Incredible music.
In the key of easy.
- The Poly Project Mac Os 7
- The Poly Project Mac Os 8
- The Poly Project Mac Os Catalina
- The Poly Project Mac Os Download
Works fine in 2017, but I also want it to work in 2016, which is also installed on my Mac, but the 'universal installer' provided ignores it, and does not install bonus tools to the older installed version of Maya. Poly is a shareware program for exploring and constructing polyhedra. Poly Pro includes all of the features of Poly and adds the ability to export polyhedral models using standard 3d file formats (3DMF and DXF). Three-dimensional models that have been exported from Poly Pro can be imported into third-party modelling software.
GarageBand is a fully equipped music creation studio right inside your Mac — with a complete sound library that includes instruments, presets for guitar and voice, and an incredible selection of session drummers and percussionists. With Touch Bar features for MacBook Pro and an intuitive, modern design, it’s easy to learn, play, record, create, and share your hits worldwide. Now you’re ready to make music like a pro.
Start making professional‑sounding music right away. Plug in your guitar or mic and choose from a jaw‑dropping array of realistic amps and effects. You can even create astonishingly human‑sounding drum tracks and become inspired by thousands of loops from popular genres like EDM, Hip Hop, Indie, and more.
More sounds, more inspiration.
Plug in your USB keyboard and dive into the completely inspiring and expanded Sound Library, featuring electronic‑based music styles like EDM and Hip Hop. The built‑in set of instruments and loops gives you plenty of creative freedom.
Plug in your USB keyboard and dive into the completely inspiring and expanded Sound Library, featuring electronic‑based music styles like EDM and Hip Hop. The built‑in set of instruments and loops gives you plenty of creative freedom.
The Touch Bar takes center stage.
The Touch Bar on MacBook Pro puts a range of instruments at your fingertips. Use Performance view to turn the Touch Bar into drum pads or a one-octave keyboard for playing and recording.
The Touch Bar on MacBook Pro puts a range of instruments at your fingertips. Use Performance view to turn the Touch Bar into drum pads or a one-octave keyboard for playing and recording.
Plug it in. Tear it up.
Plug in your guitar and choose from a van-load of amps, cabinets, and stompboxes.
Plug in your guitar and choose from a van-load of amps, cabinets, and stompboxes.
Design your dream bass rig.
Customize your bass tone just the way you want it. Mix and match vintage or modern amps and speaker cabinets. You can even choose and position different microphones to create your signature sound.
Customize your bass tone just the way you want it. Mix and match vintage or modern amps and speaker cabinets. You can even choose and position different microphones to create your signature sound.
Drumroll please.
GarageBand features Drummer, a virtual session drummer that takes your direction and plays along with your song. Choose from 28 drummers and three percussionists in six genres.
GarageBand features Drummer, a virtual session drummer that takes your direction and plays along with your song. Choose from 28 drummers and three percussionists in six genres.
Shape your sound. Quickly and easily.
Whenever you’re using a software instrument, amp, or effect, Smart Controls appear with the perfect set of knobs, buttons, and sliders. So you can shape your sound quickly with onscreen controls or by using the Touch Bar on MacBook Pro.
Whenever you’re using a software instrument, amp, or effect, Smart Controls appear with the perfect set of knobs, buttons, and sliders. So you can shape your sound quickly with onscreen controls or by using the Touch Bar on MacBook Pro.
Look, Mom — no wires.
You can wirelessly control GarageBand right from your iPad with the Logic Remote app. Play any software instrument, shape your sound with Smart Controls, and even hit Stop, Start, and Record from across the room.
You can wirelessly control GarageBand right from your iPad with the Logic Remote app. Play any software instrument, shape your sound with Smart Controls, and even hit Stop, Start, and Record from across the room.
Jam with drummers of every style.
Drummer, the virtual session player created using the industry’s top session drummers and recording engineers, features 28 beat‑making drummers and three percussionists. From EDM, Dubstep, and Hip Hop to Latin, Metal, and Blues, whatever beat your song needs, there’s an incredible selection of musicians to play it.
