Webinar on Data Science and Machine Learning in E-Mobility. ISIEINDIA | Data science,ai,artificial intelligence

Data Science and A.I Application in E-Mobility - AIT

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The future of energy storage lies in data. According to Aryan (Akhil Aryan, Co-Founder and CEO, ION Energy), Electric vehicle and energy storage space providers are increasingly understanding the importance of battery data to optimise their fleet, deploy faster, improve up time and to improve the life of the batteries, making a tremendous impact on the business. “We believe that technology alone cannot solve problems, it needs to be developed keeping in mind the domain and the business. By applying battery domain knowledge to technologies like data analytics, simulations, and machine learning, we can accelerate the transition of businesses to an all-electric future,” he asserts.

Data science, AI and IoT are revolutionising the EV space and are paving the way for an all-electric future in the next 5-10 years. “These technologies are making sense of battery data to derive valuable insights, that can determine and considerably improve the battery life. That would reduce the overall ownership cost and the planet’s dependence on fossil fuels,” states Aryan.

Trainer's Profile:

Mr. Aditya Kaki

Technical lead at ZF India Technical Center

Machine Learning and Deep Learning certification from IIIT Hyderabad, M.tech in Software and Systems in Bits Pilani

Provided training on MATLAB Simulink, MATLAB Stateflow, M scripting, Vector Cast tools, Automotive protocols, Python, Data science, Machine learning, Deep learning and Embedded etc, on corporate level. Delivered workshop in Machine learning, Deep learning and Data sciences in prestigious colleges NIIT Manglore, IIT Hyderabad, IIT Madras, IIT Bombay.  

Note: Kindly do not download certificate before update of duration in lesson. It is 00:00 now. It will be updated after completion of webinar. 

Program outcomes
  • Determining the terms Artificial Intelligence, Machine Learning, Deep Learning and Data Science

  • Difference between Traditional and Machine learning

  • Classification in Machine learning > Supervised, Unsupervised, Reinforcement and Semi supervised > Regression and Classification > Clustering and Association rules

  • Role of AI in E mobility, Discussing 2 R&D projects which are being worked on

  • Career options opportunists in Data Science and Artificial Intelligence

  • Different roles and responsibilities

  • Mobile/Laptop/Tablet with good internet connectivity


  • 1 Lessons
  • 01:00:00 Hours
  • Webinar01:00:00

About instructor

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Student : 4595 Students
Courses : 105 Courses


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