Computer Science & Eng. — 8th Semester Syllabus

Module 1: (Lectures 6 hrs.)

Introduction To VLSI Design • Moore's Law • Scale Of Integration • Types Of VLSI Chips • Design Principles (Digital VLSI) • Design Domains (Y-Chart) • Challenges Of VLSI Design- Power • Timing Area • Noise • Testability Reliability • Yield • CAD Tools For VLSI Design

Module 2: (Lectures 7 hrs.)

Introduction To VLSI Technology • VLSI Technology - An Overview • Wafer Processing • Oxidation • Epitaxial Deposition • Ion-implantation And Diffusion • The Silicon Gate Process • Basic CMOS Technology • Basic N-well CMOS Process • P-well CMOS Process • Twin Tub Process • Silicon On Insulator • CMOS Process Enhancement-interconnect • Circuit Elements • 3-D CMOS

Module 3: (Lectures 7 hrs.)

Analysis Of CMOS Logic Circuits • MOSFET As Switch • Recapitulation Of MOS • CMOS Inverter • CMOS Logic Circuits • NAND Gate And NOR Gate • Complex Logic Circuits • Pass Transistor Logic • CMOS Transmission Gate • CMOS Full Adder

Module 4: (Lectures 4 hrs.)

Advanced Techniques In CMOS Logic Circuit • Pseudo NMOS • Tri-state • Clocked CMOS • Dynamic CMOS Logic • Domino • NORA • Zipper • Etc • Dual Rail Logic Networks

Module 5: (Lectures 2 hrs.)

Memories • Static RAM • SRAM Arrays • Dynamic RAMS • ROM Arrays • Logic Arrays

Module 6: (Lectures 8 hrs.)

Timing Issues In VLSI System Design • Timing Classification • Synchronous Timing Basics • Skew And Jitter • Latch Based Clocking • Self-timed Circuit Design • Self-timed Logic • Completion Signal Generation • Self-timed Signaling-synchronizers And Arbiters

Module 7: (Lectures 6 hrs.)

Verilog Hardware Description Language • Overview Of Digital Design With Verilog HDL • Hierarchical Modeling Concepts • Modules And Port Definitions • Gate Level Modeling • Data Flow Modeling • Behavioral Modeling • Task & Functions • Test Bench

Module 1: (Lecture 10 hrs.)

Embedded Computing • Introduction • Complex Systems And Microprocessors • The Embedded System Design Process • Formalization For System Design

Module 2: (Lecture 10 hrs.)

Instruction Sets CPUs • Instruction And Preliminaries ARM And SHARC Processors • Programming I/O CPU Performance And Power Consumption

Module 3: (Lecture 10 hrs.)

The Embedded Computing Platform And Program Design • Introduction • The CPU Bus • Component Interfacing • Designing With Microprocessors • Development And Debugging

Module 4: (Lecture 10 hrs.)

Program Design And Analysis • Introduction Program Design • Assembly • Linking • Basic Compilation Techniques • Analysis Optimization Of Executive Time

Module 1: (Lecture 8 hrs.)

Introduction • Characterization And Classification Of Signals • Typical Signal Processing Operations • Review Of Discrete-time Signal And System Analysis • Advantages And Typical Applications Of DSP

Module 2: (Lecture 8 hrs.)

Sampling And Quantization • Sampling And Discrete-time Processing Of Continuous Time Signals • Sampling Of Low-pass And Band-pass Signals • Uniform And Non-uniform Quantization • Lloyd-Max Algorithm • Log-companding • A-law • μ-law • Adaptive Quantization And Prediction

Module 3: (Lecture 8 hrs.)

Orthogonal Transforms • Properties And Applications Of DFT • Implementing Linear Time Invariant Systems Using DFT • Circular Convolution • Linear Convolution Using DFT • Fast Fourier Transform • FFT Algorithms • Decimation In Time • Decimation In Frequency • Goertzel Algorithm • Application Of Transform In Speech • Audio • Image And Video Coding • Karhunen-Loeve Transform • DCT • JPEG And MPEG Coding Standards

Module 4: (Lecture 8 hrs.)

Digital Filter Design Techniques • IIR And FIR Filters • Filter Design Specifications • Design Of Digital IIR Filters • Impulse Invariant • Bilinear Transformation Techniques For Butterworth And Chebyshev Filters • Design Of FIR Filters • Windowing • Frequency Sampling Filter Design • Optimum Approximations Of FIR Filters

Module 5: (Lecture 6 hrs.)

Multi-rate Signal Processing • Fundamentals Of Multirate Systems • Decimation And Interpolation • Application Of Multirate DSP In Sampling Rate Conversion • Filter Banks • Polyphase Structures • Quadrature-mirror Filter Bank • Wavelet Transform And Its Relation To Multi-rate Filter Banks • Applications To Speech And Audio Coding

Module 6: (Lecture 4 hrs.)

Basic Concept Of Adaptive Digital Signal Processing • Adaptive Wiener Filter And LMS Algorithm • Applications Of Adaptive Filtering To Echo Cancellation And Equalization

Module 1: (Lectures 10 hrs.)

Introduction To Parallel Computing • Parallel Processing Terminology • Pipelining Vs Data Parallelism • Control Parallelism • Scalability • Control Parallel Approach • Data Parallel Approach • Data Parallel Approach With I/O Parallel Reduction • Prefix Sums • List Ranking • Preorder Tree Traversal • Merging Two Sorted Lists • Graph Coloring • Reducing The Number Of Processors • Problems Defying Fast Solutions On PRAMS

Module 2: (Lectures 10 hrs.)

Thread And Process Level Parallel Architectures • MIMD • Multi-threaded Architectures • Distributed And Shared Memory MIMD Architectures

Module 3: (Lectures 8 hrs.)

Dynamic Interconnection Networks • Mapping And Scheduling • Mapping Data To Processors On Processor Arrays And Multicomputers • Dynamic Load Balancing On Multicomputers • Static Scheduling On UMA Multiprocessors • Deadlock

Module 5: (Lectures 12 hrs.)

Parallel Programming And Parallel Algorithms • Programming Models • Parallel Programming On Multiprocessors And Multicomputers • Parallel Algorithm Structure • Analyzing Parallel Algorithm • Elementary Parallel Algorithms • Matrix Algorithms • Sorting • Graph Algorithms

Module 1: (Lectures 8 hrs.)

Introduction • Communication Model • Transmission Line • Data Communication Concepts • Data Transmission • Parallel Transmission • Serial Transmission • Asynchronous Transmission • Synchronous Transmission • Data Encoding • Non-Return To Zero (NRZ) • Return To Zero (RZ) • Modern Concept • Modern Operation

Module 2: (Lectures 6 hrs.)

Basic Signal Processing Operations In Digital Communication • Analog Pulse Modulation • Sampling Theorem For Base-band And Pass-band Signals • Quadrature Sampling Of Band Pass Signal Reconstruction Of Message From Its Samples • Signal Distortion In Sampling

Module 3: (Lectures 8 hrs.)

Pulse Amplitude Modulation • Modulation Generation And Demodulation • PAM/TDM System • Digital Pulse Modulation • Quantization • PCM • DPCM • Delta Modulation • Adaptive Delta Modulation-Design Of Typical Systems And Performance Analysis • Signal Space Concepts • Geometric Structure Of The Signal Space • Vector Representation • Distance • Norm And Inner Product • Orthogonality • Gram-Schmidt Orthogonalization Procedure

Module 4: (Lectures 8 hrs.)

Filtering And Receivers • Matched Filter Receiver • Inter Symbol Interference • Pulse Shaping • Nyquist Criterion For Zero ISI • Eye Diagram • Equalizer • Scrambling And Descrambling • Review Of Gaussian Random Process • Optimum Threshold Detection • Optimum Receiver For AWGN Channel • Matched Filter And Correlation Receivers

Module 5: (Lectures 10 hrs.)

Decision Procedure • Maximum Aposteriori Probability Detector • Maximum Likelihood Detector • Error Probability Performance Of Binary Signaling • Digital Band Pass Modulation Schemes • ASK • FSK • PSK • MSK • Digital M-ary Modulation Schemes • Signal Space Representation • Error In Communication • Detection Of Signals In Gaussian Noise • Coherent & Non-coherent Detection • Differential Modulation Schemes • Error Performance Of Binary And M-ary Modulation Schemes • Probability Of Error Of Binary DPSK • Performance Of M-ary Signaling Schemes In AWGN Channels • Power Spectra Of Digitally Modulated Signals • Performance Comparison Of Digital Modulation Schemes

Module 1: Introduction (Lectures 8 hrs.)

Fundamentals Of Wireless Communication Technology • The Electromagnetic Spectrum • Radio Propagation Mechanisms • Characteristics Of The Wireless Channel • Mobile Ad-hoc Networks (MANETS) And Wireless Sensor Networks (WSNs) • Concepts And Architectures • Applications Of Ad-hoc And Sensor Networks • Design Challenges In Ad-hoc And Sensor Networks

Module 2: Mac Protocols for Ad-hoc Wireless Networks (Lectures 8 hrs.)

Issues In Designing A MAC Protocol • Classification Of MAC Protocols • Contention Based Protocols • Contention Based Protocols With Reservation Mechanisms • Contention Based Protocols With Scheduling Mechanisms • Multi Channel MAC • IEEE 802.11

Module 3: Routing Protocols and Transport Layer in Ad-hoc Networks (Lectures 8 hrs.)

Issues In Designing A Routing And Transport Layer Protocol For Ad hoc Networks • Proactive Routing • Reactive Routing (on-demand) • Hybrid Routing • Classification Of Transport Layer Solutions • TCP Over Ad hoc Wireless Networks

Module 4: Wireless Sensor Networks (WSNs) And MAC Protocols (Lectures 8 hrs.)

