[PDF] SOFTWARE PROJECT MANAGEMENT | SPM STUDENT NOTES | JNTU

 

JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY (JNTU)

(ML) MACHINE LEARNING  - STUDENT NOTES

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UNIT I Conventional Software Management:

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UNIT II Improving Software Economics:

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UNIT III Life cycle phases:
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UNIT IV Work Flows of the process:
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UNIT V Project Control and Process instrumentation:
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UNIT I
Conventional Software Management: The waterfall model, conventional  software Management performance. Evolution of Software Economics: Software Economics, pragmatic software cost estimation

UNIT II
Improving Software Economics: Reducing Software product size, improving software processes, improving team effectiveness, improving automation, Achieving required quality, peer inspections.
The old way and the new: The principles of conventional software engineering,
principles of modern software management, transitioning to an iterative process

UNIT III
Life cycle phases: Engineering and production stages, Inception, Elaboration,
construction, transition phases.
Artifacts of the process: The artifact sets, Management artifacts, Engineering
artifacts, programmatic artifacts. Model based software architectures: A Management perspective and technical perspective.

UNIT IV
Work Flows of the process: SoReference Books :
1. Applied Software Project Management, Andrew Stellman & Jennifer Greene,
O‟Reilly, 2006
2. Head First PMP, Jennifer Greene & Andrew Stellman, O‟Reilly,2007
3. Software Engineering Project Managent, Richard H. Thayer & Edward Yourdon,
second edition,Wiley India, 2004.
4. Agile Project Management, Jim Highsmith, Pearson education, 2004
5. The art of Project management, Scott Berkun, O‟Reilly, 2005.
6. Software Project Management in Practice, Pankaj Jalote, Pearson Education,2002ftware process workflows, Inter Trans workflows.
Checkpoints of the Process: Major Mile Stones, Minor Milestones, Periodic status assessments. Iterative Process Planning: Work breakdown structures, planning guidelines, cost and schedule estimating, Interaction planning process, Pragmatic planning.
Project Organizations and Responsibilities: Line-of-Business Organizations, Project Organizations, evolution of Organizations.
Process Automation: Automation Building Blocks, The Project Environment

UNIT V
Project Control and Process instrumentation: The server care Metrics, Management indicators, quality indicators, life cycle expectations pragmatic Software Metrics, Metrics automation. Tailoring the Process: Process discriminates, Example.
Future Software Project Management: Modern Project Profiles Next generation
Software economics, modern Process transitions.
Case Study: The Command Center Processing and Display System-Replacement
(CCPDS-R)

Text Books:
1. Software Project Management, Walker Royce, Pearson Education.
2. Software Project Management, Bob Hughes & Mike Cotterell, fourth edition,Tata Mc-Graw Hill

Reference Books :
1. Applied Software Project Management, Andrew Stellman & Jennifer Greene,
O‟Reilly, 2006
2. Head First PMP, Jennifer Greene & Andrew Stellman, O‟Reilly,2007
3. Software Engineering Project Managent, Richard H. Thayer & Edward Yourdon, second edition,Wiley India, 2004.
4. Agile Project Management, Jim Highsmith, Pearson education, 2004
5. The art of Project management, Scott Berkun, O‟Reilly, 2005.
6. Software Project Management in Practice, Pankaj Jalote, Pearson Education,2002

[PDF]&[PPT] MACHINE LEARNING NOTES | ML STUDENT NOTES | JNTU

 JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY (JNTU)

(ML) MACHINE LEARNING  - STUDENT NOTES

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Unit I:What is Machine Learning?: 

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Unit 2: Evaluating Hypotheses:

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Unit 3: Dimensionality Reduction:
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Unit 4: Linear Discrimination:
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Unit 5: Kernel Machines:
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MACHINE LEARNING (Single PDF) All Topics:

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MACHINE LEARNING  SYLLABUS

Unit I:What is Machine Learning?, Examples of machine learning applications, supervised Learning: learning a class from examples, Vapnik- Chervonenkis dimension, probably approximately correct learning, noise, learning multiple classes, regression, model selection and generalization, dimensions of a supervised machine learning algorithm. Decision Tree Learning: Introduction, Decisions Tree representation, Appropriate problems for decision tree learning, the basic decision tree learning algorithm, Hypothesis space search in decision tree learning, Inductive bias in decision tree learning, issues in decision tree learning, Artificial Neural Networks: Introduction, Neural Network  Representation – Problems – Perceptrons – Multilayer Networks and Back Propagation Algorithm, Remarks on the BACKPROPGRATION Algorithm, An illustrative Example: Face Recognition, Advanced Topics in Artificial Neural  Networks.

