This is a R&D project between Sopra Steria and Université de Lorraine in France. We want to predict project performance using project maturity models and artificial intellifence
Semantic Artificial Intelligence is the fusion of various types of AI, incl. symbolic AI, reasoning, and machine learning techniques like deep learning. At the same time, Semantic AI has a strong focus on data management and data governance. With the 'wedding' of various AI techniques new promises are made, but also fundamental approaches like 'Explainable AI (XAI)', knowledge graphs, or Linked Data are more strongly focused.
Become a complete developer by learning front-end and back-end technologies in this Full Stack Web Developer Course. These are just a few of the 40 different apps that are part of this brilliant course. With this course, you will not only learn a whole lot of different technologies, but also become a complete developer.
So, what are you waiting for? Let’s become a Master Developer with this Full Stack Web Development Bundle Course.
For More Info : https://www.eduonix.com/courses/Web-Development/the-full-stack-web-development?coupon_code=kedu15
Artificial Intelligence, Machine Learning and Deep LearningSujit Pal
Slides for talk Abhishek Sharma and I gave at the Gennovation tech talks (https://gennovationtalks.com/) at Genesis. The talk was part of outreach for the Deep Learning Enthusiasts meetup group at San Francisco. My part of the talk is covered from slides 19-34.
Object classification using CNN & VGG16 Model (Keras and Tensorflow) Lalit Jain
Using CNN with Keras and Tensorflow, we have a deployed a solution which can train any image on the fly. Code uses Google Api to fetch new images, VGG16 model to train the model and is deployed using Python Django framework
How can you deal with Fuzzy Logic. Fuzzy logic is a form of many-valued logic; it deals with reasoning that is approximate rather than fixed and exact. In contrast with traditional logic theory, where binary sets have two-valued logic: true or false, fuzzy logic variables may have a truth value that ranges in degree
between 0 and 1
Semantic Artificial Intelligence is the fusion of various types of AI, incl. symbolic AI, reasoning, and machine learning techniques like deep learning. At the same time, Semantic AI has a strong focus on data management and data governance. With the 'wedding' of various AI techniques new promises are made, but also fundamental approaches like 'Explainable AI (XAI)', knowledge graphs, or Linked Data are more strongly focused.
Become a complete developer by learning front-end and back-end technologies in this Full Stack Web Developer Course. These are just a few of the 40 different apps that are part of this brilliant course. With this course, you will not only learn a whole lot of different technologies, but also become a complete developer.
So, what are you waiting for? Let’s become a Master Developer with this Full Stack Web Development Bundle Course.
For More Info : https://www.eduonix.com/courses/Web-Development/the-full-stack-web-development?coupon_code=kedu15
Artificial Intelligence, Machine Learning and Deep LearningSujit Pal
Slides for talk Abhishek Sharma and I gave at the Gennovation tech talks (https://gennovationtalks.com/) at Genesis. The talk was part of outreach for the Deep Learning Enthusiasts meetup group at San Francisco. My part of the talk is covered from slides 19-34.
Object classification using CNN & VGG16 Model (Keras and Tensorflow) Lalit Jain
Using CNN with Keras and Tensorflow, we have a deployed a solution which can train any image on the fly. Code uses Google Api to fetch new images, VGG16 model to train the model and is deployed using Python Django framework
How can you deal with Fuzzy Logic. Fuzzy logic is a form of many-valued logic; it deals with reasoning that is approximate rather than fixed and exact. In contrast with traditional logic theory, where binary sets have two-valued logic: true or false, fuzzy logic variables may have a truth value that ranges in degree
between 0 and 1
[Video recording available at https://www.youtube.com/playlist?list=PLewjn-vrZ7d3x0M4Uu_57oaJPRXkiS221]
Artificial Intelligence is increasingly playing an integral role in determining our day-to-day experiences. Moreover, with proliferation of AI based solutions in areas such as hiring, lending, criminal justice, healthcare, and education, the resulting personal and professional implications of AI are far-reaching. The dominant role played by AI models in these domains has led to a growing concern regarding potential bias in these models, and a demand for model transparency and interpretability. In addition, model explainability is a prerequisite for building trust and adoption of AI systems in high stakes domains requiring reliability and safety such as healthcare and automated transportation, and critical industrial applications with significant economic implications such as predictive maintenance, exploration of natural resources, and climate change modeling.
