromium OS and build their own versions, whereas Chrome OS code is only supported by Google and its partners and only runs on hardware designed for the purpose. I have the Polycom software downloaded on to my Mac. I need to achieve video conference function with only one other user or (I guess) 'endpoint.' In other words, I don't need any complex funtions. My Mac runs an OS Sierra (version 10.12.6) operating system, and I have a Logitech Pro Webcam camera (with microphones), model C930e. The PolyViewer project now provides a simple interface to the extension 'polydb' of polymake written by Silke Horn (see github) to acces the polymake database. To use it you most likely have to adjust some search paths. Poly G7500, Studio X50, and Studio X30 Release Notes Poly VideoOS 3.0.0 Poly, Inc. 7 Directories EN-144594 When uploading contacts from an XML file, the system doesn't display more than one contact with the same name even if the uniqeid attribute is different.

IIT Delhi

Last Updated: 14 Jan 2016 - 06.48.00 IST

COL100 Introduction to Computer Science

4 credits (3-0-2)

Organization of Computing Systems. Concept of an algorithm; termination and correctness. Algorithms to programs: specification, top-down development and stepwise refinement. Problem solving using a functional style; Correctness issues in programming; Efficiency issues in programming; Time and space measures. Procedures, functions. Data types, representational invariants. Encapsulation, abstractions, interaction and modularity. Identifying and exploiting inherent concurrency. Structured style of imperative programming. Introduction to numerical methods. At least one example of large program development.

COL106 Data Structures & Algorithms

5 credits (3-0-4)

Pre-requisites: COL100

Introduction to object-oriented programming through stacks queues and linked lists. Dictionaries; skip-lists, hashing, analysis of collision resolution techniques. Trees, traversals, binary search trees, optimal and average BSTs. Balanced BST: AVL Trees, 2-4 trees, red-balck trees, B-trees. Tries and suffix trees. Priority queues and binary heaps. Sorting: merge, quick, radix, selection and heap sort, Graphs: Breadth first search and connected components. Depth first search in directed and undirected graphs. Dijkstra’s algorithm, directed acyclic graphs and topological sort. Some geometrics theorem, Immerman-Szelepcsényi theorem etc.), Polynomial hierarchy, Boolean circuits (P/poly), Randomized classes (RP, BPP, ZPP, Adleman's Theorem, Gács-Sipser-Lautemann Theorem), Interactive proofs (Arthur-Merlin, IP=PSPACE), Cryptography (one-way functions, pseudorandom generators, zero knowledge), PCP theorem and hardness of approximation, Circuit lower bounds (Hastad's switching lemma), Other topics (#P, Toda's theorem, Average-case complexity, derandomization, pseudorandom construction)

COL754 Approximation Algorithms

3 credits (3-0-0)

Pre-requisites: COL351 OR Equivalent

NP-hardness and approximation algorithms. Different kinds of approximability. Greedy algorithm and local search with applications in facility location, TSP and scheduling. Dynamic programming with applications in knapsack, Euclidean TSP, bin packing. Linear programming, duality and rounding. Applications in facility location, Steiner tree and bin packing. Randomized rounding with applications. Primal-dual algorithms and applications in facility location and network design. Cuts and metrics with applications to multi-commodity flow. Semi-definite programming and applications: max-cut, graph coloring. Hardness of approximation.

COL756 Mathematical Programming

3 credits (3-0-0)

Pre-requisites: COL351 OR Equivalent

Overlaps with: MTL103, MTL704

Linear programming: introduction, geometry, duality, sensitivity analysis. Simplex method, Large scale optimization, network simplex. Ellipsoid method, problems with exponentially many constraints, equivalence of optimization and separation. Convex sets and functions – cones, hyperplanes, norm balls, generalized inequalities and convexity, perspective and conjugate functions. Convex optimization problems – quasi-convex, linear, quadratic, geometric, vector, semi-definite. Duality – Lagrange, geometric interpretation, optimality conditions, sensitivity analysis. Applications to approximation, fitting, statistical estimation, classification. Unconstrained minimization, equality constrained minimization and interior point methods. Integer Programming: formulations, complexity, duality. Lattices, geometry, cutting plane and branch and bound methods. Mixed integer optimization.