Unit 2: Evaluating Hypotheses: Motivation, Estimating hypothesis accuracy, basics of sampling theory, a general approach for deriving confidence intervals, differences in error of two hypothesis, comparing learning algorithms, Bayesian Learning: Introduction, Bayes Theorem, Bayes Theorem and Concept Learning, Maximum Likelihood and least squared error hypothesis, Maximum Likelihood hypothesis for predicting probabilities, Minimum Description Length Principle, Bayes Optimal Classifier, Gibbs Algorithm, Naïve Bayes Classifier , Bayesian Belief Network, EM Algorithm

Unit 3: Dimensionality Reduction: Introduction, Subset selection, principle component analysis, feature embedding, factor analysis, singular value decomposition and matrix factorization, multidimensional scaling, linear discriminant analysis, canonical correlation analysis, Isomap, Locally linear embedding, laplacian eigenmaps, Clustering: Introduction, Mixture densities, K- Means clustering, Expectations- Maximization algorithm, Mixture of latent variable models, supervised learning after clustering, spectral clustering, Hierarchal clustering, Choosing the number of clusters, Nonparametric Methods: Introduction, Non Parametric density estimation, generalization to multivariate data, nonparametric classification, condensed nearest neighbor, Distance based classification, outlier detection, Nonparametric regression: smoothing models, how to choose the smoothing parameter

Unit 4: Linear Discrimination: Introduction, Generalizing the linear model, geometry of the linear discrimination, pair wise separation, parametric discrimination revisited, gradient descent, logistic discrimination, discrimination by regression, learning to rank, Multilayer Perceptrons: Introduction, the perceptron, training a perceptron, learning Boolean functions, multilayer perceptrons, MLP as a universal approximator, Back propagation algorithm, Training procedures, Tuning the network size, Bayesian view of learning, dimensionality reduction, learning time, deep learning

Unit 5: Kernel Machines: Introduction, Optimal separating hyperplane, the non separable case: Soft Margin Hyperplane, ν-SVM, kernel Trick, Vectorial kernels, defining kernels, multiple kernel learning, multicast kernel machines, kernel machines for regression, kernel machines for ranking, one-class kernel machines, large margin nearest neighbor classifier, kernel dimensionality reduction, Graphical models: Introduction, Canonical cases for conditional independence, generativeUnit 5: Kernel Machines: models, d separation, belief propagation, undirected Graphs: Markov Random files, Learning the structure of a graphical model, influence diagrams.

Text Books:
1) Machine Learning by Tom M. Mitchell, Mc Graw Hill Education, Indian Edition, 2016.
2) Introduction to Machine learning, Ethem Alpaydin, PHI, 3 rd Edition, 2014

References Books:

1) Machine Learning: An Algorithmic Perspective, Stephen Marsland, Taylor & Francis,CRC Press Book,



@Credits: Syllabus Taken From JNTU

INFORMATION SECURITY NOTES | IS Student Notes | JNTU

JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY (JNTU)

(IS) INFORMATION SECURITY  - STUDENT NOTES

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Unit-I Computer Security concepts: 

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Unit-II Introduction to Number theory: 

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Unit-III Cryptographic Hash functions:
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Unit-IV Key Management and distribution:
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Unit-V Security at the Transport Layer(SSL and TLS):
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(IS) INFORMATION SECURITY(Single PDF) All Topics:

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INFORMATION SECURITY SYLLABUS

Unit-I Computer Security concepts, The OSI Security Architecture, Security attacks, Security services and Security mechanisms, A model for Network Security Classical encryption techniques- symmetric cipher model, substitution ciphers, transposition ciphers, Steganography. Modern Block Ciphers: Block ciphers principles, Data encryption standard (DES), Strength of DES, linear and differential cryptanalysis, block cipher modes of operations, AES, RC4.