As a consequence, AI researchers and practitioners have focused their attention on explainable AI to help them better trust and understand models at scale. The challenges for the research community include (i) defining model explainability, (ii) formulating explainability tasks for understanding model behavior and developing solutions for these tasks, and finally (iii) designing measures for evaluating the performance of models in explainability tasks.
In this tutorial, we present an overview of model interpretability and explainability in AI, key regulations / laws, and techniques / tools for providing explainability as part of AI/ML systems. Then, we focus on the application of explainability techniques in industry, wherein we present practical challenges / guidelines for effectively using explainability techniques and lessons learned from deploying explainable models for several web-scale machine learning and data mining applications. We present case studies across different companies, spanning application domains such as search & recommendation systems, hiring, sales, and lending. Finally, based on our experiences in industry, we identify open problems and research directions for the data mining / machine learning community.
Big data Analytics is a process to extract meaningful insight from big such as hidden patterns, unknown correlations, market trends and customer preferences
The presentation includes the objective, operation, characteristics , simulation, results and waveforms of Doubly Fed Induction Generator connected to variable speed Wind Turbine. which is published and presented in IEEE international conference in Technological advancements of Power and Energy which was held in Amrita Vishwa Vidyapeetam, Amritapuri, Kerala.
This is a deep learning presentation based on Deep Neural Network. It reviews the deep learning concept, related works and specific application areas.It describes a use case scenario of deep learning and highlights the current trends and research issues of deep learning
Machine Learning and its types - Internship Presentation - week 8Devang Garach
Machine Learning and its types - Internship Presentation - week 8
What is AI, ML & DL
What is Machine Learning?
How do Machine Learn?
Types of Machine Learning
Major Machine Learning Techniques
In this deck from the Stanford HPC Conference, Peter Dueben from the European Centre for Medium-Range Weather Forecasts (ECMWF) presents: Machine Learning for Weather Forecasts.
"I will present recent studies that use deep learning to learn the equations of motion of the atmosphere, to emulate model components of weather forecast models and to enhance usability of weather forecasts. I will than talk about the main challenges for the application of deep learning in cutting-edge weather forecasts and suggest approaches to improve usability in the future."
Peter is contributing to the development and optimization of weather and climate models for modern supercomputers. He is focusing on a better understanding of model error and model uncertainty, on the use of reduced numerical precision that is optimised for a given level of model error, on global cloud- resolving simulations with ECMWF's forecast model, and the use of machine learning, and in particular deep learning, to improve the workflow and predictions. Peter has graduated in Physics and wrote his PhD thesis at the Max Planck Institute for Meteorology in Germany. He worked as Postdoc with Tim Palmer at the University of Oxford and has taken up a position as University Research Fellow of the Royal Society at the European Centre for Medium-Range Weather Forecasts (ECMWF) in 2017.
Watch the video: https://youtu.be/ks3fkRj8Iqc
Learn more: https://www.ecmwf.int/
and
http://www.hpcadvisorycouncil.com/events/2020/stanford-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
A presentation about the development of the ideas from the autoencoder to the Stable Diffusion text-to-image model.
Models covered: autoencoder, VAE, VQ-VAE, VQ-GAN, latent diffusion, and stable diffusion.
Federated Learning makes it possible to build machine learning systems without direct access to training data. The data remains in its original location, which helps to ensure privacy, reduces network communication costs, and taps edge device computing resources. The principles of data minimization established by the GDPR, and the growing prevalence of smart sensors make the advantages of federated learning more compelling. Federated learning is a great fit for smartphones, industrial and consumer IoT, healthcare and other privacy-sensitive use cases, and industrial sensor applications.
We’ll present the Fast Forward Labs team’s research on this topic and the accompanying prototype application, “Turbofan Tycoon”: a simplified working example of federated learning applied to a predictive maintenance problem. In this demo scenario, customers of an industrial turbofan manufacturer are not willing to share the details of how their components failed with the manufacturer, but want the manufacturer to provide them with a strategy to maintain the part. Federated learning allows us to satisfy the customer's privacy concerns while providing them with a model that leads to fewer costly failures and less maintenance downtime.