COL757 Model Centric Algorithm Design

4 credits (3-0-2)

Pre-requisites: COL351 OR Equivalent

The RAM model and its limitations, Introduction to alternate algorithmic models Parallel models like PRAM and Interconnection networks; Basic problems like Sorting, Merging, Routing, Parallel Prefix and applications, graph algorithms like BFS, Matching

Memory hierarchy models; Caching, Sorting, Merging, FFT, Permutation, Lower bounds Data Structures - searching, Priority queues

Streaming Data models: Distinct items, frequent items, frequency moments, estimating norms, clustering

On line algorithms: competitive ratio, list accessing, paging, k-server, load-balancing, lower-bounds.

COL758 Advanced Algorithms

4 credits (3-0-2)

Pre-requisites: COL351 OR Equivalent

Advanced data structures: self-adjustment, persistence and multidimensional trees. Randomized algorithms: Use of probabilistic inequalities in analysis, Geometric algorithms: Point location, Convex hulls and Voronoi diagrams, Arrangements applications using examples. Graph algorithms: Matching and Flows. Approximation algorithms: Use of Linear programming and primal dual, Local search heuristics. Parallel algorithms: Basic techniques for sorting, searching, merging, list ranking in PRAMs and Interconnection networks.

COL759 Cryptography & Computer Security

3 credits (3-0-0)

Pre-requisites: COL351 MTL106 OR Equivalent

Overlaps with: MTL730

Part 1: Foundations: Perfect secrecy and its limitations, computational security, pseudorandom generators and one time encryption, pseudorandom functions, one way permutations, message authentication and cryptographic hash functions.

Part 2: Basic Constructions and proofs: Some number theory, symmetric key encryption, public key encryption, CPA and CCA security, digital signatures, oblivious transfer, secure multiparty computation.

Part 3: Advanced Topics: Zero knowledge proofs, identity based encryption, broadcast encryption, homomorphic encryption, lattice based cryptography.

COL760 Advanced Data Management

4 credits (3-0-2)

Pre-requisites: COL362 OR Equivalent

Storage and file structures, advanced query processing and optimization for single server databases, distributed data management (including distributed data storage, query processing and transaction management), web-data management (including managing the web-graph and implementation of web-search), big data systems.

COL762 Database Implementation

4 credits (3-0-2)

Pre-requisites: COL362 OR Equivalent

Review of Relational Model, Algebra and SQL, File structures, Constraints and Triggers, System Aspects of SQL, Data Storage, Representing Data Elements, Index, Multi dimensional and Bit-map Indexes, Hashing, Query Execution, Query Compiler.

COL765 Intro. To Logic and Functional Programming

4 credits (3-0-2)

Pre-requisites: COL106 OR Equivalent

Introduction to declarative programming paradigms. The functional style of programming, paradigms of developments of functional programs, use of higher order functionals and pattern-matching. Introduction to lambda calculus. Interpreters for functional languages and abstract machines for lazy and eager lambda calculi, Types, type-checking and their relationship to logic. Logic as a system for declarative programming. The use of pattern-matching and programming of higher order functions within a logic programming framework. Introduction to symbolic processing. The use of resolution and theorem-proving techniques in logic programming. The relationship between logic programming and functional programming.

COL768 Wireless Networks

4 credits (3-0-2)

Pre-requisites: COL334 OR Equivalent

Radio signal propagation, advanced modulation and coding, medium access techniques, self-configurable networks, mesh networks, cognitive radio and dynamic spectrum access networks, TCP over wireless, wireless security, emerging applications.

COL770 Advanced Artificial Intelligence

4 credits (3-0-2)

Pre-requisites: COL106 OR Equivalent

Overlap with: COL333, COL770, ELL789

Philosophy of artificial intelligence, fundamental and advanced search techniques (A*, local search, suboptimal heuristic search, search in AND/OR graphs), constraint optimization, temporal reasoning, knowledge representation and reasoning through propositional and first order logic, modern game playing (UCT), planning under uncertainty (Topological value iteration, LAO*, LRTDP), reinforcement learning, introduction to robotics, introduction to probabilistic graphical models (Bayesian networks, Hidden Markov models, Conditional random fields), machine learning, introduction to information systems (information retrieval, information extraction).

COL772 Natural Language Processing

4 credits (3-0-2)

Pre-requisites: COL106 OR Equivalent

Overlaps with: MTL785

NLP concepts: Tokenization, lemmatization, part of speech tagging, noun phrase chunking, named entity recognition, co-reference resolution, parsing, information extraction, sentiment analysis, question answering, text classification, document clustering, document summarization, discourse, machine translation.