Single Node Architecture • Hardware And Software Components Of A Sensor Node • WSN Network Architecture • Typical Network Architectures • Data Relaying And Aggregation Strategies • MAC Layer Protocols • Self-organizing • Hybrid TDMA/FDMA And CSMA Based MAC • IEEE 802.15.4

Module 5: Security in Ad Hoc and Sensor Networks (Lectures 8 hrs.)

Security Attacks • Key Distribution And Management • Intrusion Detection • Software Based Anti-tamper Techniques • Water Marking Techniques • Defense Against Routing Attacks • Secure Ad hoc Routing Protocols • Broadcast Authentication WSN Protocols • TESLA • Biba • Sensor Network Security Protocols • SPINS

Module 1: (Lectures 6 hrs.)

Introduction To VLSI Design • Moore's Law • Scale Of Integration • Types Of VLSI Chips • Design Principles (Digital VLSI) • Design Domains (Y-Chart) • Challenges Of VLSI Design- Power • Timing Area • Noise • Testability Reliability • Yield • CAD Tools For VLSI Design

Module 2: (Lectures 7 hrs.)

Introduction To VLSI Technology • VLSI Technology - An Overview • Wafer Processing • Oxidation • Epitaxial Deposition • Ion-implantation And Diffusion • The Silicon Gate Process • Basic CMOS Technology • Basic N-well CMOS Process • P-well CMOS Process • Twin Tub Process • Silicon On Insulator • CMOS Process Enhancement-interconnect • Circuit Elements • 3-D CMOS

Module 3: (Lectures 7 hrs.)

Analysis Of CMOS Logic Circuits • MOSFET As Switch • Recapitulation Of MOS • CMOS Inverter • CMOS Logic Circuits • NAND Gate And NOR Gate • Complex Logic Circuits • Pass Transistor Logic • CMOS Transmission Gate • CMOS Full Adder

Module 4: (Lectures 4 hrs.)

Advanced Techniques In CMOS Logic Circuit • Pseudo NMOS • Tri-state • Clocked CMOS • Dynamic CMOS Logic • Domino • NORA • Zipper • Etc • Dual Rail Logic Networks

Module 5: (Lectures 2 hrs.)

Memories • Static RAM • SRAM Arrays • Dynamic RAMS • ROM Arrays • Logic Arrays

Module 6: (Lectures 8 hrs.)

Timing Issues In VLSI System Design • Timing Classification • Synchronous Timing Basics • Skew And Jitter • Latch Based Clocking • Self-timed Circuit Design • Self-timed Logic • Completion Signal Generation • Self-timed Signaling-synchronizers And Arbiters

Module 7: (Lectures 6 hrs.)

Verilog Hardware Description Language • Overview Of Digital Design With Verilog HDL • Hierarchical Modeling Concepts • Modules And Port Definitions • Gate Level Modeling • Data Flow Modeling • Behavioral Modeling • Task & Functions • Test Bench

Module 1: (Lecture 10 hrs.)

Embedded Computing • Introduction • Complex Systems And Microprocessors • The Embedded System Design Process • Formalization For System Design

Module 2: (Lecture 10 hrs.)

Instruction Sets CPUs • Instruction And Preliminaries ARM And SHARC Processors • Programming I/O CPU Performance And Power Consumption

Module 3: (Lecture 10 hrs.)

The Embedded Computing Platform And Program Design • Introduction • The CPU Bus • Component Interfacing • Designing With Microprocessors • Development And Debugging

Module 4: (Lecture 10 hrs.)

Program Design And Analysis • Introduction Program Design • Assembly • Linking • Basic Compilation Techniques • Analysis Optimization Of Executive Time

Module 1: (Lecture 8 hrs.)

Introduction • Characterization And Classification Of Signals • Typical Signal Processing Operations • Review Of Discrete-time Signal And System Analysis • Advantages And Typical Applications Of DSP

Module 2: (Lecture 8 hrs.)

Sampling And Quantization • Sampling And Discrete-time Processing Of Continuous Time Signals • Sampling Of Low-pass And Band-pass Signals • Uniform And Non-uniform Quantization • Lloyd-Max Algorithm • Log-companding • A-law • μ-law • Adaptive Quantization And Prediction

Module 3: (Lecture 8 hrs.)

Orthogonal Transforms • Properties And Applications Of DFT • Implementing Linear Time Invariant Systems Using DFT • Circular Convolution • Linear Convolution Using DFT • Fast Fourier Transform • FFT Algorithms • Decimation In Time • Decimation In Frequency • Goertzel Algorithm • Application Of Transform In Speech • Audio • Image And Video Coding • Karhunen-Loeve Transform • DCT • JPEG And MPEG Coding Standards

Module 4: (Lecture 8 hrs.)

Digital Filter Design Techniques • IIR And FIR Filters • Filter Design Specifications • Design Of Digital IIR Filters • Impulse Invariant • Bilinear Transformation Techniques For Butterworth And Chebyshev Filters • Design Of FIR Filters • Windowing • Frequency Sampling Filter Design • Optimum Approximations Of FIR Filters

Module 5: (Lecture 6 hrs.)

Multi-rate Signal Processing • Fundamentals Of Multirate Systems • Decimation And Interpolation • Application Of Multirate DSP In Sampling Rate Conversion • Filter Banks • Polyphase Structures • Quadrature-mirror Filter Bank • Wavelet Transform And Its Relation To Multi-rate Filter Banks • Applications To Speech And Audio Coding

Module 6: (Lecture 4 hrs.)

Basic Concept Of Adaptive Digital Signal Processing • Adaptive Wiener Filter And LMS Algorithm • Applications Of Adaptive Filtering To Echo Cancellation And Equalization

Module 1: (Lectures 10 hrs.)

Introduction To Parallel Computing • Parallel Processing Terminology • Pipelining Vs Data Parallelism • Control Parallelism • Scalability • Control Parallel Approach • Data Parallel Approach • Data Parallel Approach With I/O Parallel Reduction • Prefix Sums • List Ranking • Preorder Tree Traversal • Merging Two Sorted Lists • Graph Coloring • Reducing The Number Of Processors • Problems Defying Fast Solutions On PRAMS

Module 2: (Lectures 10 hrs.)

Thread And Process Level Parallel Architectures • MIMD • Multi-threaded Architectures • Distributed And Shared Memory MIMD Architectures

Module 3: (Lectures 8 hrs.)

Dynamic Interconnection Networks • Mapping And Scheduling • Mapping Data To Processors On Processor Arrays And Multicomputers • Dynamic Load Balancing On Multicomputers • Static Scheduling On UMA Multiprocessors • Deadlock

Module 5: (Lectures 12 hrs.)

Parallel Programming And Parallel Algorithms • Programming Models • Parallel Programming On Multiprocessors And Multicomputers • Parallel Algorithm Structure • Analyzing Parallel Algorithm • Elementary Parallel Algorithms • Matrix Algorithms • Sorting • Graph Algorithms

Module 1: (Lectures 8 hrs.)

Introduction • Communication Model • Transmission Line • Data Communication Concepts • Data Transmission • Parallel Transmission • Serial Transmission • Asynchronous Transmission • Synchronous Transmission • Data Encoding • Non-Return To Zero (NRZ) • Return To Zero (RZ) • Modern Concept • Modern Operation

Module 2: (Lectures 6 hrs.)

Basic Signal Processing Operations In Digital Communication • Analog Pulse Modulation • Sampling Theorem For Base-band And Pass-band Signals • Quadrature Sampling Of Band Pass Signal Reconstruction Of Message From Its Samples • Signal Distortion In Sampling

Module 3: (Lectures 8 hrs.)

Pulse Amplitude Modulation • Modulation Generation And Demodulation • PAM/TDM System • Digital Pulse Modulation • Quantization • PCM • DPCM • Delta Modulation • Adaptive Delta Modulation-Design Of Typical Systems And Performance Analysis • Signal Space Concepts • Geometric Structure Of The Signal Space • Vector Representation • Distance • Norm And Inner Product • Orthogonality • Gram-Schmidt Orthogonalization Procedure

Module 4: (Lectures 8 hrs.)

Filtering And Receivers • Matched Filter Receiver • Inter Symbol Interference • Pulse Shaping • Nyquist Criterion For Zero ISI • Eye Diagram • Equalizer • Scrambling And Descrambling • Review Of Gaussian Random Process • Optimum Threshold Detection • Optimum Receiver For AWGN Channel • Matched Filter And Correlation Receivers

Module 5: (Lectures 10 hrs.)

Decision Procedure • Maximum Aposteriori Probability Detector • Maximum Likelihood Detector • Error Probability Performance Of Binary Signaling • Digital Band Pass Modulation Schemes • ASK • FSK • PSK • MSK • Digital M-ary Modulation Schemes • Signal Space Representation • Error In Communication • Detection Of Signals In Gaussian Noise • Coherent & Non-coherent Detection • Differential Modulation Schemes • Error Performance Of Binary And M-ary Modulation Schemes • Probability Of Error Of Binary DPSK • Performance Of M-ary Signaling Schemes In AWGN Channels • Power Spectra Of Digitally Modulated Signals • Performance Comparison Of Digital Modulation Schemes

Module 1: Introduction (Lectures 8 hrs.)

Fundamentals Of Wireless Communication Technology • The Electromagnetic Spectrum • Radio Propagation Mechanisms • Characteristics Of The Wireless Channel • Mobile Ad-hoc Networks (MANETS) And Wireless Sensor Networks (WSNs) • Concepts And Architectures • Applications Of Ad-hoc And Sensor Networks • Design Challenges In Ad-hoc And Sensor Networks

Module 2: Mac Protocols for Ad-hoc Wireless Networks (Lectures 8 hrs.)

