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Top 16 Data Science Job Roles To Pursue in 2024

Knowledge Hut

According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. Thus, almost every organization has access to large volumes of rich data and needs “experts” who can generate insights from this rich data.

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What is the Future Scope of Computer Science?

Knowledge Hut

With the growth of cloud computing, data analysis, & automation, computer scientists are developing solutions that help organizations perform at their best. Computer science offer career opportunities like software engineering, cybersecurity, and data analysis which are in high demand and offer great opportunities for growth.

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A List of Machine Learning Libraries

U-Next

Because they may utilize the functionalities of the Machine Learning libraries knowing how the methods are implemented, this helps programmers save a huge amount of time, making their lives simpler. The American Deep Learning and Machine Learning Markets are expected to be worth $80 million by 2025. TensorFlow.

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Data Science Learning Path [Beginners Roadmap]

Knowledge Hut

In 2018, the world produced 33 Zettabytes (ZB) of data, which is equivalent to 33 trillion Gigabytes (GB). In 2020, this number grew to 59 ZB and was expected to reach a whopping 175 ZB in 2025. Can you imagine the data that big? How can companies leverage the data that they have to solve problems or innovate with current ideas?

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Machine Learning Career Track, Learning Path & Roadmap

ProjectPro

These statistics show that it's a perfect time to pursue a career in machine learning and artificial intelligence. Get Closer To Your Dream of Becoming a Data Scientist with 150+ Solved End-to-End ML Projects How much does an ML Engineer earn? Deep learning and computer vision-related careers may demand higher degrees.

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Cyber Security vs Data Science: Key Difference & Similarities

Knowledge Hut

To combat these dirty challenges thrown by hackers, the field of data science has emerged as a powerful player in the battleground against cybercrimes. Once this knowledge is applied, the data is cleaned and organized using techniques such as data analysis, feature engineering, and machine learning to make it usable and reliable.

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Machine Learning in Insurance: Applications, Use Cases, and Projects

ProjectPro

Significant automation capabilities- McKinsey expects automation to influence 25% of the insurance sector by 2025. 15 Applications of Machine Learning in Insurance For insurance companies to manage their data and analytics, they must implement emerging technologies like ML.