9 Common Mistakes Data Scientists Must Avoid

Here is the list of 9 mistakes data scientists must avoid in their data science projects and get better results by overcoming these common mistakes. https://www.dasca.org/world-of-big-data/article/9-common-mistakes-data-scientists-must-avoid

The Simple 5-Step Process for Creating a Winning Data Pipeline
Data pipelines are the heart and soul of data science. Are you a beginner looking to understand data pipelines? A glimpse into what they are and how they work. https://www.dasca.org/world-of-big-data/article/the-simple-5-step-process-for-creating-a-winning-data-pipeline

What Is More Beneficial for Data Science Career: Projects or Certifications?

Whether you are a data science professional in demand for a role or seeking one out, you must be wondering what is best for your career- data science projects or certifications. Find out here : https://albertchristopherr.medium.com/what-is-more-beneficial-for-data-science-career-projects-or-certifications-d29c1675cc07

Businesses today require a unified & modern approach to data. Data Engineers & Data Scientists should work together to meet data challenges
https://www.facebook.com/DataScienceCouncil/videos/3242101942671075

5 Topmost Programming Languages used by AI Engineers

AI Engineers make use of programming languages to find solutions. Some of the crucial languages are Python, Java, R, Prolog and Lisp. https://www.artiba.org/blog/5-topmost-programming-languages-used-by-ai-engineers-in-2021