About Us

This website and its entire tutorial content is regulated and managed by the author: Dr. Bonaventure Chidube Molokwu.

The fundamental objective of the web content(s) herein is to simplify as well as synergize the concepts of programming and the science of computing. Our strategy essentially focuses on harnessing several vital learning outcomes in addition to their respective teaching/learning concepts, and with the ultimate goal of fostering Active Learning and Experiential Learning for students in the domain of Computer Science and Software Engineering.

Generally, the content-delivery approach we have employed herein tackles each teaching/learning concept via a 4-point strategy as outlined below, viz:
  1. Introduction: A icebreaker that is targeted at motivating the reader and/or learner in active preparation for the core content.
  2. Core Content: This encapsulates the participatory-learning activities and practicals targeted at delivering the teaching/learning concept.
  3. Conclusion: The summary of the teaching and/or learning session.
  4. Exercise: A take-home post-assessment activity which is aimed at reinforcing Active Learning and Experiential Learning among students.

Furthermore, the author holds B.Sc., M.Sc., and Ph.D. degrees in the field of Computer Science. Consecutively, the author is a Certified Internet Professional – Web Development (BCIP), Certified PHP 5 Programmer, Certified C++ Programmer, Certified HTML 4.0 Programmer, and Certified JavaScript-JQuery Programmer. Additionally, the author does possess a University Teaching Certificate (UTC) in Teaching and Learning.

Moreover, the author has actively been involved in classroom teaching activities, which entail large-class and small-class sizes, both at undergraduate (bachelor's) and graduate (master's) levels. Also, the author is an active academic researcher within the domain of Artificial Intelligence (AI) with respect to Social Network Analysis (SNA). This academic research entails harnessing Machine Learning (ML) and Deep Learning (DL) methodologies toward resolving a range of open (research) problems and real-world problems in SNA.

"Learning is a treasure that will follow its owner everywhere."

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