From the BlogSubscribe Now

Machine Learning and Data Science Project Management from an Agile Perspective

Access to new resource related to Agility and Agile Project Management added to PMWL



Resource provided by Balzhan Khamitova

31 August 2022 – Almaty, Kazakhstan – Access to a new resource has been added to the PM World Library (PMWL) related to Agility and Agile Project Management. The new resource titled “Machine Learning and Data Science Project Management from an Agile Perspective: Methods and Challenges by Murat Pasa Uysal and is chapter 5 in the book titled “Contemporary Challenges for Agile Project Management.”

In the modern world, when organizations introduce new technologies such as machine learning, data analysis, etc., this opens up new opportunities for organizations, allows them to implement various innovative business models, etc.

However, studies show that such organizations are at high risk of failure. One of the main factors for these failures is the adoption, adaptation of the project management method to the specific requirements of the joint use of ML and DA. In this regard, the author of this work suggests using Agile Project Management (APM) as a solution. This study can be seen as an initial attempt to broaden these areas of knowledge and practice from an APM perspective.

To begin with, the author gives a background on the concepts of Data Science and Machine Learning, where he describes in detail the problem, the data analysis process, how he obtains this data, how he builds models and the results themselves.  He also describes the machine learning process, that is, describes the stages of ML, how the model trains, describes 3 different methods of models / algorithms, how to properly monitor data, and what results as output. Further, the author gives an explanation of the Agile method, what it consists of and on what principles it is based.

In conclusion, the author gives his recommendations on how to use the Agile method in certain conditions, in this case, introducing ML and Data Science into the work. The author suggests using a hybrid method to customize APM according to the needs of the organization or the requirements of the DS and ML project.

To access this new resource, go to the Advanced / Hot topics in PPM section of the library at scroll down to and  click on “Agility - Agile Decision Making and Management”, scroll down to resource. Must be a registered  member and logged-in to access. If not yet registered, please consider the FREE 30-day Trial Membership.

This new resource provided through the PMWL university research internship program; to learn more, click here