Issues In Designing A MAC Protocol • Classification Of MAC Protocols • Contention Based Protocols • Contention Based Protocols With Reservation Mechanisms • Contention Based Protocols With Scheduling Mechanisms • Multi Channel MAC • IEEE 802.11

Module 3: Routing Protocols and Transport Layer in Ad-hoc Networks (Lectures 8 hrs.)

Issues In Designing A Routing And Transport Layer Protocol For Ad hoc Networks • Proactive Routing • Reactive Routing (on-demand) • Hybrid Routing • Classification Of Transport Layer Solutions • TCP Over Ad hoc Wireless Networks

Module 4: Wireless Sensor Networks (WSNs) And MAC Protocols (Lectures 8 hrs.)

Single Node Architecture • Hardware And Software Components Of A Sensor Node • WSN Network Architecture • Typical Network Architectures • Data Relaying And Aggregation Strategies • MAC Layer Protocols • Self-organizing • Hybrid TDMA/FDMA And CSMA Based MAC • IEEE 802.15.4

Module 5: Security in Ad Hoc and Sensor Networks (Lectures 8 hrs.)

Security Attacks • Key Distribution And Management • Intrusion Detection • Software Based Anti-tamper Techniques • Water Marking Techniques • Defense Against Routing Attacks • Secure Ad hoc Routing Protocols • Broadcast Authentication WSN Protocols • TESLA • Biba • Sensor Network Security Protocols • SPINS

Module 1: (Lecture 8 hrs.)

Data Warehousing And Business Analysis • Data Warehousing Components • Building A Data warehouse • Data Warehouse Architecture • DBMS Schemas For Decision Support • Data Extraction • Cleanup • Transformation Tools • Metadata • Reporting • Query Tools And Applications • Online Analytical Processing (OLAP) • OLAP And Multidimensional Data Analysis

Module 2: (Lecture 8 hrs.)

Data Mining • Data Mining Functionalities • Data Preprocessing • Data Cleaning • Data Integration And Transformation • Data Reduction • Data Discretization And Concept Hierarchy Generation • Architecture Of A Typical Data Mining Systems • Classification Of Data Mining Systems • Association Rule Mining • Efficient And Scalable Frequent Item set Mining Methods • Mining Various Kinds Of Association Rules • Association Mining To Correlation Analysis • Constraint-Based Association Mining

Module 3: (Lecture 8 hrs.)

Classification And Prediction • Issues Regarding Classification And Prediction • Classification By Decision Tree Introduction • Bayesian Classification • Rule Based Classification • Classification By Back propagation • Support Vector Machines • Associative Classification • Lazy Learners • Other Classification Methods • Prediction • Accuracy And Error Measures • Evaluating The Accuracy Of A Classifier Or Predictor • Ensemble Methods • Model Section

Module 4: (Lecture 8 hrs.)

Cluster Analysis • Types Of Data In Cluster Analysis • A Categorization Of Major Clustering Methods • Partitioning Methods • Hierarchical Methods • Density-Based Methods • Grid-Based Methods • Model-Based Clustering Methods • Clustering High-Dimensional Data • Constraint-Based Cluster Analysis • Outlier Analysis

Module 5: (Lecture 8 hrs.)

Mining Object • Spatial • Multimedia • Text And Web Data • Multidimensional Analysis And Descriptive Mining Of Complex Data Objects • Spatial Data Mining • Multimedia Data Mining • Text Mining • Mining The World Wide Web

Module 1: (Lecture 8 hrs.)

Algorithms For Integer Arithmetic • Divisibility • GCD Computation • Euclid's Algorithm • Extended Euclid's Algorithm • Modular Arithmetic • Modular Exponentiation • Montgomery Arithmetic • Congruence • Chinese Remainder Theorem • Hensel Lifting • Orders And Primitive Roots • Quadratic Residues • Integer And Modular Square Roots • Prime Number Theorem • Continued Fractions And Rational Approximations

Module 2: (Lecture 8 hrs.)

Representation Of Finite Fields • Prime And Extension Fields • Representation Of Extension Fields • Polynomial Basis • Primitive Elements • Normal Basis • Optimal Normal Basis • Irreducible Polynomials • Algorithms For Polynomials • Root-finding And Factorization • Lenstra-Lenstra-Lovasz Algorithm • Polynomials Over Finite Fields

Module 3: (Lecture 6 hrs.)

Elliptic Curves • The Elliptic Curve Group • Elliptic Curves Over Finite Fields • Schoof's Point Counting Algorithm

Module 4: (Lecture 8 hrs.)

Primality Testing Algorithms • Fermat Test • Miller-Rabin Test • Solovay-Strassen Test • AKS Test • Integer Factoring Algorithms • Trial Division • Pollard Rho Method • P-1 Method • CFRAC Method • Quadratic Sieve Method • Elliptic Curve Method

Module 5: (Lecture 8 hrs.)

Computing Discrete Logarithms Over Finite Fields • Baby-step-giant-step Method • Pollard Rho Method • Pohlig-Hellman Method • Index Calculus Methods • Linear Sieve Method • Coppersmith's Algorithm • Applications • Algebraic Coding Theory • Cryptography

Module 1: (Lecture 6 hrs.)

Introduction To Advance Operating System • Comparative Study Of OS • LINUX • Linux File System + Measurements • The Log Structured File System • Server Less Network File Systems • The Coda File System • AFS • Virtual Memory • Stack/ Buffer Overflow • Address Space Layout Randomization (ASLR) User-Level Virtual Memory • Global Network Scheduling • Network Optimization • Extensible Operating Systems • Issues Of Security In OS • Cryptographic File Systems

Module 2: (Lecture 6 hrs.)

Distributed Operating Systems • System Architecture Types • Issues In Distributed Operating Systems • Naming • Scalability • Security • Client-Server Model • Process Synchronization • Global Knowledge • Etc • RPC • Message Passing • Absence Of Global Lock • Absence Of Shared Memory • Lamport's Logical Clock • Chandy Lamport's Algorithm • Termination Detection • Distributed Mutual Exclusion • Non Token Based Algorithms • Ricart Agarwala Algorithm • Lamport's Algorithm • Generalized Non-Token Based Algorithm • Comparative Performance Analysis

Module 3: (Lecture 6 hrs.)

Synchronization • Clock Synchronization • Event Ordering • Mutual Exclusion • Deadlock • Election Algorithms • Desirable Features Of Good Global Scheduling Algorithms • Task Assignment Approach • Load Balancing Approach • Load Sharing Approach • Process Management • Process Migration • Threads Distributed Deadlock Detection • Centralized/Distributed/ Hierarchical Control • Path Pushing Algorithm • Edge-Chasing Algorithm • Ho-Ramamoorthy Algorithms

Module 4: (Lecture 6 hrs.)

Resource Management In Distributed Systems • Distributed File Systems • Mounting • Caching • Bulk Data Transfer • Design Issues • Cache Consistency • Scalability • Log Structured File systems • Distributed Shared Memory • Central-Server Algorithm • Full-Replication Algorithm • Etc • Coherence Protocols • Granularity • Page Replacement • Distributed Scheduling • Load • Classification • Load Balancing And Load Sharing • Policies For Transfer • Selection • Location • Information • Stability • Load Balancing Algorithms • Load Sharing Case Studies

Module 5: (Lecture 6 hrs.)

Fault Tolerance • Recovery • Protection And Security • Atomic Actions And Commit • Commit Protocols • Voting Protocols • Dynamic Voting • Classification Of Failures • Backward And Forward Error Recovery • Synchronous/Asynchronous Checkpoints And Recovery • Recovery In Concurrent Systems • Access Matrix Model • Advanced Models Of Protection • Cryptography

Module 6: (Lecture 6 hrs.)

Multiprocessor And Database Operating Systems • Tightly And Loosely Coupled Systems • Interconnect Networks • Caching • Hypercube Architectures • Threads • Process Synchronization In MP Systems • Process Scheduling In MP Systems • Requirements Of Database OS • Transactions • Conflicts • Serializability Theory • Distributed Database Systems • Concurrency Control Algorithms • Lock Based Algorithms • Timestamp Based Algorithms • 2PL

Module 7: (Lecture 6 hrs.)

Virtualization • Introduction • Simulation • Emulation • Para-Virtualization • Full virtualization • X86 Virtualization • Privileged Instructions • Control Sensitive Instructions • Trap And Emulate • Binary Translation • X86 Hardware Virtualization Vmxon/vmxoff • Vmentry • Vm Exit • Intel VTd • VMCS • Shadow Page Tables • EPT/NPT

Module 1: (Lecture 8 hrs.)

Introduction To Genetic Algorithm • Genetic Algorithms • Traditional And Search Methods And Their Differences • A Simple Genetic Algorithm

Module 2: (Lecture 8 hrs.)

Genetic Algorithms Revisited • The Fundamental Theorem • Schema Processing

Module 3: (Lecture 8 hrs.)

Two & K-Armed Bandit Problem • Hypothesis • Schemata And Revisited

Module 4: (Lecture 8 hrs.)

Computer Implementation Of A Genetic Algorithm • Data Structures • Reproduction • Crossover And Mutation • A Time To Reproduce • A Time To Cross • How Well Does It Work • Mapping Objective Functions To Fitness Form • Fitness Scaling • Coding • A Multiparameter Mapped • Fixed-Point Coding • Discretization • Constraints

Module 5: (Lecture 8 hrs.)

