Kanth Mentorship Show
"Kanth Mentorship Podcast" is a podcast series hosted by Rajeev Kanth that focuses on career transition and development, particularly in Data Analytics, Data Science, Machine Learning, Data Engineering, Cloud Computing, AWS, Azure, DataBricks, SQL, Power BI, Tableau, Python Generative AI, Deep Learning, Computer Vision, LLMs, and Artificial Intelligence. The podcast covers various topics, including interview preparation, industry insights, and career path guidance, aimed at various individuals, including students, working professionals, and those re-entering the workforce.
Kanth provides personalized guidance for career transitions, discussing suitable pathways based on individual backgrounds and challenges. The focus is on the strategic enhancement of resumes and interview preparation, especially for jobs in India, the USA, the UK, Canada, and the UAE.
For more details and to listen to the podcast episodes, you can visit their pages on Apple Podcasts and Spotify.
Connect with Host: www.instagram.com/meet_kanth/
Kanth Mentorship Show
What is Data Science? based on MNC's
Data science is the study of data and it involves the developing methods of recording, storing, and analyzing data to effectively extract the useful information. Being a Data Scientist is one of the hottest and trending career option of decade. The demand for data scientist is huge,the number is said to be much bigger than the available candidates. Data Scientist help companies interpret and manage data and solve complex problems using expertise in a variety of data niches.
They generally have a foundation in computer science,modeling,statistics,analytics and math coupled with strong business sense.In large companies a data scientist works on the same problem for several months or even years. He/she only need to concentrate on the modelling of the data, and the mathematics or the statistics involved that goes into the model, because the employees of other are working on the certain specified jobs needed like engineering the data ingest, storage and production deployment. Fresher on the other hand, make the data scientist’s work uncertain and they work on multiple problems which can be of different domains at the same time.
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