Twelve Myths about Data Science

سرفصل های دوره

As data science continues to shape industries and societies, myths and misconceptions often abound, leading to misguided expectations and ineffective strategies. In this course, instructor Ben Sullins delves deep into twelve prevalent myths that have persisted over time, shedding light on the truths behind them and equipping you with the knowledge to navigate the data landscape more effectively.

Note: This course was created by Ben Sullins of Free the Data Academy. We are pleased to host this content in our library.

01 - Introduction

01 - Welcome

02 - 1. 12 Myths

01 - AI will solve all our problems effortlessly

02 - Data science projects will always yield immediate ROI

03 - AI and automation will replace human decision-making entirely

04 - Data quality is not as important as quantity

05 - Machine learning models are always objective and unbiased

06 - Data science is solely a technical discipline

07 - Deep learning is the answer to every problem

08 - AI and machine learning will replace jobs, leading to mass unemployment

09 - Anyone can become a data scientist with a short online course

10 - Data science is only relevant for large corporations

11 - Implementing AI is a one-time project, not an ongoing process

12 - More data always leads to better results

03 - Conclusion

01 - Recap

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تولید کننده: LinkedIn Learning (Lynda)