Machine learning concepts: Naïve Bayes, Hidden Markov Models, EM, Conditional Random Fields, MaxEnt Classifiers, Probabilistic Context Free Grammars.

COL774 Machine Learning

4 credits (3-0-2)

Pre-requisites: MTL106 OR Equivalent

Overlaps with: COL341 ELL784, ELL888

Supervised learning algorithms: Linear and Logistic Regression, Gradient Descent, Support Vector Machines, Kernels, Artificial Neural Networks, Decision Trees, ML and MAP Estimates, K-Nearest Neighbor, Naive Bayes, Introduction to Bayesian Networks. Unsupervised learning algorithms: K-Means clustering, Gaussian Mixture Models, Learning with Part

ially Observable Data (EM). Dimensionality Reduction and Principal Component Analysis. Bias Variance Trade-off. Model Selection and Feature Selection. Regularization. Learning Theory. Introduction to Markov Decision Processes. Application to Information Retrieval, NLP, Biology and Computer Vision. Advanced Topics.

COL776 Learning Probabilistic Graphical Models

4 credits (3-0-2)

Pre-requisites: MTL106 OR Equivalent

Basics: Introduction. Undirected and Directed Graphical Models. Bayesian Networks. Markov Networks. Exponential Family Models. Factor Graph Representation. Hidden Markov Models. Conditional Random Fields. Triangulation and Chordal Graphs. Other Special Cases: Chains, Trees. Inference: Variable Elimination (Sum Product and Max-Product). Junction Tree Algorithm. Forward Backward Algorithm (for HMMs). Loopy Belief Propagation. Markov Chain Monte Carlo. Metropolis Hastings. Importance Sampling. Gibbs Sampling. Variational Inference. Learning: Discriminative Vs. Generative Learning. Parameter Estimation in Bayesian and Markov Networks. Structure Learning. EM: Handling Missing Data. Applications in Vision, Web/IR, NLP and Biology. Advanced Topics: Statistical Relational Learning, Markov Logic Networks.

COL780 Computer Vision

4 credits (3-0-2)

Pre-requisites: EC 80

Overlaps with: ELL793

Camera models. Calibration, multi-views projective geometry and invariants. Feature detection, correspondence and tracking. 3D structure/motion estimation. Application of machine learning in object detection and recognition, category discovery, scene and activity interpretation.

COL781 Computer Graphics

4.5 credits (3-0-3)

Pre-requisites: COL106 OR Equivalent

Overlaps with: ELL792

Graphics pipeline; Graphics hardware: Display devices, Input devices; Raster Graphics: line and circle drawing algorithms; Windowing and 2D/3D clipping: Cohen and Sutherland line clipping, Cyrus Beck clipping method; 2D and 3D Geometrical Transformations: scaling, translation, rotation, reflection; Viewing Transformations: parallel and perspective projection; Curves and Surfaces: cubic splines, Bezier curves, B-splines, Parametric surfaces, Surface of revolution, Sweep surfaces, Fractal curves and surfaces; Hidden line/surface removal methods; illuminations model; shading: Gouraud, Phong; Introduction to Ray-tracing; Animation; Programming practices with standard graphics libraries like openGL.

COL783 Digital Image Analysis

4.5 credits (3-0-3)

Pre-requisites: COL106, ELL205 OR Equivalent

Overlap with: ELL715

Digital Image Fundamentals; Image Enhancement in Spatial Domain: Gray Level Transformation, Histogram Processing, Spatial Filters; Image Transforms: Fourier Transform and their properties, Fast Fourier Transform, Other Transforms; Image Enhancement in Frequency Domain; Color Image Processing; Image Warping and Restoration; Image Compression; Image Segmentation: edge detection, Hough transform, region based segmentation; Morphological operators; Representation and Description; Features based matching and Bayes classification; Introduction to some computer vision techniques: Imaging geometry, shape from shading, optical flow; Laboratory exercises will emphasize development and evaluation of image processing methods.

COL786 Advanced Functional Brain Imaging

4 credits (3-0-2)

Introduction to human Neuro-anatomy, Hodgkin Huxley model, overview of brain imaging methods, introduction to magnetic resonance imaging, detailed fMRI, fMRI data analysis methods, general linear model, network analysis, machine learning based methods of analysis.