We’ll discuss the advantages and tradeoffs of taking the federated approach. We’ll assess the state of tooling for federated learning, circumstances in which you might want to consider applying it, and the challenges you’d face along the way.
Speaker
Chris Wallace
Data Scientist
Cloudera
A sharing talk in Hsinchu Coders.
The materials (i.e. images) are from their respective owners:
https://research.googleblog.com/2017/04/federated-learning-collaborative.html
A CCP is an experienced practitioner with advanced knowledge and technical expertise to apply the broad principles and best practices of Total Cost Management (TCM) in the planning, execution and management of any organizational project or program. CCPs also demonstrate the ability to research and communicate aspects of TCM principles and practices to all levels of project or program stakeholders, both internally and externally.
[Video recording available at https://www.youtube.com/playlist?list=PLewjn-vrZ7d3x0M4Uu_57oaJPRXkiS221]
Artificial Intelligence is increasingly playing an integral role in determining our day-to-day experiences. Moreover, with proliferation of AI based solutions in areas such as hiring, lending, criminal justice, healthcare, and education, the resulting personal and professional implications of AI are far-reaching. The dominant role played by AI models in these domains has led to a growing concern regarding potential bias in these models, and a demand for model transparency and interpretability. In addition, model explainability is a prerequisite for building trust and adoption of AI systems in high stakes domains requiring reliability and safety such as healthcare and automated transportation, and critical industrial applications with significant economic implications such as predictive maintenance, exploration of natural resources, and climate change modeling.
As a consequence, AI researchers and practitioners have focused their attention on explainable AI to help them better trust and understand models at scale. The challenges for the research community include (i) defining model explainability, (ii) formulating explainability tasks for understanding model behavior and developing solutions for these tasks, and finally (iii) designing measures for evaluating the performance of models in explainability tasks.
In this tutorial, we present an overview of model interpretability and explainability in AI, key regulations / laws, and techniques / tools for providing explainability as part of AI/ML systems. Then, we focus on the application of explainability techniques in industry, wherein we present practical challenges / guidelines for effectively using explainability techniques and lessons learned from deploying explainable models for several web-scale machine learning and data mining applications. We present case studies across different companies, spanning application domains such as search & recommendation systems, hiring, sales, and lending. Finally, based on our experiences in industry, we identify open problems and research directions for the data mining / machine learning community.
Big data Analytics is a process to extract meaningful insight from big such as hidden patterns, unknown correlations, market trends and customer preferences
The presentation includes the objective, operation, characteristics , simulation, results and waveforms of Doubly Fed Induction Generator connected to variable speed Wind Turbine. which is published and presented in IEEE international conference in Technological advancements of Power and Energy which was held in Amrita Vishwa Vidyapeetam, Amritapuri, Kerala.
This is a deep learning presentation based on Deep Neural Network. It reviews the deep learning concept, related works and specific application areas.It describes a use case scenario of deep learning and highlights the current trends and research issues of deep learning
Machine Learning and its types - Internship Presentation - week 8Devang Garach
Machine Learning and its types - Internship Presentation - week 8
What is AI, ML & DL
What is Machine Learning?
How do Machine Learn?
Types of Machine Learning
Major Machine Learning Techniques
In this deck from the Stanford HPC Conference, Peter Dueben from the European Centre for Medium-Range Weather Forecasts (ECMWF) presents: Machine Learning for Weather Forecasts.
"I will present recent studies that use deep learning to learn the equations of motion of the atmosphere, to emulate model components of weather forecast models and to enhance usability of weather forecasts. I will than talk about the main challenges for the application of deep learning in cutting-edge weather forecasts and suggest approaches to improve usability in the future."
Peter is contributing to the development and optimization of weather and climate models for modern supercomputers. He is focusing on a better understanding of model error and model uncertainty, on the use of reduced numerical precision that is optimised for a given level of model error, on global cloud- resolving simulations with ECMWF's forecast model, and the use of machine learning, and in particular deep learning, to improve the workflow and predictions. Peter has graduated in Physics and wrote his PhD thesis at the Max Planck Institute for Meteorology in Germany. He worked as Postdoc with Tim Palmer at the University of Oxford and has taken up a position as University Research Fellow of the Royal Society at the European Centre for Medium-Range Weather Forecasts (ECMWF) in 2017.
