SPE Online Education
Data Science Projects: A Roadmap to Success
Recorded On: 02/19/2021
Data science projects exhibit many challenges that drive most of these projects into failure. Data scientists should equip themselves with different techniques: coding, business skills, data handling skills in order to deliver a successful project. As it is reported, data scientists spend 80% of their time on cleaning and preparing data. Thus, a high focus should be devoted to this step in order to be done the right way. Since data science project lifecycle is composed of several phases, we are going to explore these phases in detail to ensure a correct implementation and successful delivery of the project. Although a lot of material are given addressing this area, this webinar will cover the industrial experiences and the practical implementations of data preparation step. Without putting these phases into context, citizen data scientists might overlook some of these crucial steps. Thus the webinar is providing a roadmap that highlights all of these steps from implementation perspectives. The presenter will share different lessons, issues and mistakes that practitioners sometimes make.
This webinar is categorized under the Data Science and Engineering Analytics technical discipline.
All content contained within this webinar is copyrighted by Dr. Abdulrahman Baqais and its use and/or reproduction outside the portal requires express permission from Dr. Abdulrahman Baqais.
For more information on this topic, please check out the SPE suggested reading links below. Here you will find topic-related books, publications, and papers for purchase in the SPE Bookstore.
Dr. Abdulrahman Baqais
Lead Data Scientist at a large telecom company
Dr. Abdulrahman is working as a lead data scientist at a large telecom company. He has worked in different industrial sectors including: O&G, Retail and Telecom. He also published several papers about utilizing different Artificial Intelligence algorithms and delivered end-to-end machine learning projects in industry addressing wide spectrum of problems including: Image recognition, NLP, recommendation and anomaly detection, and classification. He was the Lead instructor of data science intensive course at General Assembly. Dr. Abdulrahman has delivered a number of seminars and online trainings on different topics related to data science given his combined knowledge of theory and industrial implementation.
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