Applications Of Genetic Algorithms • The Rise Of Genetic Algorithms • Genetic Algorithm Applications Of Historical Interest • De Jong And Function Optimization • Improvements In Basic Technique • Current Applications Of Genetic Algorithms • Genetics-Based Machine Learning • Whence It Came • What Is Classifier System • Rule And Message • Genetic Algorithm

Module 1: (Lecture 4 hrs.)

Introduction • Distributed Computing And Enabling Technologies • Cloud Fundamentals • Cloud Definition • Evolution • Architecture • Applications • Deployment Models • Service Models

Module 2: (Lecture 5 hrs.)

Virtualization • Issues With Virtualization • Virtualization Technologies And Architectures • Internals Of Virtual Machine Monitors/hypervisors • Virtualization Of Data Centers • Issues With Multitenancy

Module 3: (Lecture 6 hrs.)

Implementation • Study Of Cloud Computing Systems Like Amazon EC2 And S3 • Google App Engine • Microsoft Azure • Build Private/Hybrid Cloud Using Open Source Tools • SLA Management

Module 4: (Lecture 12 hrs.)

Resource Management • Cloud Resource Provisioning Plan (advance Reservation • On Demand Plan • Spot Instances) • Various Scheduling And Load Balancing Techniques To Improve QoS Parameters • Resource Optimization Algorithms • Task Migration And VM Migration Technique

Module 5: (Lecture 7 hrs.)

Security • Vulnerability Issues And Security Threats • Application-level Security • Data Level Security • Virtual Machine Level Security • Infrastructure Security • Multi-tenancy Issues

Module 6: (Lecture 6 hrs.)

Advances • Green Cloud • Mobile Cloud Computing • Fog Computing • Internet Of Things

Module 1: (Lectures 6 hrs.)

Introduction To Quantum Computing • Motivation For Studying Quantum Computing • Major Players In The Industry (IBM, Microsoft, Rigetti, D-Wave Etc) • Origin Of Quantum Computing • Overview Of Major Concepts In Quantum Computing • Qubits And Multi-qubits States • Bra-ket Notation • Bloch Sphere Representation • Quantum Superposition • Quantum Entanglement

Module 2: (Lectures 9 hrs.)

Math Foundation For Quantum Computing • Matrix Algebra • Basis Vectors And Orthogonality • Inner Product And Hilbert Spaces • Matrices And Tensors • Unitary Operators And Projectors • Dirac Notation • Eigen Values And Eigen Vectors

Module 3: (Lectures 8 hrs.)

Building Blocks For Quantum Program • Architecture Of A Quantum Computing Platform • Details Of Q-bit System Of Information Representation • Block Sphere • Multi-qubits States • Quantum Superposition Of Qubits (valid And Invalid Superposition) • Quantum Entanglement • Useful States From Quantum Algorithmic Perceptive E.g. Bell State • Operation On Qubits • Measuring And Transforming Using Gates • Quantum Logic Gates And Circuit • Pauli • Hadamard • Phase Shift • Controlled Gates • Ising • Deutsch • Swap Etc • Programming Model For A Quantum Computing Program • Steps Performed On Classical Computer • Steps Performed On Quantum Computer • Moving Data Between Bits And Qubits

Module 4: (Lectures 18 hrs.)

Quantum Algorithms • Basic Techniques Exploited By Quantum Algorithms • Amplitude Amplification • Quantum Fourier Transform • Phase Kick-back • Quantum Phase Estimation • Quantum Walks • Major Algorithms • Shor's Algorithm • Grover's Algorithm • Deutsch's Algorithm • Deutsch - Jozsa Algorithm • OSS Toolkits For Implementing Quantum Program • IBM Quantum Experience • Microsoft Q • Rigetti PyQuil (QPU/QVM)

Module 1: (Lecture 8 hrs.)

Consistency • Atomicity • Durability • Isolation • Flat Transactions • Providing Structure Within A Transaction • Structuring An Application As Multiple Transactions

Module 2: (Lecture 8 hrs.)

Schedules And Schedule Equivalence • Recoverability • Cascaded Aborts And Strictness • Models For Concurrency Control • A Strategy For Immediate-Update Pessimistic Concurrency Controls • Design Of An Immediate-Update Pessimistic Concurrency Control • Objects And Semantic Commutativity • Atomicity • Recoverability And Compensating Operations • Locking And SQL Isolation Levels • Granular Locking • Intention Locks And Index Locks • Tuning Transactions • Multi version Concurrency Controls

Module 3: (Lecture 8 hrs.)

Crash • Abort And Media Failure • Immediate-Update Systems And Write-Ahead Logs • Recovery In Deferred-Update Systems • Recovery From Media Failure

Module 4: (Lecture 8 hrs.)

Transaction Processing In A Centralized System • Transaction Processing In A Distributed System • Global Atomicity And The Transaction Manager • Remote Procedure Call • Pear-to-Pear Communication • Event Communication • Storage Architectures • Transaction Processing On The Internet • Implementing The ACID Properties • Distributed Deadlock • Global Serialization

Module 5: (Lecture 8 hrs.)

Authentication • Authorization And Encryption • Digital Signatures • Key Distribution And Authentication • Authorization • Authenticated RPC • Electronic Commerce • Certificates • Passport • SSO • SET Protocol • Dual Signatures • Goods Atomicity • Certified Delivery • Escrow

Module 1: (Lecture 6 hrs.)

Introduction • Importance Of Pattern Recognition • Features • Feature Vectors • Classifiers • Supervised Versus Unsupervised Pattern Recognition

Module 2: (Lecture 6 hrs.)

Bayes Decision Theory • Discriminant Functions And Services O The Normal Distribution • Bayesian Classification • Estimating Probability Density Functions • Nearest Neighbour Rules Bayesian Networks

Module 3: (Lecture 6 hrs.)

Linear And Nonlinear Classifiers • The Perceptron Algorithm • Least-Squares Methods • Nonlinear Classifiers • Multilayer Perceptron's • Back Propagation Algorithm • Decision Trees • Combinations Of Classifiers • Boosting

Module 4: (Lecture 6 hrs.)

Feature Selection • Data Pre-processing • ROC Curves • Class Separability Measures • Feature Subset Selection • Bayesian Information Criterion

Module 5: (Lecture 6 hrs.)

Dimensionality Reduction • Basis Vectors • Singular Value Decomposition • Independent Component Analysis • Kernel PCA • Wavelets

Module 6: (Lecture 6 hrs.)

Additional Features And Template Matching • Texture • Shape And Size Characterization • Fractals • Features For Audio • Template Matching Using Dynamic Time Warping And Edit Distance • Context Dependent Classification

Module 7: (Lecture 6 hrs.)

Clustering • Sequential Algorithms • Hierarchical Algorithms • Functional Optimization-Based Clustering Graph Clustering • Learning Clustering • Clustering High Dimensional Data • Subspace Clustering • Cluster Validity Measure

Module 1: Introduction (Lecture 4 hrs.)

Brief Introduction Of Big Data Problem • Overview Of Linear Algebra • Probability • Numerical Computation • Basics Of Machine learning/Feature Engineering

Module 2: Basics of Neural networks (Lecture 4 hrs.)

Neural Networks • Tools For Deep Learning Network • Shallow Vs Deep Network

Module 3: Feed forward Networks (Lecture 6 hrs.)

Multilayer Perceptron • Gradient • Loss Function • Gradient Descent • Stochastic Gradient Descent (SDD) • Backpropagation Algorithm • Empirical Risk Minimization • Regularization • Gradient Based Learning • Cost Function • Learning Rate • Soft Max • Sigmoid Function • Hidden Unit • ReLU • Logistic Sigmoid • Hyperbolic Tangent Architecture Design • Heuristics For Faster Training

Module 4: Unsupervised learning (Lecture 10 hrs.)

Deep Belief Network • Deep Boltzmann Machine (DBM) • Factor Analysis • Auto-encoders (standard, Sparse, Denoising, Contractive, Etc) • Variational Auto-encoders • Adversarial Generative Networks • Auto-encoder • Regularization Optimization For Training Deep Model

Module 5: Advanced topics (Lecture 10 hrs.)

Convolutional Neural Network (CNN) • Architectures • Convolution/pooling Layers • Recurrent Neural Network (RNN)/ Sequence Modeling • Long Short Term Memory Networks (LSTM) • GRU • Encoder Decoder Architectures Reinforcement Learning

Module 6: Practical applications (Lecture 6 hrs.)

Application Of Deep Learning To Computer Vision • Speech Recognition • Natural Language Processing • Etc

Module 1: (Lecture 6 hrs.)

Polygon Triangulation • Triangulation Theory • Area Of Polygon • Segment Intersection • Segment-triangle Intersection • Polygon Partitioning • Monotone Partitioning • Trapezoidalization • Partition Into Monotone Mountains • Linear-Time Triangulation • Convex Partitioning

Module 2: (Lecture 5 hrs.)

Convex Hulls In Two Dimensions • Definitions Of Convexity And Convex Hulls • Naive Algorithms For Extreme Points • Gift Wrapping • QuickHull • Graham's Algorithm • Lower Bound • Incremental Algorithm • Divide And Conquer

Module 3: (Lecture 6 hrs.)

Convex Hulls In Three Dimensions • Polyhedra And Data Structures • Gift Wrapping • Preparata-Hong Algorithm • Incremental Algorithm • Randomized Incremental Algorithm

Module 4: (Lecture 6 hrs.)

Voronoi Diagrams • Definitions And Basic Properties • Delaunay Triangulations • Algorithms • Applications In Detail • Medial Axis • Connection To Convex Hulls • Connection To Arrangements

Module 5: (Lecture 6 hrs.)

Arrangements • Combinatorics Of Arrangements • Incremental Algorithm • Three And Higher Dimensions • Duality • Higher-Order Voronoi • Diagrams • Applications

Module 6: (Lecture 8 hrs.)