COL788 Advanced Topics in Embedded Computing

3 credits (3-0-0)

Pre-requisites: COL216, COL331 OR Equivalent

Overlaps with: ELL782

Embedded Platforms , Embedded processor architectures, System initialization, Embedded operating systems (linux) , DSP and graphics acceleration, Interfaces, Device Drivers, Network, Security, Debug support, Performance tuning.

The course would involve substantial programming assignments on embedded platforms.

COS799 Independent Study

3 credits (0-3-0)

The student will be tasked with certain reading assignments and related problem solving in a appropriate area of research in Computer Science under the overall guidance of a CSE Faculty member. The work will be evaluated through term paper.

COL812 System Level Design and Modelling

3 credits (3-0-0)

Pre-requisites: COL719

Embedded systems and system-level design, models of computation, specification languages, hardware/software co-design, system partitioning, application specific processors and memory, low power design.

COL818 Principles of Multiprocessor Systems

4 credits (3-0-2)

Pre-requisites: COL216, COL351, COL331 OR Equivalent

Mutual Exclusion, Coherence and Consistency, Register Constructions , Power of Synchronization Operations , Locks and Monitors, Concurrent queues, Futures and Work-Stealing, Barriers, Basics of Transactional Memory (TM), Regular Hardware TMs, Unbounded HadwareTMs, Software TMs

COL819 Advanced Distributed Systems

4 credits (3-0-2)

Pre-requisites: COL331 COL334 COL380 OR Equivalent

Epidemic/Gossip based algorithms, Peer to peer networks, Distributed hash tables, Synchronization, Mutual exclusion, Leader election, Distributed fault tolerance, Large scale storage systems, Distributed file systems, Design of social networking systems.

COL821 Reconfigurable Computing

3 credits (3-0-0)

Pre-requisites: COL719

FPGA architectures, CAD for FPGAs: overview, LUT mapping, timing analysis, placement and routing, Reconfigurable devices - from fine-grained to coarse-grained devices, Reconfiguration modes and multi-context devices, Dynamic reconfiguration, Compilation from high level languages, System level design for reconfigurable systems: heuristic temporal partitioning and ILP-based temporal partitioning, Behavioral synthesis, Reconfigurable example systems’ tool chains.

COL829 Advanced Computer Graphics

4 credits (3-0-2)

Pre-requisites: COL781

Rendering: Ray tracing, Radiosity methods, Global illumination models, Shadow generation, Mapping, Anti-aliasing, Volume rendering, Geometrical Modeling: Parametric surfaces, Implicit surfaces, Meshes, Animation: spline driven, quarternions, articulated structures (forward and inverse kinematics), deformation- purely geometric, physically-based, Other advanced topics selected from research papers.

COL830 Distributed Computing

3 credits (3-0-0)

Pre-requisites: COL226 OR Equivalent

Models of Distributed Computing; Basic Issues: Causality, Exclusion, Fairness, Independence, Consistency; Specification of Distributed Systems: Transition systems, petri nets, process algebra properties: Safety, Liveness, stability.

COL831 Semantics of Programming Languages

3 credits (3-0-0)

Pre-requisites: COL226, COL352

Study of operational, axiomatic and denotational semantics of procedural languages; semantics issues in the design of functional and logic programming languages, study of abstract data types.

COL832 Proofs and Types

3 credits (3-0-0)

Pre-requisites: COL226, COL352

Syntax and semantic foundations: Ranked algebras, homomorphisms, initial algebras, congruences. First-order logic review: Soundness, completeness, compactness. Herbrand models and Herbrand’s theorem, Horn-clauses and resolution. Natural deduction and the Sequent calculus. Normalization and cut elimination. Lambda-calculus and Combinatory Logic: syntax and operational semantics (beta-eta equivalence), confluence and Church-Rosser property. Introduction to Type theory: The simply-typed lambda-calculus, Intuitionistic type theory. Curry-Howard correspondence. Polymorphism, algorithms for polymorphic type inference, Girard and Reynolds’ System F. Applications: type-systems for programming languages; modules and functors; theorem proving, executable specifications.

COL851 Special Topics in Operating Systems

3 credits (3-0-0)

Pre-requisites: COL331 Or Equivalent

To provide insight into current research problems in the area of operating systems. Topics may include, but are not limited to, OS design, web servers, Networking stack, Virtualization, Cloud Computing, Distributed Computing, Parallel Computing, Heterogeneous Computing, etc.