Watch the video: https://youtu.be/ks3fkRj8Iqc
Learn more: https://www.ecmwf.int/
and
http://www.hpcadvisorycouncil.com/events/2020/stanford-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
A presentation about the development of the ideas from the autoencoder to the Stable Diffusion text-to-image model.
Models covered: autoencoder, VAE, VQ-VAE, VQ-GAN, latent diffusion, and stable diffusion.
Federated Learning makes it possible to build machine learning systems without direct access to training data. The data remains in its original location, which helps to ensure privacy, reduces network communication costs, and taps edge device computing resources. The principles of data minimization established by the GDPR, and the growing prevalence of smart sensors make the advantages of federated learning more compelling. Federated learning is a great fit for smartphones, industrial and consumer IoT, healthcare and other privacy-sensitive use cases, and industrial sensor applications.
We’ll present the Fast Forward Labs team’s research on this topic and the accompanying prototype application, “Turbofan Tycoon”: a simplified working example of federated learning applied to a predictive maintenance problem. In this demo scenario, customers of an industrial turbofan manufacturer are not willing to share the details of how their components failed with the manufacturer, but want the manufacturer to provide them with a strategy to maintain the part. Federated learning allows us to satisfy the customer's privacy concerns while providing them with a model that leads to fewer costly failures and less maintenance downtime.
We’ll discuss the advantages and tradeoffs of taking the federated approach. We’ll assess the state of tooling for federated learning, circumstances in which you might want to consider applying it, and the challenges you’d face along the way.
Speaker
Chris Wallace
Data Scientist
Cloudera
A sharing talk in Hsinchu Coders.
The materials (i.e. images) are from their respective owners:
https://research.googleblog.com/2017/04/federated-learning-collaborative.html
A CCP is an experienced practitioner with advanced knowledge and technical expertise to apply the broad principles and best practices of Total Cost Management (TCM) in the planning, execution and management of any organizational project or program. CCPs also demonstrate the ability to research and communicate aspects of TCM principles and practices to all levels of project or program stakeholders, both internally and externally.
On 24 July 2009, I was fortunate enough to speak at the BA World conference in Wellington, to talk about Centres of Excellence for business analysis, how aiming for excellence would help us overcome some of our challenges, on what those first steps would look like. This was the first public airing of the early stages of what would evolve to become my practice development approach.
AN HIGH INFLUENCE PMO IN AN AGILE WORLDKenMartin18
An Enterprise PMO (EPMO) is a PMO that is able to operate at the corporate side of the business ensures that projects are aligned with the strategic goals of the organisation. With executive support, enterprise PMOs influence strategy, drive key initiatives, and control changes across the organisation.
Did you know? Over the years, enterprises have achieved 65% of higher project savings by adhering to Six Sigma methodology.
Leadership is a critical element in the success of both implementing and using Six Sigma Techniques and Tool to support process change and delivering value in conducting Six Sigma Projects. Having the role of Leadership defined and the necessary knowledge of the methods that will set the expectation of change within processes can inspire teams to stay focused and deliver timely results.