Search And Intersection • Segment-Segment Intersection • Segment- Triangle Intersection • Point In Polygon • Point In Polyhedron • Intersection Of Convex Polygons • Intersection Of Segments • Intersection Of Nonconvex Polygons • Extreme Point Of Convex Polygon • Extremal Polytope • Queries • Planar Point Location

Module 7: (Lecture 5 hrs.)

Motion Planning • Shortest Paths • Moving A Disk • Translating A Convex Polygon • Moving A Ladder • Robot Arm Motion • Separability

Module 1: (Lecture 7 hrs.)

Introduction To Big Data • Definition • Characteristic Features • Big Data Applications • Big Data Vs Traditional Data • Risks Of Big Data • Structure Of Big Data • Challenges Of Conventional Systems • Web Data • Evolution Of Analytic Scalability • Evolution Of Analytic Processes • Tools And Methods • Analysis Vs Reporting • Modern Data Analytic Tools

Module 2: (Lecture 9 hrs.)

HADOOP Framework • Distributed File Systems • Large-Scale File System • Organization • HDFS Concepts • Map Reduce Execution • Algorithms Using Map Reduce • Matrix-Vector Multiplication • Hadoop YARN

Module 3: (Lecture 10 hrs.)

Data Analysis • Statistical Methods • Regression Modelling • Multivariate Analysis • Classification • SVM & Kernel Methods • Rule Mining • Cluster Analysis • Types Of Data In Cluster Analysis • Partitioning Methods • Hierarchical Methods • Density Based Methods • Grid Based Methods • Model Based Clustering Methods • Clustering High Dimensional Data • Predictive Analytics • Data Analysis Using R

Module 4: (Lecture 7 hrs.)

Mining Data Streams • Streams • Concepts • Stream Data Model And Architecture • Sampling Data In A Stream • Mining Data Streams And Mining Time-series Data • Real Time Analytics Platform (RTAP) Applications • Case Studies • Real Time Sentiment Analysis • Stock Market Predictions

Module 5: (Lecture 9 hrs.)

Big Data Frameworks • Introduction To NoSQL • Aggregate Data Models • Hbase • Data Model And Implementations • Hbase Clients • Examples • Cassandra • Data Model • Examples • Cassandra Clients • Hadoop Integration • Pig • Grunt • Pig Data Model • Pig Latin • Developing And Testing Pig Latin Scripts • Hive • Data Types And File Formats • HiveQL Data Definition • HiveQL Data Manipulation • HiveQL Queries

Module 1: (Lecture 10 hrs.)

Introduction • Hard Vs. Soft Real Time Systems • A Reference Model Of Real Time System • Real-time Scheduling • Clock Driven Approach • Weighted Round-robin Approach • Priority Driven Approach • Dynamic Vs. Static System • Effective Release Times And Deadlines • EDF And LST Algorithm • Optimality And Non-Optimality Of The EDF And LST Algorithms • Off Line Vs. Online Scheduling

Module 2: (Lecture 6 hrs.)

Clock-Driven Scheduling • Static • Time-Driven Scheduler • General Structure Of Cyclic Schedules • Cyclic Executives • Improving The Average Response Time Of Aperiodic Jobs • Scheduling Sporadic Jobs

Module 3: (Lecture 7 hrs.)

Priority Driven Scheduling Of Periodic Tasks • Fixe-priority Vs. Dynamic Priority Algorithms • Maximum Schedulable Utilization • Optimality Of The RM And DM Algorithms • A Schedulability Test For Fixed-priority Tasks With Short Response Times • Sufficient Schedulability Conditions For The RM And DM Algorithms

Module 4: (Lecture 6 hrs.)

Scheduling Aperiodic And Sporadic Jobs In Priority-Driven Systems • Assumptions And Approaches • Deferrable Servers • Sporadic Servers • Constant Utilization • Total Bandwidth And Weighted Fair-Queueing Servers

Module 5: (Lecture 8 hrs.)

Resources And Resource Access Control • Resource Contention • Resource Access Control • Non-preemptive Critical Section • Basic Priority-Inheritance Protocol • Basic Priority Ceiling Protocol • Stack Based • Priority-ceiling Protocol • Preemption Ceiling Protocol

Module 6: (Lecture 5 hrs.)

Multiprocessor Scheduling • Resource Access Control • Synchronization • Model Of Multiprocessor & Distributed Systems • Task Assignment • Multiprocessor Priority-ceiling Protocol • Elements Of Scheduling Algorithms For End-to-End Periodic Tasks • IPS Protocols • PM Protocols • MPM Protocol

Module 1: (Lectures 6 hrs.)

Introduction • Overview Of Block Chain • Public Ledgers • Bitcoin • Smart Contracts • Block In A Block Chain • Transactions • Distributed Consensus • Public Vs Private Block Chain • Understanding Crypto Currency To Block Chain • Permissioned Model Of Block Chain • Overview Of Security Aspects Of Block Chain Basic Crypto Primitives • Cryptographic Hash Function • Properties Of A Hash Function • Hash Pointer And Merkle Tree • Digital Signature • Public Key Cryptography • A Basic Cryptocurrency

Module 2: (Lectures 10 hrs.)

Understanding Block Chain With Crypto Currency • Bitcoin And Block Chain • Creation Of Coins • Payments And Double Spending • Bitcoin Scripts • Bitcoin P2P Network • Transaction In Bitcoin Network • Block Mining • Block Propagation And Block Relay • Working With Consensus In Bitcoin • Distributed Consensus In Open Environments • Consensus In A Bitcoin Network • Proof Of Work (PoW) • Basic Introduction • Hashcash PoW • Bitcoin PoW • Attacks On Pow And The Monopoly Problem • Proof Of Stake • Proof Of Burn And Proof Of Elapsed Time • The Life Of A Bitcoin Miner • Mining Difficulty • Mining Pool

Module 3: (Lectures 12 hrs.)

Understanding Block Chain For Enterprises • Permissioned Block Chain • Permissioned Model And Use Cases • Design Issues For Permissioned Block Chains • Execute Contracts • State Machine Replication • Overview Of Consensus Models For Permissioned Block Chain • Distributed Consensus In Closed Environment • Paxos • RAFT Consensus • Byzantine General Problem • Byzantine Fault Tolerant System • Lamport-Shostak-Pease BFT Algorithm • BFT Over Asynchronous Systems • Enterprise Application Of Block Chain • Cross Border Payments • Know Your Customer (KYC) • Food Security • Mortgage Over Block Chain • Block Chain Enabled Trade • We Trade Trade Finance Network • Supply Chain Financing • Identity On Block Chain

Module 4: (Lectures 12 hrs.)

Block Chain Application Development • Hyperledger Fabric • Architecture • Identities And Policies • Membership And Access Control • Channels • Transaction Validation • Writing Smart Contract Using Hyperledger Fabric • Writing Smart Contract Using Ethereum • Overview Of Ripple And Corda

Module 1:(Lectures 10 hrs.)

Optimization Techniques • Model Formulation • Models • General L.R Formulation • Simplex Techniques • Sensitivity Analysis • Inventory Control Models

Module 2:(Lectures 8 hrs.)

Formulation Of A LPP • Graphical Solution Revised Simplex Method • Duality Theory • Dual Simplex Method • Sensitivity Analysis • Parametric Programming

Module 3:

T Flow Problem • Max Flow Problem • CPM/PERT

Module 4:(Lectures 7 hrs.)

Scheduling And Sequencing • Single Server And Multiple Server Models • Deterministic Inventory Models • Probabilistic Inventory Control Models • Geometric Programming

Module 5:(Lectures 8 hrs.)

Competitive Models • Single And Multi-channel Problems • Sequencing Models • Dynamic Programming • Flow In Networks • Elementary Graph Theory • Game Theory Simulation

Module 1: (Lectures 12 hrs.)

Introduction To Information Retrieval • Goals And History Of IR • The Impact Of The Web On IR • Unstructured And Semi-structured Text • Basic IR Models Inverted Index And Boolean Queries • Boolean And Vector-space Retrieval Models • Ranked Retrieval • Text-similarity Metrics • TF-IDF (term Frequency/inverse Document Frequency) Weighting • Cosine Similarity • Basic Tokenizing • Indexing • Implementation Of Vector-Space Retrieval • Simple Tokenizing • Stop-word Removal • Stemming • Inverted Indices • Efficient Processing With Sparse Vectors

Module 2: (Lectures 8 hrs.)

Experimental Evaluation Of IR • Performance Metrics • Recall • Precision • F-measure • Query Operations • Relevance Feedback • Query Expansion • Query Languages • Text Representation • Word Statistics • Porter Stemmer • Index Term Selection • Using Thesauri • Metadata And Markup Languages (SGML, HTML, XML)

Module 3: (Lectures 10 hrs.)

Web Search • Introduction • Spidering • Interfaces • Link Analysis Text Categorization • Categorization Algorithms • Language-Model Based Retrieval • Text Clustering • Applications To Web Search And Information Organization

Module 4: (Lectures 10 hrs.)

Recommender Systems • Collaborative Filtering And Content-based Recommendation Of Documents And Products • Information Extraction And Integration • Extracting Data From Text • Semantic Web • Collecting And Integrating Specialized Information On The Web

Module 1: (Lecture 8 hrs.)

Introduction To Cryptography • Cryptographic Hash Functions • SHA-256 • Hash Pointers And Data Structures • Merkle Tree

Module 2: (Lecture 8 hrs.)

Digital Signatures • Elliptic Curve Group • Elliptic Curve Digital Signature Algorithm (ECDSA) • Public Keys As Identities • A Simple Crypto Currency

Module 3: (Lecture 8 hrs.)

