Event Details
Data Scientist Offline Sessions in Hyderabad
A data scientist is a master at transforming intricate datasets into powerful insights that propel business success. Utilizing advanced analytics, statistical techniques, and machine learning, they adeptly manage vast amounts of data to address complex business challenges, develop predictive models, and inform strategic decisions. Success in this dynamic field demands not only technical expertise but also a deep domain understanding to convert raw data into meaningful, actionable intelligence.
DataMites stands out by offering exceptional educational programs for aspiring data scientists. Their comprehensive curriculum covers essential areas such as machine learning, data analysis, and big data technologies, with a strong emphasis on practical, hands-on learning through real-world projects. This approach equips learners with the vital skills and knowledge necessary to excel in today’s competitive data science arena.
For Hyderabad Location: https://maps.app.goo.gl/drBT7Px5snuKyM4u9
For the course link: https://datamites.com/data-science-course-training-hyderabad/
For the website link: https://datamites.com/
DataMites stands out by offering exceptional educational programs for aspiring data scientists. Their comprehensive curriculum covers essential areas such as machine learning, data analysis, and big data technologies, with a strong emphasis on practical, hands-on learning through real-world projects. This approach equips learners with the vital skills and knowledge necessary to excel in today’s competitive data science arena.
For Hyderabad Location: https://maps.app.goo.gl/drBT7Px5snuKyM4u9
For the course link: https://datamites.com/data-science-course-training-hyderabad/
For the website link: https://datamites.com/
Entry Fees
Free Registration
Categories
Event Frequency
One Time
Event Timings
(GMT+5:30) Mumbai, Kolkata, New Delhi
10:00 AM - 06:00 PM (Oct 19, Oct 20, Oct 21, Oct 22, Oct 23, Oct 24, Oct 25, Oct 26, Oct 27, Oct 28, Oct 29, Oct 30, Oct 31, Nov 01, Nov 02, Nov 03, Nov 04, Nov 05, Nov 06, Nov 07, Nov 08, Nov 09, Nov 10, Nov 11, Nov 12, Nov 13, Nov 14, Nov 15, Nov 16, Nov 17, Nov 18, Nov 19, Nov 20, Nov 21, Nov 22, Nov 23, Nov 24, Nov 25, Nov 26, Nov 27, Nov 28, Nov 29, Nov 30, Dec 01, Dec 02, Dec 03, Dec 04, Dec 05, Dec 06, Dec 07, Dec 08, Dec 09, Dec 10, Dec 11, Dec 12, Dec 13, Dec 14, Dec 15, Dec 16, Dec 17, Dec 18, Dec 19, Dec 20, Dec 21, Dec 22, Dec 23, Dec 24, Dec 25, Dec 26, Dec 27, Dec 28, Dec 29, Dec 30, Dec 31, Jan 01, Jan 02, Jan 03, Jan 04, Jan 05, Jan 06, Jan 07, Jan 08, Jan 09, Jan 10, Jan 11, Jan 12, Jan 13, Jan 14, Jan 15) (Public)
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