COL852 Special Topics in COMPILER DESIGN

3 credits (3-0-0)

Pre-requisites: COL728/COL729

Special topic that focuses on state of the art and research problems of importance in this area.

COL860 Special Topics in Parallel Computation

3 credits (3-0-0)

The course will focus on research issues in areas like parallel computation models, parallel algorithms, Parallel Computer architectures and interconnection networks, Shared memory parallel architectures and programming with OpenMP and Ptheards, Distributed memory message-passing parallel architectures and programming, portable parallel message-passing programming using MPI. This will also include design and implementation of parallel numerical and non-numerical algorithms for scientific and engineering, and commercial applications. Performance evaluation and benchmarking high-performance computers.

COL861 Special Topics in Hardware Systems

3 credits (3-0-0)

Under this topic one of the following areas will be covered: Fault Detection and Diagnosability. Special Architectures. Design Automation Issues. Computer Arithmetic, VLSI.

COL862 Special Topics in Software Systems

3 credits (3-0-0)

Special topic that focuses on state of the art and research problems of importance in this area.

COL863 Special Topics in Theoretical Computer Science

3 credits (3-0-0)

Pre-requisites: COL351

Under this topic one of the following areas will be covered: Design and Analysis of Sequential and Parallel Algorithms. Complexity issues, Trends in Computer Science Logic, Quantum Computing and Bioinformatics, Theory of computability. Formal Languages. Semantics and Verification issues.

COL864 Special Topics in Artificial Intelligence

3 credits (3-0-0)

Pre-requisites: COL333 / COL671 / Equivalent

Potential topics or themes which may be covered (one topic per offering) include: information extraction, industrial applications of AI, advanced logic-based AI, Markov Decision Processes, statistical relational learning, etc.

COL865 Special Topics in Computer Applications

3 credits (3-0-0)

Pre-requisites: Permission of the Instructor

Special topic that focuses on special topics and research problems of importance in this area.

COL866 Special Topics in Algorithms

3 credits (3-0-0)

Pre-requisites: COL 351 OR Equivalent

The course will focus on specialized topics in areas like Computational Topology, Manufacturing processes, Quantum Computing, Computational Biology, Randomized algorithms and other research intensive topics.

COL867 Special Topics in High Speed Networks

3 credits (3-0-0)

Pre-requisites: COL334 OR COL672

The course will be delivered through a mix of lectures and paper reading seminars on advanced topics in Computer Networks. Hands-on projects will be conceptualized to challenge students to take up current research problems in areas such as software defined networking, content distribution, advanced TCP methodologies, delay tolerant networking, data center networking, home networking, green networking, clean state architecture for the Internet, Internet of things, etc.

COL868 Special topics in Database Systems

3 credits (3-0-0)

Pre-requisites: COL334 / COL672 / Equivalent

The contents would include specific advanced topics in Database Management Systems in which research is currently going on in the department. These would be announced every time the course is offered.

COL869 Special topics in Concurrency

3 credits (3-0-0)

The course will focus on research issues in concurrent, distributed and mobile computations. Models of Concurrent, Distributed and Mobile computation. Process calculi, Event Structures, Petri Nets an labeled transition systems. Implementations of concurrent and mobile, distributed programming languages. Logics and specification models for concurrent and mobile systems.Verification techniques and algorithms for model checking.Type systems for concurrent/mobile programming languages.Applications of the above models and techniques.

COL870 Special Topics in Machine Learning

3 credits (3-0-0)

Pre-requisites: COL341 OR Equivalent

Contents may vary based on the instructor’s expertise and interests within the broader area of Machine Learning. Example topics include (but not limiting to) Statistical Relational Learning, Markov Logic, Multiple Kernel Learning, Multi-agent Systems, Multi-Class Multi-label Learning, Deep Learning, Sum-Product Networks, Active and Semi-supervised Learning, Reinforcement Learning, Dealing with Very High-Dimensional Data, Learning with Streaming Data, Learning under Distributed Architecture.

COL871 Special Topics in programming languages & Compilers

3 credits (3-0-0)

Pre-requisites: COL728 / COL729 / Equivalent

Contents may vary based on the instructor’s interests within the broader area of Programming Languages and Compilers.

COL872 Special Topics in Cryptography

3 credits (3-0-0)

Pre-requisites: COL759 OR Equivalent

Contents may vary based on the instructor’s interests within the broader area of Cryptography. Examples include CCA secure encryption, multiparty computation, leakage resilient cryptography, broadcast encryption, fully homomorphic encryption, obfuscation, functional encryption, zero knowledge, private information retrieval, byzantine agreement, cryptography against extreme attacks etc.

