This document provides information about a project management paper solution from Mumbai University for the B.Sc. IT program. It includes the university details, course information, author information, and the paper itself which contains 7 sections with multiple choice questions covering various aspects of project management like the project life cycle, cost estimation, quality parameters, workflows, and more.
Overview of CAD/CAM: Product cycle, CAD, CAM and CIM. CAD Tools, CAM Tools,
Utilization in an Industrial Environment, Evaluation criteria. CAD standards, CAD data
structure, Data base management systems.
Computer Graphics: Co-ordinate systems, Graphics package functions, 2D and 3D
transformations, homogeneous transformations, clipping, hidden line / surface removal
colour, shading.
Computer Aided Processes Planning: Retrieval type and Generative type, benefits
A new model for software costestimationijfcstjournal
Accurate and realistic estimation is always considered to be a great challenge in software industry.
Software Cost Estimation (SCE) is the standard application used to manage software projects. Determining
the amount of estimation in the initial stages of the project depends on planning other activities of the
project. In fact, the estimation is confronted with a number of uncertainties and barriers’, yet assessing the
previous projects is essential to solve this problem. Several models have been developed for the analysis of
software projects. But the classical reference method is the COCOMO model, there are other methods
which are also applied such as Function Point (FP), Line of Code(LOC); meanwhile, the expert`s opinions
matter in this regard. In recent years, the growth and the combination of meta-heuristic algorithms with
high accuracy have brought about a great achievement in software engineering. Meta-heuristic algorithms
which can analyze data from multiple dimensions and identify the optimum solution between them are
analytical tools for the analysis of data. In this paper, we have used the Harmony Search (HS)algorithm for
SCE. The proposed model which is a collection of 60 standard projects from Dataset NASA60 has been
assessed.The experimental results show that HS algorithm is a good way for determining the weight
similarity measures factors of software effort, and reducing the error of MRE.
EFFICIENCY OF SOFTWARE DEVELOPMENT AFTER IMPROVEMENTS IN REQUIREMENTS ENGINEE...ijseajournal
In the past decade multiple challenges arose from the method of software development [4, 4]. As described by Davenport, the development process needs an overhaul [4, 4]. Different disciplines, like project management, requirements engineering, the development of code or quality assurance have been investigated intensively, in order to improve the productivity of development. To obtain valid results, the
overhaul needs to start with the refactoring of the right process at first. Often, it is sensible to start with such processes, which operate at the interface to the customer, because they are perhaps the most critical to an organization’s success [3, 270 – 271]. Mainly, software development consists of four sub processes:
requirements engineering, development, quality assurance and delivery. Requirements engineering and
delivery operate on the interface to the customers. Because of the fact that the analysis of requirements is
groundbreaking, we select this process as the starting point of a process innovation initiative. We analyse
the impact of requirements engineering in KANBAN development processes. Special emphasis is put on the
productivity of the overall development process, after a refactoring of requirements engineering.
Overview of CAD/CAM: Product cycle, CAD, CAM and CIM. CAD Tools, CAM Tools,
Utilization in an Industrial Environment, Evaluation criteria. CAD standards, CAD data
structure, Data base management systems.
Computer Graphics: Co-ordinate systems, Graphics package functions, 2D and 3D
transformations, homogeneous transformations, clipping, hidden line / surface removal
colour, shading.
Computer Aided Processes Planning: Retrieval type and Generative type, benefits
A new model for software costestimationijfcstjournal
Accurate and realistic estimation is always considered to be a great challenge in software industry.
Software Cost Estimation (SCE) is the standard application used to manage software projects. Determining
the amount of estimation in the initial stages of the project depends on planning other activities of the
project. In fact, the estimation is confronted with a number of uncertainties and barriers’, yet assessing the
previous projects is essential to solve this problem. Several models have been developed for the analysis of
software projects. But the classical reference method is the COCOMO model, there are other methods
which are also applied such as Function Point (FP), Line of Code(LOC); meanwhile, the expert`s opinions
matter in this regard. In recent years, the growth and the combination of meta-heuristic algorithms with
high accuracy have brought about a great achievement in software engineering. Meta-heuristic algorithms
which can analyze data from multiple dimensions and identify the optimum solution between them are
analytical tools for the analysis of data. In this paper, we have used the Harmony Search (HS)algorithm for
SCE. The proposed model which is a collection of 60 standard projects from Dataset NASA60 has been
assessed.The experimental results show that HS algorithm is a good way for determining the weight
similarity measures factors of software effort, and reducing the error of MRE.
EFFICIENCY OF SOFTWARE DEVELOPMENT AFTER IMPROVEMENTS IN REQUIREMENTS ENGINEE...ijseajournal
In the past decade multiple challenges arose from the method of software development [4, 4]. As described by Davenport, the development process needs an overhaul [4, 4]. Different disciplines, like project management, requirements engineering, the development of code or quality assurance have been investigated intensively, in order to improve the productivity of development. To obtain valid results, the
overhaul needs to start with the refactoring of the right process at first. Often, it is sensible to start with such processes, which operate at the interface to the customer, because they are perhaps the most critical to an organization’s success [3, 270 – 271]. Mainly, software development consists of four sub processes:
requirements engineering, development, quality assurance and delivery. Requirements engineering and
delivery operate on the interface to the customers. Because of the fact that the analysis of requirements is
groundbreaking, we select this process as the starting point of a process innovation initiative. We analyse
the impact of requirements engineering in KANBAN development processes. Special emphasis is put on the
productivity of the overall development process, after a refactoring of requirements engineering.