Unit-II Introduction to Number theory – Integer Arithmetic, Modular Arithmetic, Matrices, Linear Congruence, Algebraic Structures, GF(2n) Fields, Primes, Primality Testing, Factorization, Chinese Remainder Theorem, Quadratic Congruence, Exponentiation and Logarithm. Public-key cryptography - Principles of public-key cryptography, RSA Algorithm, Diffie- Hellman Key Exchange, ElGamal cryptographic system, Elliptic Curve Arithmetic, Elliptic curve cryptography

Unit-III Cryptographic Hash functions: Applications of Cryptographic Hash functions, Requirements and security, Hash functions based on Cipher Block Chaining, Secure Hash Algorithm (SHA) Message Authentication Codes: Message authentication Requirements, Message authentication functions, Requirements for Message authentication codes, security of MACs, HMAC, MACs based on Block Ciphers, Authenticated Encryption Digital Signatures-RSA with SHA & DSS

Unit-IV Key Management and distribution: Symmetric key distribution using Symmetric Encryption, Symmetric key distribution using Asymmetric, Distribution of Public keys, X.509 Certificates, Public key Infrastructure. User Authentication: Remote user Authentication Principles, Remote user Authentication using Symmetric Encryption, Kerberos, Remote user Authentication using Asymmetric Encryption, Federated Identity Management, Electronic mail security: Pretty Good Privacy (PGP), S/MIME.

Unit-V Security at the Transport Layer(SSL and TLS): SSL Architecture, Four Protocols, SSL Message Formats, Transport Layer Security, HTTPS, SSH Security at the Network layer (IPSec): Two modes, Two Security Protocols,  Security Association, Security Policy, Internet Key Exchange. System Security: Description of the system, users, Trust and Trusted Systems, Buffer Overflow and Malicious Software, Malicious Programs, worms, viruses, Intrusion Detection System(IDS), Firewalls.

Text books:
1. ―Cryptography and Network Security‖, Behrouz A. Frouzan and Debdeep Mukhopadhyay, Mc Graw Hill Education, 2nd edition, 2013.
2.―Cryptography and Network Security: Principals and Practice‖, William Stallings, Pearson Education, Fifth Edition, 2013.

References:
1. ―Network Security and Cryptography‖, Bernard Menezes, Cengage Learning.
2. ―Cryptography and Security‖, C.K. Shymala, N. Harini and Dr. T.R. Padmanabhan, Wiley-India.
3. ―Applied Cryptography, Bruce Schiener, 2nd edition, John Wiley & Sons.
4. ―Cryptography and Network Security‖, Atul Kahate, TMH.
5. ‗Introduction to Cryptography‖, Buchmann, Springer.
6. ‗Number Theory in the Spirit of Ramanujan‖, Bruce C.Berndt, University Press
7. ―Introduction to Analytic Number Theory‖, Tom M.Apostol, University Press

@Credits: Syllabus Taken From JNTU 

GRID AND CLOUD COMPUTING NOTES | GCC Student Notes | JNTU

JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY (JNTU)

GRID AND CLOUD COMPUTING  - STUDENT NOTES

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UNIT I: INTRODUCTION: 

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UNIT II GRID SERVICES:

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UNIT III VIRTUALIZATION

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UNIT IV PROGRAMMING MODEL

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UNIT V SECURITY

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TEXT BOOK:
1. Kai Hwang, Geoffery C. Fox and Jack J. Dongarra, ―Distributed and Cloud Computing: Clusters, Grids, Clouds and the Future of Internet‖, First Edition, Morgan Kaufman Publisher, an Imprint of Elsevier, 2012.

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GRID AND CLOUD COMPUTING  - SYLLABUS

UNIT I INTRODUCTION
Evolution of Distributed computing: Scalable computing over the Internet – Technologies for network based systems – clusters of cooperative computers - Grid computing Infrastructures – cloud computing - service oriented architecture – Introduction to Grid Architecture and standards – Elements of Grid – Overview of Grid Architecture.

UNIT II GRID SERVICES
Introduction to Open Grid Services Architecture (OGSA) – Motivation – Functionality Requirements – Practical & Detailed view of OGSA/OGSI – Data intensive grid service models – OGSA services.

UNIT III VIRTUALIZATION
Cloud deployment models: public, private, hybrid, community – Categories of cloud computing: Everything as a service: Infrastructure, platform, software - Pros and Cons of cloud computing – Implementation levels of virtualization – virtualization structure – virtualization of CPU, Memory and I/O devices – virtual clusters and Resource Management – Virtualization for data center automation.

UNIT IV PROGRAMMING MODEL
Open source grid middleware packages – Globus Toolkit (GT4) Architecture , Configuration – Usage of Globus – Main components and Programming model - Introduction to Hadoop Framework - MapReduce, Input splitting, map and reduce functions, specifying input and output parameters, configuring and running a job – Design of Hadoop file system, HDFS concepts, command line and Java interface, dataflow of File read & File write.

UNIT V SECURITY
Trust models for Grid security environment – Authentication and Authorization methods – Grid security infrastructure – Cloud Infrastructure security: network, host and application level – aspects of data security, provider data and its security, Identity and access management architecture, IAM practices in the cloud, SaaS, PaaS, IaaS availability in the cloud, Key privacy issues in the cloud.

