Event Details
Data Scientist Classroom Training in Hyderabad
A data scientist uses advanced analytics, statistical techniques, and machine learning to derive valuable insights from complex datasets. They handle large volumes of data to address business challenges, develop predictive models, and inform strategic decisions. To excel in this field, a data scientist needs a blend of technical prowess and domain expertise to translate data into actionable intelligence.
DataMites offers specialized courses designed to prepare learners for success in data science. Their programs encompass essential topics like machine learning, data analysis, and big data technologies, with a strong emphasis on hands-on experience through real-world projects. By focusing on practical application, DataMites equips aspiring data scientists with the skills and knowledge necessary to excel in a competitive job market.
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 offers specialized courses designed to prepare learners for success in data science. Their programs encompass essential topics like machine learning, data analysis, and big data technologies, with a strong emphasis on hands-on experience through real-world projects. By focusing on practical application, DataMites equips aspiring data scientists with the skills and knowledge necessary to excel in a competitive job market.
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 (Sep 09, Sep 10, Sep 11, Sep 12, Sep 13, Sep 14, Sep 15, Sep 16, Sep 17, Sep 18, Sep 19, Sep 20, Sep 21, Sep 22, Sep 23, Sep 24, Sep 25, Sep 26, Sep 27, Sep 28, Sep 29, Sep 30, Oct 01, Oct 02, Oct 03, Oct 04, Oct 05, Oct 06, Oct 07, Oct 08, Oct 09, Oct 10, Oct 11, Oct 12, Oct 13, Oct 14, Oct 15, Oct 16, Oct 17, Oct 18, 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) (Public)
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