Each drummer has a signature kit that lets you produce a variety of groove and fill combinations. Use the intuitive controls to enable and disable individual sounds while you create a beat with kick, snare, cymbals, and all the cowbell you want. Dangers afloat mac os. If you need a little inspiration, Drummer Loops gives you a diverse collection of prerecorded acoustic and electronic loops that can be easily customized and added to your song.
Powerful synths with shape‑shifting controls.
Get creative with 100 EDM- and Hip Hop–inspired synth sounds. Every synth features the Transform Pad Smart Control, so you can morph and tweak sounds to your liking.
Learn to play
Welcome to the school of rock. And blues. And classical.
Get started with a great collection of built‑in lessons for piano and guitar. Or learn some Multi‑Platinum hits from the actual artists who recorded them. You can even get instant feedback on your playing to help hone your skills.
Take your skills to the next level. From any level.
Choose from 40 different genre‑based lessons, including classical, blues, rock, and pop. Video demos and animated instruments keep things fun and easy to follow.
Choose from 40 different genre‑based lessons, including classical, blues, rock, and pop. Video demos and animated instruments keep things fun and easy to follow.
Teachers with advanced degrees in hit‑making.
Learn your favorite songs on guitar or piano with a little help from the original recording artists themselves. Who better to show you how it’s done?
Learn your favorite songs on guitar or piano with a little help from the original recording artists themselves. Who better to show you how it’s done?
Instant feedback.
Play along with any lesson, and GarageBand will listen in real time and tell you how you’re doing, note for note. Track your progress, beat your best scores, and improve your skills.
Play along with any lesson, and GarageBand will listen in real time and tell you how you’re doing, note for note. Track your progress, beat your best scores, and improve your skills.
Tons of helpful recording and editing features make GarageBand as powerful as it is easy to use. Edit your performances right down to the note and decibel. Fix rhythm issues with a click. Finesse your sound with audio effect plug‑ins. And finish your track like a pro, with effects such as compression and visual EQ.
Go from start to finish. And then some.
Create and mix up to 255 audio tracks. Easily name and reorder your song sections to find the best structure. Then polish it off with all the essentials, including reverb, visual EQ, volume levels, and stereo panning.
Create and mix up to 255 audio tracks. Easily name and reorder your song sections to find the best structure. Then polish it off with all the essentials, including reverb, visual EQ, volume levels, and stereo panning.
Take your best take.
Record as many takes as you like. You can even loop a section and play several passes in a row. GarageBand saves them all in a multi‑take region, so it’s easy to pick the winners.
Record as many takes as you like. You can even loop a section and play several passes in a row. GarageBand saves them all in a multi‑take region, so it’s easy to pick the winners.
Your timing is perfect. Even when it isn’t.
Played a few notes out of time? Simply use Flex Time to drag them into place. You can also select one track as your Groove Track and make the others fall in line for a super‑tight rhythm.
Played a few notes out of time? Simply use Flex Time to drag them into place. You can also select one track as your Groove Track and make the others fall in line for a super‑tight rhythm.
Polish your performance.
Capture your changes in real time by adjusting any of your software instruments’ Smart Controls while recording a performance. You can also fine‑tune your music later in the Piano Roll Editor.
Capture your changes in real time by adjusting any of your software instruments’ Smart Controls while recording a performance. You can also fine‑tune your music later in the Piano Roll Editor.
Touch Bar. A whole track at your fingertips.
The Touch Bar on MacBook Pro lets you quickly move around a project by dragging your finger across a visual overview of the track.
The Touch Bar on MacBook Pro lets you quickly move around a project by dragging your finger across a visual overview of the track.
Wherever you are, iCloud makes it easy to work on a GarageBand song. You can add tracks to your GarageBand for Mac song using your iPhone or iPad when you’re on the road. Or when inspiration strikes, you can start sketching a new song idea on your iOS device, then import it to your Mac to take it even further.
GarageBand for iOS
Play, record, arrange, and mix — wherever you go.
GarageBand for Mac
Your personal music creation studio.
Logic Remote
A companion app for Logic Pro.
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) Sit with me a while mac os.
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)
The Poly Project Mac Os 7
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.
The Poly Project Mac Os 8
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.
COV886 Special Module in Algorithms
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)
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
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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.
The Poly Project Mac Os Catalina
COD893 M.Tech Project Part-II
14 credits (0-0-28)
Pre-requisites: COD 892
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.