Centralization Vs. Decentralization • Distributed Consensus • Consensus Without Identity Using A Block Chain • Incentives And Proof Of Work • Bitcoin Transactions • Bitcoin Scripts • Applications Of Bitcoin Scripts • Bitcoin Blocks • The Bitcoin Network

Module 4: (Lecture 8 hrs.)

Simple Local Storage • Hot And Cold Storage • Splitting And Sharing Keys • Online Wallets And Exchanges • Payment Services • Transaction Fees • Currency Exchange Markets

Module 5: (Lecture 8 hrs.)

Bitcoin Mining • Mining Pools • Mining Incentives And Strategies • Bitcoin And Anonymity • Anonymity Basics • Mixing • Zerocoin And Zerocash

Module 1: (Lecture 8 hrs.)

Data Warehousing And Business Analysis • Data Warehousing Components • Building A Data warehouse • Data Warehouse Architecture • DBMS Schemas For Decision Support • Data Extraction • Cleanup • Transformation Tools • Metadata • Reporting • Query Tools And Applications • Online Analytical Processing (OLAP) • OLAP And Multidimensional Data Analysis

Module 2: (Lecture 8 hrs.)

Data Mining • Data Mining Functionalities • Data Preprocessing • Data Cleaning • Data Integration And Transformation • Data Reduction • Data Discretization And Concept Hierarchy Generation • Architecture Of A Typical Data Mining Systems • Classification Of Data Mining Systems • Association Rule Mining • Efficient And Scalable Frequent Item set Mining Methods • Mining Various Kinds Of Association Rules • Association Mining To Correlation Analysis • Constraint-Based Association Mining

Module 3: (Lecture 8 hrs.)

Classification And Prediction • Issues Regarding Classification And Prediction • Classification By Decision Tree Introduction • Bayesian Classification • Rule Based Classification • Classification By Back propagation • Support Vector Machines • Associative Classification • Lazy Learners • Other Classification Methods • Prediction • Accuracy And Error Measures • Evaluating The Accuracy Of A Classifier Or Predictor • Ensemble Methods • Model Section

Module 4: (Lecture 8 hrs.)

Cluster Analysis • Types Of Data In Cluster Analysis • A Categorization Of Major Clustering Methods • Partitioning Methods • Hierarchical Methods • Density-Based Methods • Grid-Based Methods • Model-Based Clustering Methods • Clustering High-Dimensional Data • Constraint-Based Cluster Analysis • Outlier Analysis

Module 5: (Lecture 8 hrs.)

Mining Object • Spatial • Multimedia • Text And Web Data • Multidimensional Analysis And Descriptive Mining Of Complex Data Objects • Spatial Data Mining • Multimedia Data Mining • Text Mining • Mining The World Wide Web

Module 1: (Lecture 8 hrs.)

Algorithms For Integer Arithmetic • Divisibility • GCD Computation • Euclid's Algorithm • Extended Euclid's Algorithm • Modular Arithmetic • Modular Exponentiation • Montgomery Arithmetic • Congruence • Chinese Remainder Theorem • Hensel Lifting • Orders And Primitive Roots • Quadratic Residues • Integer And Modular Square Roots • Prime Number Theorem • Continued Fractions And Rational Approximations

Module 2: (Lecture 8 hrs.)

Representation Of Finite Fields • Prime And Extension Fields • Representation Of Extension Fields • Polynomial Basis • Primitive Elements • Normal Basis • Optimal Normal Basis • Irreducible Polynomials • Algorithms For Polynomials • Root-finding And Factorization • Lenstra-Lenstra-Lovasz Algorithm • Polynomials Over Finite Fields

Module 3: (Lecture 6 hrs.)

Elliptic Curves • The Elliptic Curve Group • Elliptic Curves Over Finite Fields • Schoof's Point Counting Algorithm

Module 4: (Lecture 8 hrs.)

Primality Testing Algorithms • Fermat Test • Miller-Rabin Test • Solovay-Strassen Test • AKS Test • Integer Factoring Algorithms • Trial Division • Pollard Rho Method • P-1 Method • CFRAC Method • Quadratic Sieve Method • Elliptic Curve Method

Module 5: (Lecture 8 hrs.)

Computing Discrete Logarithms Over Finite Fields • Baby-step-giant-step Method • Pollard Rho Method • Pohlig-Hellman Method • Index Calculus Methods • Linear Sieve Method • Coppersmith's Algorithm • Applications • Algebraic Coding Theory • Cryptography

Module 1: (Lecture 6 hrs.)

Introduction To Advance Operating System • Comparative Study Of OS • LINUX • Linux File System + Measurements • The Log Structured File System • Server Less Network File Systems • The Coda File System • AFS • Virtual Memory • Stack/ Buffer Overflow • Address Space Layout Randomization (ASLR) User-Level Virtual Memory • Global Network Scheduling • Network Optimization • Extensible Operating Systems • Issues Of Security In OS • Cryptographic File Systems

Module 2: (Lecture 6 hrs.)

Distributed Operating Systems • System Architecture Types • Issues In Distributed Operating Systems • Naming • Scalability • Security • Client-Server Model • Process Synchronization • Global Knowledge • Etc • RPC • Message Passing • Absence Of Global Lock • Absence Of Shared Memory • Lamport's Logical Clock • Chandy Lamport's Algorithm • Termination Detection • Distributed Mutual Exclusion • Non Token Based Algorithms • Ricart Agarwala Algorithm • Lamport's Algorithm • Generalized Non-Token Based Algorithm • Comparative Performance Analysis

Module 3: (Lecture 6 hrs.)

Synchronization • Clock Synchronization • Event Ordering • Mutual Exclusion • Deadlock • Election Algorithms • Desirable Features Of Good Global Scheduling Algorithms • Task Assignment Approach • Load Balancing Approach • Load Sharing Approach • Process Management • Process Migration • Threads Distributed Deadlock Detection • Centralized/Distributed/ Hierarchical Control • Path Pushing Algorithm • Edge-Chasing Algorithm • Ho-Ramamoorthy Algorithms

Module 4: (Lecture 6 hrs.)

Resource Management In Distributed Systems • Distributed File Systems • Mounting • Caching • Bulk Data Transfer • Design Issues • Cache Consistency • Scalability • Log Structured File systems • Distributed Shared Memory • Central-Server Algorithm • Full-Replication Algorithm • Etc • Coherence Protocols • Granularity • Page Replacement • Distributed Scheduling • Load • Classification • Load Balancing And Load Sharing • Policies For Transfer • Selection • Location • Information • Stability • Load Balancing Algorithms • Load Sharing Case Studies

Module 5: (Lecture 6 hrs.)

Fault Tolerance • Recovery • Protection And Security • Atomic Actions And Commit • Commit Protocols • Voting Protocols • Dynamic Voting • Classification Of Failures • Backward And Forward Error Recovery • Synchronous/Asynchronous Checkpoints And Recovery • Recovery In Concurrent Systems • Access Matrix Model • Advanced Models Of Protection • Cryptography

Module 6: (Lecture 6 hrs.)

Multiprocessor And Database Operating Systems • Tightly And Loosely Coupled Systems • Interconnect Networks • Caching • Hypercube Architectures • Threads • Process Synchronization In MP Systems • Process Scheduling In MP Systems • Requirements Of Database OS • Transactions • Conflicts • Serializability Theory • Distributed Database Systems • Concurrency Control Algorithms • Lock Based Algorithms • Timestamp Based Algorithms • 2PL

Module 7: (Lecture 6 hrs.)

Virtualization • Introduction • Simulation • Emulation • Para-Virtualization • Full virtualization • X86 Virtualization • Privileged Instructions • Control Sensitive Instructions • Trap And Emulate • Binary Translation • X86 Hardware Virtualization Vmxon/vmxoff • Vmentry • Vm Exit • Intel VTd • VMCS • Shadow Page Tables • EPT/NPT

Module 1: (Lecture 8 hrs.)

Introduction To Genetic Algorithm • Genetic Algorithms • Traditional And Search Methods And Their Differences • A Simple Genetic Algorithm

Module 2: (Lecture 8 hrs.)

Genetic Algorithms Revisited • The Fundamental Theorem • Schema Processing

Module 3: (Lecture 8 hrs.)

Two & K-Armed Bandit Problem • Hypothesis • Schemata And Revisited

Module 4: (Lecture 8 hrs.)

Computer Implementation Of A Genetic Algorithm • Data Structures • Reproduction • Crossover And Mutation • A Time To Reproduce • A Time To Cross • How Well Does It Work • Mapping Objective Functions To Fitness Form • Fitness Scaling • Coding • A Multiparameter Mapped • Fixed-Point Coding • Discretization • Constraints

Module 5: (Lecture 8 hrs.)

Applications Of Genetic Algorithms • The Rise Of Genetic Algorithms • Genetic Algorithm Applications Of Historical Interest • De Jong And Function Optimization • Improvements In Basic Technique • Current Applications Of Genetic Algorithms • Genetics-Based Machine Learning • Whence It Came • What Is Classifier System • Rule And Message • Genetic Algorithm

Module 1: (Lecture 4 hrs.)

Introduction • Distributed Computing And Enabling Technologies • Cloud Fundamentals • Cloud Definition • Evolution • Architecture • Applications • Deployment Models • Service Models

Module 2: (Lecture 5 hrs.)

Virtualization • Issues With Virtualization • Virtualization Technologies And Architectures • Internals Of Virtual Machine Monitors/hypervisors • Virtualization Of Data Centers • Issues With Multitenancy

Module 3: (Lecture 6 hrs.)