COV877 Special Module on Visual Computing

1 credit (1-0-0)

The course will be a seminar-based course where the instructor would present topics in a selected theme in the area of visual computing through research papers. Students will also be expected to participate in the seminar.

COV878 Special Module in Machine Learning

1 credit (1-0-0)

Contents may vary based on the instructor’s expertise and interests within the broader area of Machine Learning. Example topics include (but not limiting to) Statistical Relational Learning, Markov Logic, Multiple Kernel Learning, Multi-agent Systems, Multi-Class Multi-label Learning, Deep Learning, Sum-Product Networks, Active and Semi-supervised Learning, Reinforcement Learning, Dealing with Very High-Dimensional Data, Learning with Streaming Data, Learning under Distributed Architecture.

COV879 Special Module in Financial Algorithms

1 credits (1-0-0)

Pre-requisites: MTL106 OR Equivalent

Overlap with: MTL 732 & MTL 733

Special module that focuses on special topics and research problems of importance in this area.

COV880 Special Module in Parallel Computation

1 credit (1-0-0)

Pre-requisites: Permission of Instructor

Special module that focuses on special topics and research problems of importance in this area.

COV881 Special Module in Hardware Systems

1 credit (1-0-0)

Pre-requisites: Permission of Instructor

Special module that focuses on special topics and research problems of importance in this area.

COV882 Special Module in Software Systems

1 credit (1-0-0)

Special module that focuses on special topics and research problems of importance in this area.

COV883 Special Module in Theoretical Computer Science

1 credit (1-0-0)

Pre-requisites: COL 351 OR equivalent

Special module that focuses on special topics and research problems of importance in this area.

COV884 Special Module in Artificial Intelligence

1 credit (1-0-0)

Pre-requisites: COL333 / COL671 / Equivalent

Special module that focuses on special topics and research problems of importance in this area.

COV885 Special Module in Computer Applications

1 credit (1-0-0)

Special module that focuses on special topics and research problems of importance in this area.

The Poly Project Mac Os Pro

COV886 Special Module in Algorithms

The Poly Project Mac Os 8

1 credit (1-0-0)

Pre-requisites: COL351 OR Equivalent

Special module that focuses on special topics and research problems of importance in this area.

COV887 Special Module in High Speed Networks

1 credit (1-0-0)

The Poly Project Mac Os X

Pre-requisites: COL 334 OR COl 672

The course will be delivered through a mix of lectures and paper reading seminars on advanced topics in Computer Networks. Students will be introduced to topics such as software defined networking, content distribution, advanced TCP methodologies, delay tolerant networking, data center networking, home networking, green networking, clean state architecture for the Internet, Internet of things, etc.

COV888 Special Module in Database Systems

1 credit (1-0-0)

Pre-requisites: COL362 OR COL632 OR Equivalent

Potential topics or themes which may be covered (one topic per offering) include: data mining, big data management, information retrieval and database systems, semantic web data management, etc

COV889 Special Module in Concurrency

1 credit (1-0-0)

Pre-requisites: MTL106 OR Equivalent

Special module that focuses on special topics and research problems of importance in this area.

COD891 M.Tech Minor Project

3 credits (0-0-6)

Research and development oriented projects based on problems of practical and theoretical interest. Evaluation done based on periodic presentations, student seminars, written reports, and evaluation of the developed system (if applicable). Students are generally expected to work towards the goals and mile stones set for Minor Project COP 891.

COD892 M.Tech Project Part-I

7 credits (0-0-14)

It is expected that the problem specification and milestones to be achieved in solving the problem are clearly specified. Survey of the related area should be completed. This project spans also the course COP892. Hence it is expected that the problem specification and the milestones to be achieved in solving the problem are clearly specified.

COD893 M.Tech Project Part-II

14 credits (0-0-28)

Pre-requisites: COD 892

The Poly Project Mac Os 7

The student(s) who work on a project are expected to work towards the goals and milstones set in COP893. At the end there would be a demonstration of the solution and possible future work on the same problem. A dissertation outlining the entire problem, including a survey of literature and the various results obtained along with their solutions is expected to be produced by each student.

The Poly Project Mac Os X

The Poly Project Mac OS