Free Seminar: Data Science for Non Techies

You need to have a technical background to be a Data Scientist. Said no one ever!

 

 

Mr. Ali Raza Anjum (Co-Founder, Dice Analytics) and Mr. Usman Akram (Data Scientist at S&P Global) aimed to eliminate this misconception in an interactive session carried out by Dice Analytics on 25th February’2020. Professionals from commercial departments & career newbies from Marketing, HR and Finance backgrounds intrigued by Data Science attended the session and had a productive Saturday!

 

 

 

Mr. Ali Raza Anjum initiated the session with the introduction of Dice Analytics and then kicked off the discussion by explaining the impact of Data Science in our lives. He revealed how Machine Learning has created an ease for consumers in every sector whether its Banking, Manufacturing, Health or Telecom. Companies who are deploying Machine Learning in their operations save a lot of time and effort and also provide more value to their customers.

Furthermore, audience got to know about their roles as Data Scientist in their specific industries and how they can make use of the tools & technologies of Data Science.

 

 

 

 

Mr. Usman Akram further supported the discussion by explaining the practices  in non technical departments of S&P which utilize Machine Learning & Data Science and have witnessed relative growth in the processes.

 

 

 

 

The session was concluded with a Q&A session where attendees were given a chance to ask one to one questions and clarify their concepts. The participants were able to network with industry experts and discover career opportunities in the rising domain.

 

 

The key note from the session was that Data Science is for everyone! Whether technical or non technical background, the approach to it might be different but non techies can equally get benefit  from Machine Learning applications. Non Technical individuals learn different tools such as Rapid Miner, SAP Predictive Modeling, Teradata Miner, SAS Enterprise Miner and KNIME to have access to Data Science instead of coding (R or Python), they can explore new dimensions in their work and bring required reforms in their organizations to stay ahead in the game!