Implementation • Study Of Cloud Computing Systems Like Amazon EC2 And S3 • Google App Engine • Microsoft Azure • Build Private/Hybrid Cloud Using Open Source Tools • SLA Management

Module 4: (Lecture 12 hrs.)

Resource Management • Cloud Resource Provisioning Plan (advance Reservation • On Demand Plan • Spot Instances) • Various Scheduling And Load Balancing Techniques To Improve QoS Parameters • Resource Optimization Algorithms • Task Migration And VM Migration Technique

Module 5: (Lecture 7 hrs.)

Security • Vulnerability Issues And Security Threats • Application-level Security • Data Level Security • Virtual Machine Level Security • Infrastructure Security • Multi-tenancy Issues

Module 6: (Lecture 6 hrs.)

Advances • Green Cloud • Mobile Cloud Computing • Fog Computing • Internet Of Things

Module 1: (Lectures 6 hrs.)

Introduction To Quantum Computing • Motivation For Studying Quantum Computing • Major Players In The Industry (IBM, Microsoft, Rigetti, D-Wave Etc) • Origin Of Quantum Computing • Overview Of Major Concepts In Quantum Computing • Qubits And Multi-qubits States • Bra-ket Notation • Bloch Sphere Representation • Quantum Superposition • Quantum Entanglement

Module 2: (Lectures 9 hrs.)

Math Foundation For Quantum Computing • Matrix Algebra • Basis Vectors And Orthogonality • Inner Product And Hilbert Spaces • Matrices And Tensors • Unitary Operators And Projectors • Dirac Notation • Eigen Values And Eigen Vectors

Module 3: (Lectures 8 hrs.)

Building Blocks For Quantum Program • Architecture Of A Quantum Computing Platform • Details Of Q-bit System Of Information Representation • Block Sphere • Multi-qubits States • Quantum Superposition Of Qubits (valid And Invalid Superposition) • Quantum Entanglement • Useful States From Quantum Algorithmic Perceptive E.g. Bell State • Operation On Qubits • Measuring And Transforming Using Gates • Quantum Logic Gates And Circuit • Pauli • Hadamard • Phase Shift • Controlled Gates • Ising • Deutsch • Swap Etc • Programming Model For A Quantum Computing Program • Steps Performed On Classical Computer • Steps Performed On Quantum Computer • Moving Data Between Bits And Qubits

Module 4: (Lectures 18 hrs.)

Quantum Algorithms • Basic Techniques Exploited By Quantum Algorithms • Amplitude Amplification • Quantum Fourier Transform • Phase Kick-back • Quantum Phase Estimation • Quantum Walks • Major Algorithms • Shor's Algorithm • Grover's Algorithm • Deutsch's Algorithm • Deutsch - Jozsa Algorithm • OSS Toolkits For Implementing Quantum Program • IBM Quantum Experience • Microsoft Q • Rigetti PyQuil (QPU/QVM)

Module 1: (Lecture 8 hrs.)

Consistency • Atomicity • Durability • Isolation • Flat Transactions • Providing Structure Within A Transaction • Structuring An Application As Multiple Transactions

Module 2: (Lecture 8 hrs.)

Schedules And Schedule Equivalence • Recoverability • Cascaded Aborts And Strictness • Models For Concurrency Control • A Strategy For Immediate-Update Pessimistic Concurrency Controls • Design Of An Immediate-Update Pessimistic Concurrency Control • Objects And Semantic Commutativity • Atomicity • Recoverability And Compensating Operations • Locking And SQL Isolation Levels • Granular Locking • Intention Locks And Index Locks • Tuning Transactions • Multi version Concurrency Controls

Module 3: (Lecture 8 hrs.)

Crash • Abort And Media Failure • Immediate-Update Systems And Write-Ahead Logs • Recovery In Deferred-Update Systems • Recovery From Media Failure

Module 4: (Lecture 8 hrs.)

Transaction Processing In A Centralized System • Transaction Processing In A Distributed System • Global Atomicity And The Transaction Manager • Remote Procedure Call • Pear-to-Pear Communication • Event Communication • Storage Architectures • Transaction Processing On The Internet • Implementing The ACID Properties • Distributed Deadlock • Global Serialization

Module 5: (Lecture 8 hrs.)

Authentication • Authorization And Encryption • Digital Signatures • Key Distribution And Authentication • Authorization • Authenticated RPC • Electronic Commerce • Certificates • Passport • SSO • SET Protocol • Dual Signatures • Goods Atomicity • Certified Delivery • Escrow

Module 1: (Lecture 6 hrs.)

Introduction • Importance Of Pattern Recognition • Features • Feature Vectors • Classifiers • Supervised Versus Unsupervised Pattern Recognition

Module 2: (Lecture 6 hrs.)

Bayes Decision Theory • Discriminant Functions And Services O The Normal Distribution • Bayesian Classification • Estimating Probability Density Functions • Nearest Neighbour Rules Bayesian Networks

Module 3: (Lecture 6 hrs.)

Linear And Nonlinear Classifiers • The Perceptron Algorithm • Least-Squares Methods • Nonlinear Classifiers • Multilayer Perceptron's • Back Propagation Algorithm • Decision Trees • Combinations Of Classifiers • Boosting

Module 4: (Lecture 6 hrs.)

Feature Selection • Data Pre-processing • ROC Curves • Class Separability Measures • Feature Subset Selection • Bayesian Information Criterion

Module 5: (Lecture 6 hrs.)

Dimensionality Reduction • Basis Vectors • Singular Value Decomposition • Independent Component Analysis • Kernel PCA • Wavelets

Module 6: (Lecture 6 hrs.)

Additional Features And Template Matching • Texture • Shape And Size Characterization • Fractals • Features For Audio • Template Matching Using Dynamic Time Warping And Edit Distance • Context Dependent Classification

Module 7: (Lecture 6 hrs.)

Clustering • Sequential Algorithms • Hierarchical Algorithms • Functional Optimization-Based Clustering Graph Clustering • Learning Clustering • Clustering High Dimensional Data • Subspace Clustering • Cluster Validity Measure

Module 1: Introduction (Lecture 4 hrs.)

Brief Introduction Of Big Data Problem • Overview Of Linear Algebra • Probability • Numerical Computation • Basics Of Machine learning/Feature Engineering

Module 2: Basics of Neural networks (Lecture 4 hrs.)

Neural Networks • Tools For Deep Learning Network • Shallow Vs Deep Network

Module 3: Feed forward Networks (Lecture 6 hrs.)

Multilayer Perceptron • Gradient • Loss Function • Gradient Descent • Stochastic Gradient Descent (SDD) • Backpropagation Algorithm • Empirical Risk Minimization • Regularization • Gradient Based Learning • Cost Function • Learning Rate • Soft Max • Sigmoid Function • Hidden Unit • ReLU • Logistic Sigmoid • Hyperbolic Tangent Architecture Design • Heuristics For Faster Training

Module 4: Unsupervised learning (Lecture 10 hrs.)

Deep Belief Network • Deep Boltzmann Machine (DBM) • Factor Analysis • Auto-encoders (standard, Sparse, Denoising, Contractive, Etc) • Variational Auto-encoders • Adversarial Generative Networks • Auto-encoder • Regularization Optimization For Training Deep Model

Module 5: Advanced topics (Lecture 10 hrs.)

Convolutional Neural Network (CNN) • Architectures • Convolution/pooling Layers • Recurrent Neural Network (RNN)/ Sequence Modeling • Long Short Term Memory Networks (LSTM) • GRU • Encoder Decoder Architectures Reinforcement Learning

Module 6: Practical applications (Lecture 6 hrs.)

Application Of Deep Learning To Computer Vision • Speech Recognition • Natural Language Processing • Etc

Module 1: (Lecture 6 hrs.)

Polygon Triangulation • Triangulation Theory • Area Of Polygon • Segment Intersection • Segment-triangle Intersection • Polygon Partitioning • Monotone Partitioning • Trapezoidalization • Partition Into Monotone Mountains • Linear-Time Triangulation • Convex Partitioning

Module 2: (Lecture 5 hrs.)

Convex Hulls In Two Dimensions • Definitions Of Convexity And Convex Hulls • Naive Algorithms For Extreme Points • Gift Wrapping • QuickHull • Graham's Algorithm • Lower Bound • Incremental Algorithm • Divide And Conquer

Module 3: (Lecture 6 hrs.)

Convex Hulls In Three Dimensions • Polyhedra And Data Structures • Gift Wrapping • Preparata-Hong Algorithm • Incremental Algorithm • Randomized Incremental Algorithm

Module 4: (Lecture 6 hrs.)

Voronoi Diagrams • Definitions And Basic Properties • Delaunay Triangulations • Algorithms • Applications In Detail • Medial Axis • Connection To Convex Hulls • Connection To Arrangements

Module 5: (Lecture 6 hrs.)

Arrangements • Combinatorics Of Arrangements • Incremental Algorithm • Three And Higher Dimensions • Duality • Higher-Order Voronoi • Diagrams • Applications

Module 6: (Lecture 8 hrs.)

Search And Intersection • Segment-Segment Intersection • Segment- Triangle Intersection • Point In Polygon • Point In Polyhedron • Intersection Of Convex Polygons • Intersection Of Segments • Intersection Of Nonconvex Polygons • Extreme Point Of Convex Polygon • Extremal Polytope • Queries • Planar Point Location

Module 7: (Lecture 5 hrs.)

Motion Planning • Shortest Paths • Moving A Disk • Translating A Convex Polygon • Moving A Ladder • Robot Arm Motion • Separability

Module 1: (Lecture 7 hrs.)