Areas covered in the webinar
- The WHO in Leadership supporting Six Sigma
- The WHY as it relates to the Business Goals and Objectives
- The EXPECTATION or VISION for change to deliver value
- The INVOLVEMENT and participation of leadership
- The SUPPORT and resources needed
- The AUTHORITY to make change happen
- The RECOGNITION of all who contributed to delivering the value
- The MOMENTUM to build on success and continuous improvement
For more details click here - https://www.invensislearning.com/webinar/leading-the-way-in-six-sigma
#sixsigma #leansixsigma #sixsigmablackbelt #sixsigmayellowbelt #sixsigmagreenbelt #sixsigmamethodlogy #sixsigmaprocess #sixsigmacourse #sixsigmavideo #sixsigmamanagement #leansixsigmamethod #SixSigmaTraining
About Invensis Learning
Invensis Learning is a leading training and professional development solutions provider. We deliver globally-recognized training and certifications to individuals and enterprises to aid key business transformations and help to stay relevant by closing skill gaps and cultivate an environment that fosters continuous learning. We have trained 10000+ professionals over wide portfolio of training and certification courses. We are a trusted partner of many Fortune 500 companies for training and development
For more details please visit: https://www.invensislearning.com/
تواصل_تطوير
المحاضرة رقم 186
دكتور / اشرف حمدان
بمشاركة الاستاذة /سارة سالم
عنوان المحاضرة:
"المنظور الجديد لمدير المشروع من خلال
منهجية المفوضية الأوربية PM²"
يوم الإثنين 19 ديسمبر 2022
الثامنة مساء توقيت القاهرة
التاسعة مساء توقيت مكة المكرمة
و الحضور عبر تطبيق زووم من خلال الرابط
https://us02web.zoom.us/meeting/register/tZMkf--oqDIiGNCeJibDkS_L_a3pPalrlHZo
علما ان هناك بث مباشر للمحاضرة على القنوات الخاصة بجمعية المهندسين المصريين
ونأمل أن نوفق في تقديم ما ينفع المهندس ومهمة الهندسة في عالمنا العربي
والله الموفق
للتواصل مع إدارة المبادرة عبر قناة التليجرام
https://t.me/EEAKSA
ومتابعة المبادرة والبث المباشر عبر نوافذنا المختلفة
رابط اللينكدان والمكتبة الالكترونية
https://www.linkedin.com/company/eeaksa-egyptian-engineers-association/
رابط قناة التويتر
https://twitter.com/eeaksa
رابط قناة الفيسبوك
https://www.facebook.com/EEAKSA
رابط قناة اليوتيوب
https://www.youtube.com/user/EEAchannal
رابط التسجيل العام للمحاضرات
https://forms.gle/vVmw7L187tiATRPw9
ملحوظة : توجد شهادات حضور مجانية لمن يسجل فى رابط التقيم اخر المحاضرة.
Increasing Project Success through Project Management Maturity Based on ISO 2...PECB
The webinar presented has introduced the main project management methodology which project managers use nowadays. The methodology is based on best ISO 21500 practices. In addition, the presenter has provided useful information to the audience, in regards of survey findings and facts which PMs can use in their daily activities.
Main points covered:
• Short introduction of the project management methodology ISO 21500
• PM maturity, PM organizations
• Results of project survey including fact and findings
Presenter:
The webinar was presented by John Roos is project –en program manager on consultancy bases. He has an extended experience in many fields a.o. Business Improvement, ISO 27001/ISO 21500 and Total Quality Management (TQM).
Link of the webinar published on YouTube: https://youtu.be/ziqybFGtJDo
CMI Sydney presentation Building Enterprise Change Capability - Top Global T...Prosci ANZ
In this interactive presentation, Being Human Managing Director Catherine Smithson will highlight the top global trends in the emerging field of Enterprise Change Management, using insights from Prosci’s recently released 2016 Best Practices in Change Management Benchmarking Report.
Similar to Machine Learning applied to Project Management (20)
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
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Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
Water billing management system project report.pdfKamal Acharya
Our project entitled “Water Billing Management System” aims is to generate Water bill with all the charges and penalty. Manual system that is employed is extremely laborious and quite inadequate. It only makes the process more difficult and hard.
The aim of our project is to develop a system that is meant to partially computerize the work performed in the Water Board like generating monthly Water bill, record of consuming unit of water, store record of the customer and previous unpaid record.
We used HTML/PHP as front end and MYSQL as back end for developing our project. HTML is primarily a visual design environment. We can create a android application by designing the form and that make up the user interface. Adding android application code to the form and the objects such as buttons and text boxes on them and adding any required support code in additional modular.
MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software. It is a stable ,reliable and the powerful solution with the advanced features and advantages which are as follows: Data Security.MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software.
2. 89%
36%
97%
<30%
HOW IMPORTANT IS PROJECT MANAGEMENT FOR YOUR
ORGANIZATION ?