Project Management (April – 2016) [Question Paper | CBSGS: 75:25 Pattern]Mumbai B.Sc.IT Study
Project Management (April – 2016) [Question Paper | CBSGS: 75:25 Pattern]
april - 2017, april - 2016, april - 2015, april - 2014, april - 2013, october - 2017, october - 2016, october - 2015, october - 2014, may - 2016, may - 2017, december - 2017, 75:25 pattern, 60:40 pattern, revised course, old course, mumbai bscit study, mumbai university, bscit semester vi, bscit question paper, old question paper, previous year question paper, semester vi question paper, question paper, CBSGS, IDOL, kamal t, internet technology, digital signals and systems, data warehousing, ipr and cyber laws, project management, geographic information system
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
Productionalizing Machine Learning Models: The Good, The Bad and The UglyIrina Kukuyeva, Ph.D.
Data science teams tend to put a lot of thought into developing a predictive model to address a business need, tackling data processing, model development, training, and validation. After validation, the model then tends to get rolled out -- without much testing -- into production. While software engineering best practices have been around for a long time until recently, no formal guidelines existed for checking the quality of code of a machine learning pipeline.
The talk will cover tips and best practices for writing more robust production-ready predictive model pipelines. We know that code is never perfect; Irina will also share the pains and lessons learned from experience productionalizing and maintaining 4 customer-facing models at 4 different companies: in online advertising, consulting, finance, and fashion.
Om0017 advanced production and planning controlsmumbahelp
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
help.mbaassignments@gmail.com
or
call us at : 08263069601
Software Engineering
We Also Provide SYNOPSIS AND PROJECT.
Contact www.kimsharma.co.in for best and lowest cost solution or
Email: amitymbaassignment@gmail.com
Call: 9971223030
QFD (Quality Function Deployment) introduction,
Concept of QFD, History of QFD, Traditional systems & Development of QFD, Technical story as for QFD, Scope of QFD, Benefits of QFD, where does QFD fits, when to use QFD, House of quality (HOQ) model in QFD, relationship matrix of QFD, QFD overview, References, Conclusion
Project Management (October – 2016) [Question Paper | CBSGS: 75:25 Pattern]Mumbai B.Sc.IT Study
Project Management (October – 2016) [Question Paper | CBSGS: 75:25 Pattern]
april - 2017, april - 2016, april - 2015, april - 2014, april - 2013, october - 2017, october - 2016, october - 2015, october - 2014, may - 2016, may - 2017, december - 2017, 75:25 pattern, 60:40 pattern, revised course, old course, mumbai bscit study, mumbai university, bscit semester vi, bscit question paper, old question paper, previous year question paper, semester vi question paper, question paper, CBSGS, IDOL, kamal t, internet technology, digital signals and systems, data warehousing, ipr and cyber laws, project management, geographic information system
Project Management (April – 2016) [Question Paper | CBSGS: 75:25 Pattern]Mumbai B.Sc.IT Study
Project Management (April – 2016) [Question Paper | CBSGS: 75:25 Pattern]
april - 2017, april - 2016, april - 2015, april - 2014, april - 2013, october - 2017, october - 2016, october - 2015, october - 2014, may - 2016, may - 2017, december - 2017, 75:25 pattern, 60:40 pattern, revised course, old course, mumbai bscit study, mumbai university, bscit semester vi, bscit question paper, old question paper, previous year question paper, semester vi question paper, question paper, CBSGS, IDOL, kamal t, internet technology, digital signals and systems, data warehousing, ipr and cyber laws, project management, geographic information system
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
Productionalizing Machine Learning Models: The Good, The Bad and The UglyIrina Kukuyeva, Ph.D.
Data science teams tend to put a lot of thought into developing a predictive model to address a business need, tackling data processing, model development, training, and validation. After validation, the model then tends to get rolled out -- without much testing -- into production. While software engineering best practices have been around for a long time until recently, no formal guidelines existed for checking the quality of code of a machine learning pipeline.
The talk will cover tips and best practices for writing more robust production-ready predictive model pipelines. We know that code is never perfect; Irina will also share the pains and lessons learned from experience productionalizing and maintaining 4 customer-facing models at 4 different companies: in online advertising, consulting, finance, and fashion.
Om0017 advanced production and planning controlsmumbahelp
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
help.mbaassignments@gmail.com
or
call us at : 08263069601
Software Engineering
We Also Provide SYNOPSIS AND PROJECT.
Contact www.kimsharma.co.in for best and lowest cost solution or
Email: amitymbaassignment@gmail.com
Call: 9971223030
QFD (Quality Function Deployment) introduction,
Concept of QFD, History of QFD, Traditional systems & Development of QFD, Technical story as for QFD, Scope of QFD, Benefits of QFD, where does QFD fits, when to use QFD, House of quality (HOQ) model in QFD, relationship matrix of QFD, QFD overview, References, Conclusion
Project Management (October – 2016) [Question Paper | CBSGS: 75:25 Pattern]Mumbai B.Sc.IT Study
Project Management (October – 2016) [Question Paper | CBSGS: 75:25 Pattern]
april - 2017, april - 2016, april - 2015, april - 2014, april - 2013, october - 2017, october - 2016, october - 2015, october - 2014, may - 2016, may - 2017, december - 2017, 75:25 pattern, 60:40 pattern, revised course, old course, mumbai bscit study, mumbai university, bscit semester vi, bscit question paper, old question paper, previous year question paper, semester vi question paper, question paper, CBSGS, IDOL, kamal t, internet technology, digital signals and systems, data warehousing, ipr and cyber laws, project management, geographic information system
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1. BOOK CODE: TYBSCIT-PM-004
APRIL – 2019
Mumbai University
B.Sc.IT (Information Technology)
CBSGS: Semester – VI
YEAR: OCTOBER – 2015
PROJECT
MANAGEMENT
By
Kamal Thakur