Introduction To Big Data • Definition • Characteristic Features • Big Data Applications • Big Data Vs Traditional Data • Risks Of Big Data • Structure Of Big Data • Challenges Of Conventional Systems • Web Data • Evolution Of Analytic Scalability • Evolution Of Analytic Processes • Tools And Methods • Analysis Vs Reporting • Modern Data Analytic Tools

Module 2: (Lecture 9 hrs.)

HADOOP Framework • Distributed File Systems • Large-Scale File System • Organization • HDFS Concepts • Map Reduce Execution • Algorithms Using Map Reduce • Matrix-Vector Multiplication • Hadoop YARN

Module 3: (Lecture 10 hrs.)

Data Analysis • Statistical Methods • Regression Modelling • Multivariate Analysis • Classification • SVM & Kernel Methods • Rule Mining • Cluster Analysis • Types Of Data In Cluster Analysis • Partitioning Methods • Hierarchical Methods • Density Based Methods • Grid Based Methods • Model Based Clustering Methods • Clustering High Dimensional Data • Predictive Analytics • Data Analysis Using R

Module 4: (Lecture 7 hrs.)

Mining Data Streams • Streams • Concepts • Stream Data Model And Architecture • Sampling Data In A Stream • Mining Data Streams And Mining Time-series Data • Real Time Analytics Platform (RTAP) Applications • Case Studies • Real Time Sentiment Analysis • Stock Market Predictions

Module 5: (Lecture 9 hrs.)

Big Data Frameworks • Introduction To NoSQL • Aggregate Data Models • Hbase • Data Model And Implementations • Hbase Clients • Examples • Cassandra • Data Model • Examples • Cassandra Clients • Hadoop Integration • Pig • Grunt • Pig Data Model • Pig Latin • Developing And Testing Pig Latin Scripts • Hive • Data Types And File Formats • HiveQL Data Definition • HiveQL Data Manipulation • HiveQL Queries

Module 1: (Lecture 10 hrs.)

Introduction • Hard Vs. Soft Real Time Systems • A Reference Model Of Real Time System • Real-time Scheduling • Clock Driven Approach • Weighted Round-robin Approach • Priority Driven Approach • Dynamic Vs. Static System • Effective Release Times And Deadlines • EDF And LST Algorithm • Optimality And Non-Optimality Of The EDF And LST Algorithms • Off Line Vs. Online Scheduling

Module 2: (Lecture 6 hrs.)

Clock-Driven Scheduling • Static • Time-Driven Scheduler • General Structure Of Cyclic Schedules • Cyclic Executives • Improving The Average Response Time Of Aperiodic Jobs • Scheduling Sporadic Jobs

Module 3: (Lecture 7 hrs.)

Priority Driven Scheduling Of Periodic Tasks • Fixe-priority Vs. Dynamic Priority Algorithms • Maximum Schedulable Utilization • Optimality Of The RM And DM Algorithms • A Schedulability Test For Fixed-priority Tasks With Short Response Times • Sufficient Schedulability Conditions For The RM And DM Algorithms

Module 4: (Lecture 6 hrs.)

Scheduling Aperiodic And Sporadic Jobs In Priority-Driven Systems • Assumptions And Approaches • Deferrable Servers • Sporadic Servers • Constant Utilization • Total Bandwidth And Weighted Fair-Queueing Servers

Module 5: (Lecture 8 hrs.)

Resources And Resource Access Control • Resource Contention • Resource Access Control • Non-preemptive Critical Section • Basic Priority-Inheritance Protocol • Basic Priority Ceiling Protocol • Stack Based • Priority-ceiling Protocol • Preemption Ceiling Protocol

Module 6: (Lecture 5 hrs.)

Multiprocessor Scheduling • Resource Access Control • Synchronization • Model Of Multiprocessor & Distributed Systems • Task Assignment • Multiprocessor Priority-ceiling Protocol • Elements Of Scheduling Algorithms For End-to-End Periodic Tasks • IPS Protocols • PM Protocols • MPM Protocol

Module 1: (Lectures 6 hrs.)

Introduction • Overview Of Block Chain • Public Ledgers • Bitcoin • Smart Contracts • Block In A Block Chain • Transactions • Distributed Consensus • Public Vs Private Block Chain • Understanding Crypto Currency To Block Chain • Permissioned Model Of Block Chain • Overview Of Security Aspects Of Block Chain Basic Crypto Primitives • Cryptographic Hash Function • Properties Of A Hash Function • Hash Pointer And Merkle Tree • Digital Signature • Public Key Cryptography • A Basic Cryptocurrency

Module 2: (Lectures 10 hrs.)

Understanding Block Chain With Crypto Currency • Bitcoin And Block Chain • Creation Of Coins • Payments And Double Spending • Bitcoin Scripts • Bitcoin P2P Network • Transaction In Bitcoin Network • Block Mining • Block Propagation And Block Relay • Working With Consensus In Bitcoin • Distributed Consensus In Open Environments • Consensus In A Bitcoin Network • Proof Of Work (PoW) • Basic Introduction • Hashcash PoW • Bitcoin PoW • Attacks On Pow And The Monopoly Problem • Proof Of Stake • Proof Of Burn And Proof Of Elapsed Time • The Life Of A Bitcoin Miner • Mining Difficulty • Mining Pool

Module 3: (Lectures 12 hrs.)

Understanding Block Chain For Enterprises • Permissioned Block Chain • Permissioned Model And Use Cases • Design Issues For Permissioned Block Chains • Execute Contracts • State Machine Replication • Overview Of Consensus Models For Permissioned Block Chain • Distributed Consensus In Closed Environment • Paxos • RAFT Consensus • Byzantine General Problem • Byzantine Fault Tolerant System • Lamport-Shostak-Pease BFT Algorithm • BFT Over Asynchronous Systems • Enterprise Application Of Block Chain • Cross Border Payments • Know Your Customer (KYC) • Food Security • Mortgage Over Block Chain • Block Chain Enabled Trade • We Trade Trade Finance Network • Supply Chain Financing • Identity On Block Chain

Module 4: (Lectures 12 hrs.)

Block Chain Application Development • Hyperledger Fabric • Architecture • Identities And Policies • Membership And Access Control • Channels • Transaction Validation • Writing Smart Contract Using Hyperledger Fabric • Writing Smart Contract Using Ethereum • Overview Of Ripple And Corda

Module 1:(Lectures 10 hrs.)

Optimization Techniques • Model Formulation • Models • General L.R Formulation • Simplex Techniques • Sensitivity Analysis • Inventory Control Models

Module 2:(Lectures 8 hrs.)

Formulation Of A LPP • Graphical Solution Revised Simplex Method • Duality Theory • Dual Simplex Method • Sensitivity Analysis • Parametric Programming

Module 3:

T Flow Problem • Max Flow Problem • CPM/PERT

Module 4:(Lectures 7 hrs.)

Scheduling And Sequencing • Single Server And Multiple Server Models • Deterministic Inventory Models • Probabilistic Inventory Control Models • Geometric Programming

Module 5:(Lectures 8 hrs.)

Competitive Models • Single And Multi-channel Problems • Sequencing Models • Dynamic Programming • Flow In Networks • Elementary Graph Theory • Game Theory Simulation

Module 1: (Lectures 12 hrs.)

Introduction To Information Retrieval • Goals And History Of IR • The Impact Of The Web On IR • Unstructured And Semi-structured Text • Basic IR Models Inverted Index And Boolean Queries • Boolean And Vector-space Retrieval Models • Ranked Retrieval • Text-similarity Metrics • TF-IDF (term Frequency/inverse Document Frequency) Weighting • Cosine Similarity • Basic Tokenizing • Indexing • Implementation Of Vector-Space Retrieval • Simple Tokenizing • Stop-word Removal • Stemming • Inverted Indices • Efficient Processing With Sparse Vectors

Module 2: (Lectures 8 hrs.)

Experimental Evaluation Of IR • Performance Metrics • Recall • Precision • F-measure • Query Operations • Relevance Feedback • Query Expansion • Query Languages • Text Representation • Word Statistics • Porter Stemmer • Index Term Selection • Using Thesauri • Metadata And Markup Languages (SGML, HTML, XML)

Module 3: (Lectures 10 hrs.)

Web Search • Introduction • Spidering • Interfaces • Link Analysis Text Categorization • Categorization Algorithms • Language-Model Based Retrieval • Text Clustering • Applications To Web Search And Information Organization

Module 4: (Lectures 10 hrs.)

Recommender Systems • Collaborative Filtering And Content-based Recommendation Of Documents And Products • Information Extraction And Integration • Extracting Data From Text • Semantic Web • Collecting And Integrating Specialized Information On The Web

Module 1: (Lecture 8 hrs.)

Introduction To Cryptography • Cryptographic Hash Functions • SHA-256 • Hash Pointers And Data Structures • Merkle Tree

Module 2: (Lecture 8 hrs.)

Digital Signatures • Elliptic Curve Group • Elliptic Curve Digital Signature Algorithm (ECDSA) • Public Keys As Identities • A Simple Crypto Currency

Module 3: (Lecture 8 hrs.)

Centralization Vs. Decentralization • Distributed Consensus • Consensus Without Identity Using A Block Chain • Incentives And Proof Of Work • Bitcoin Transactions • Bitcoin Scripts • Applications Of Bitcoin Scripts • Bitcoin Blocks • The Bitcoin Network

Module 4: (Lecture 8 hrs.)

Simple Local Storage • Hot And Cold Storage • Splitting And Sharing Keys • Online Wallets And Exchanges • Payment Services • Transaction Fees • Currency Exchange Markets

Module 5: (Lecture 8 hrs.)

Bitcoin Mining • Mining Pools • Mining Incentives And Strategies • Bitcoin And Anonymity • Anonymity Basics • Mixing • Zerocoin And Zerocash