Topics: AI | Data Science | Data Visualization | Deep Learning | Machine Learning | NLP | Python | R | Statistics

About Benjamin Obi Tayo, Ph.D.

Physicist, Data Science Educator, Writer. Owner, DataScienceHub. Previously, was teaching Engineering and Physics at U. of Central Oklahoma, Grand Canyon U., and Pittsburgh State U.

Benjamin Obi Tayo, Ph.D. Posts (10)

  • Platinum Blog20 Core Data Science Concepts for Beginners - 08 Dec 2020
    With so much to learn and so many advancements to follow in the field of data science, there are a core set of foundational concepts that remain essential. Twenty of these ideas are highlighted here that are key to review when preparing for a job interview or just to refresh your appreciation of the basics.
  • Silver BlogIs Data Science for Me? 14 Self-examination Questions to Consider - 17 Nov 2020
    You are intrigued by this exciting new field of Data Science, and you think you want in on the action. The demand remains very high and the salaries are strong. Before taking the leap onto this path, these questions will help you evaluate if you are ready for the challenges and opportunities.
  • Silver BlogHow to ace the data science coding challenge - 15 Oct 2020
    Preparing to interview for a Data Scientist position takes preparation and practice, and then it could all boil down to a final review of your skills. Based on personal experience, these tips on how to approach such a review will help you excel in the coding challenge project for your next interview.
  • Gold BlogPlatinum BlogData Science Minimum: 10 Essential Skills You Need to Know to Start Doing Data Science - 01 Oct 2020
    Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.
  • 6 Common Mistakes in Data Science and How To Avoid Them - 10 Sep 2020
    As a novice or seasoned Data Scientist, your work depends on the data, which is rarely perfect. Properly handling the typical issues with data quality and completeness is crucial, and we review how to avoid six of these common scenarios.
  • Design of Experiments in Data Science - 03 Sep 2020
    Read this overview of the process of designing experiments for collecting data.
  • Gold BlogThese Data Science Skills will be your Superpower - 20 Aug 2020
    Learning data science means learning the hard skills of statistics, programming, and machine learning. To complete your training, a broader set of soft skills will round out your capabilities as an effective and successful professional Data Scientist.
  • Silver BlogPlatinum BlogData Science MOOCs are too Superficial - 20 Jul 2020
    Most massive open online courses are too superficial because they offer introductory-level courses. For in-depth knowledge, more is needed to increase your knowledge and expertise after establishing a foundation.
  • Gold BlogPlatinum BlogHow Much Math do you need in Data Science? - 26 Jun 2020
    There exist so many great computational tools available for Data Scientists to perform their work. However, mathematical skills are still essential in data science and machine learning because these tools will only be black-boxes for which you will not be able to ask core analytical questions without a theoretical foundation.
  • Data Science Curriculum for self-study - 26 Feb 2020
    Are you asking the question, "how do I become a Data Scientist?" This list recommends the best essential topics to gain an introductory understanding for getting started in the field. After learning these basics, keep in mind that doing real data science projects through internships or competitions is crucial to acquiring the core skills necessary for the job.

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