Understanding the Pre-requisites for a Career in Data Science. Data science is an emerging field in Tech IT. To seek a career in this, LinkedIn data suggests a data scientist must be proficient in Python, R and have sound knowledge in machine learning.
The interdisciplinary field of data science is growing with extraordinary relevance and so do data scientists. At the same time, the world is generating more data than ever before, supported by inexpensive and endless cloud computing resources available to process that data. Since data is the new currency, companies focus on extracting value from the data pool that will help them boost business and adapt to the changing technologies in the market. For this, they need to hire the right people with reliable data science skills. Data scientists are generally believed to have profound knowledge and expertise in fields like machine learning, statistics, mathematics, computing science, data visualization, and communication. Besides, it is justified to possess such technical skills as a data scientist is one of the highest paying jobs in the Tech community. Along with these, a data scientist must have the ability to solve business problems, be agile, carry effective business communication, be a good data storyteller, and a team player.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
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Need a data set to practice with? Data Science Dojo has created an archive of 32 data sets for you to use to practice and improve your skills as a data scientist.
Even though Big data is into main stream of operations as of 2020, there are still potential issues or challenges the researchers.