TEXT BOOK:
1. Kai Hwang, Geoffery C. Fox and Jack J. Dongarra, ―Distributed and Cloud Computing: Clusters, Grids, Clouds and the Future of Internet‖, First Edition, Morgan Kaufman Publisher, an Imprint of Elsevier, 2012.

REFERENCES:
1. Jason Venner, ―Pro Hadoop- Build Scalable, Distributed Applications in the Cloud‖, A Press, 2009
2. Tom White, ―Hadoop The Definitive Guide‖, First Edition. O‘Reilly, 2009.
3. Bart Jacob (Editor), ―Introduction to Grid Computing‖, IBM Red Books, Vervante, 2005
4. Ian Foster, Carl Kesselman, ―The Grid: Blueprint for a New Computing Infrastructure‖, 2nd Edition, Morgan Kaufmann.
5. Frederic Magoules and Jie Pan, ―Introduction to Grid Computing‖ CRC Press, 2009.
6. Daniel Minoli, ―A Networking Approach to Grid Computing‖, John Wiley Publication, 2005.
7. Barry Wilkinson, ―Grid Computing: Techniques and Applications‖, Chapman and Hall, CRC,
Taylor and Francis Group, 2010.

@Credits: Syllabus Taken From JNTU 

MANAGEMENT SCIENCE NOTES | MS PDF Download | Student Notes | JNTU

JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY

MANAGEMENT SCIENCE - STUDENT NOTES

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UNIT –I: Introduction to Management: 

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UNIT- II: Operations Management: 

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UNIT –III: Human Resource Management (HRM):

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UNIT –IV: Strategic Management:

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UNIT-V: Contemporary Management Practices:

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MANAGEMENT SCIENCE SYLLABUS

UNIT –I: Introduction to Management: Concept-Nature and Importance of Management, Functions-Evaluation of Scientific Management, Modern management- Motivation Theories-Leadership Styles-Decision Making Process-Designing Organization Structure-Principles and Types of Organization.

UNIT- II: Operations Management: Plant location and Layout, Methods of production, Work-Study-Statistical Quality Control through Control Charts, Objectives of Inventory Management, Need for Inventory Control-EOQ&ABC Analysis(Simple Problems).

Marketing Management: Meaning, Nature, Functions of Marketing, Marketing Mix, Channels of distribution- Advertisement and sales promotion-Marketing strategies-Product Life Cycle.

UNIT -III: Human Resource Management (HRM): Significant and Basic functions of HRM-Human Resource Planning(HRP), Job evaluation, Recruitment and Selection, Placement and Induction-Wage and Salary administration. Employee Training and development-Methods-Performance Appraisal-Employee Grievances-techniques of handling Grievances.

UNIT –IV: Strategic Management: Vision, Mission, Goals and Strategy- Corporate Planning Process-Environmental Scanning-SWOT analysis-Different Steps in Strategy Formulation, Implementation and Evaluation. 

Project Management: Network Analysis- PERT, CPM, Identifying Critical Path-Probability-Project Cost Analysis, Project Crashing (Simple Problems).

UNIT-V: Contemporary Management Practices: Basic concepts of MIS-Materials Requirement Planning(MRP), Just-In-Time(JIT)System, Total Quality Management(TQM)-Six Sigma and Capability Maturity Models(CMM) evies, Supply Chain Management, Enterprise Resource Planning(ERP), Performance Management, Business Process Outsourcing(BPO), Business Process Re-Engineering and Bench Marking, Balance Score Card.

TEXT BOOKS:
1. A.R Aryasri: Management Science, TMH, 2013
2. Kumar /Rao/Chalill ‗Introduction to Management Science‘ Cengage, Delhi, 2012.

REFERENCE BOOKS:
1. A.K.Gupta ―Engineering Management‖, S.CHAND, New Delhi, 2016.
2. Stoner, Freeman, Gilbert, Management, Pearson Education, New Delhi, 2012.
3. Kotler Philip & Keller Kevin Lane: Marketing Mangement, PHI,2013.
5. Koontz & Weihrich: Essentials of Management, 6/e, TMH, 2005.
6. Kanishka Bedi, Production and Operations Management, Oxford University Press,
2004.
7. Memoria & S.V.Gauker, Personnel Management, Himalaya, 25/e, 2005
8. Parnell: Strategic Management, Biztantra, 2003.
9. L.S.Srinath: PERT/CPM, Affiliated East-West Press, 2005.

@Credits: Syllabus Taken From JNTU