High
performance
Low
Performance
All ProjectsOrganisations
Of organizations believe project management is critical to business
performance and organizational success
High-performing organizations complete 89% of their projects
…while low performers
of those projects successfully completed on time and on
budget
But only
[PMI, 2014], [PWC, 2016]
3. YOU ARE NOT THE ONLY ONE HAVING THIS PROBLEMS
130%
500%20%
75%
AVERAGE COST OVERRUN IN
BIG PROJECTS
[Atif Ansa et al. 2017]
4. ONE SOLUTION IN PM LITTERATURE IS BY DEVELOPING
PROJECT MANAGEMENT MATURITY MODELS (PMMM)
Maturity Level 1
Maturity Level 2
Maturity Level 3
Maturity Level 4 & 5
There are not any project
management practice stablish,
the project is first in its type in
the company (ad hoc), it
doesn’t have a defined team or
senior management support.
there are some good practices
in place and there is a small
team engage, also the
organization have done some
similar work before.
The project management
practices are standardize
within the organization, there
is a clear project team that
have informal skill and training
in project management.
There is a team with strength
teamwork and formal training
in project management, they
benchmark best practices and
formally report the
information. .
[PMI, 2008], [CMMI, 2006], [Ibbs et al., 2000], [Crawford, J.K. 2002] , [OGC, 2008]
5. 90% OF THEM ARE UNDER
LEVEL 2
The maturity models have several
problems:
Level 2 Level 3 Level 4 & 5Level 1
22%
6%
68%
4%
100% Can’t make any
prediction of the success of
projects
90% Can’t take account of
strategy problems in the
environment of the company
72% Not created for the
adequate level of complexity of
the project
65% Are too long to apply, they give
best practice but didn’t help the
company to get to the next level
BUT, AFTER THE EVALUATION OF MORE THAN 200
ORGANIZATIONS…
[Grant & Pennypacker. 2016 ]5
7. FOR DEVELOPPING IT, WE START STUDING THE KM OF SOPRA
STERIA CONSULTING:
AREVA
Evaluation of
Maturity in project
management for 20
projects
01
02 04
03 05
Chrous
Evaluation of the
complexity of
projects
Project Health Check
Evaluation of problems to
turnaround of drift projects
PnM
Tool created to
evaluate Project
Management
Maturity
Tender M4
Tool created to evaluate Bid
management maturity
8. WE PROPOSE THIS CLASSIFICATION OF PROJECTS IN
ORDER TO ANALYSE THEIR MATURITY LEVEL:
2
4
1
ComplexityLevel
Strategic Value
Complexity
Strategic
Agile
Complicate
Leverage
Complex
Projects’ classificationComplex
Projects
2
3
1Complicate
Projects
Agile
Projects
3
Leverage
Projects
4
10. Practices
Practices
Practices
Criterion
Practices
Practices
Practices
Maturity
Level 5
Maturity
Level 4
Maturity
Level 3
Maturity
Level 2
Maturity
Level 1
Dimension
Criterion
Practices
Practices
Practices
Criterion
Practices
Practices
Practices
Dimension
Criterion
CriterionCriterionCriterionCriterion
ML Algorithm
Performance
EfficiencyEfficacity
FINALLY, CONVERGING THE BLACK BOX MODEL INTO A WHITE BOX
MODEL (USING MACHINE LEARNING) TO PREDICT PERFORMANCE:
RETEX
KM
Interviews
11. PLANNING
FOR THE NEXT 3 YEARS
State of the art
PM, AI, ML Criteria,
interviews
01
Model development
Bayes Networks, Quantitative data02
Test of the model:
EOI, Sopra Steria, Customers03
Publications
Articles, sustentation04
S1 2017 S2 2017 S1 2018 S2 2018 S1 2019 S2 2019
Editor's Notes
Maturité et performance de la gestion projet appliqué à la TD
=> Learning Maturity
https://www.weforum.org/agenda/2017/03/learning-about-creativity-from-formula-1?utm_content=buffer364ce&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer
When was the last time you lead or participle in a project?
97% of organizations believe project management is critical to business performance and organizational success (Source: PWC)
PMI organization affirm that $122 million was wasted for every $1 billion invested in the United States, due to poor project performance.
Fewer than a third of all projects were successfully completed on time and on budget over the past year. (Source: Standish Group)
18. High-performing organizations successfully complete 89% of their projects, while low performers complete only 36%. (Source: PMI.org)
Project Management Maturity: An Assessment of Project Management Capabilities Among and Between Selected Industries
Kevin P. Grant and James S. Pennypacker