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Online Orientation Session on

How to Start a Career in Data Science

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  • About the Webinar

    Duration

    60 mins

    Day

    March 18, 2020

    Time

    3:00 pm

    Who is the Speaker?

    Vaibhav Verdhan is a Data Science, Machine Learning, and Artificial Intel professional. He has in-depth experience of leading multiple engagements in Data Science, Machine Learning space, and Analytics Consulting. He is a hands-on technical expert with the acuity to assimilate and analyze data, drawing meaningful insights leading to strategic planning and decision making.

    His skill set includes Python, R, SPSS, SAS EG, Clustering, Market-Basket, SPADE, Regression, Decision Tree, Random Forest, SVM, Time Series, NLP, Text Mining, Neural Network, Deep Learning, TensorFlow, Keras, SQL, MS Excel, MS PowerPoint, Tableau, and COGNOS. His areas of expertise include Data Science, Machine Learning, Artificial Intelligence, Deep Learning, Customer & Marketing Analytics, Customer Life Cycle Management, Sentiment Analysis, Pricing, Text/Image Analysis, Business Consulting and Strategy, Project Management, and Team Mentoring.

    He is a leader with global client exposure across the UK, Ireland, UAE, KSA, India, and South Africa. He is well-known for his work in retail, telecom, manufacturing, insurance, and energy utility domain.

    Vaibhav Verdhan

    Key Takeaways
    • Do not enter Data Science just for the sake of it. Enter if you really enjoy analysis and solving unknown problems.
    • Skills matter tools do not. Regression is the same in Python, R, SAS, Weka, Julia.
    • Fail, learn and repeat. Make new mistakes and do not repeat the old ones.
    • Network, network, network, network.
    • Your learning never stops. It is an unending process.

    Session Agenda

    Data is the new oil. It is shaping our world and opening doors to different career paths. What are the steps for making a career in Data Science? Join us to understand the skills that matter in the long run and how tools are the means to an end.

    Who Should Attend?



    Students

    Computer Science Graduates

    Aspiring Machine Learning Engineers



    CTO’s

    Aspiring Data Analysts

    Aspiring Data Scientists

    Software Engineers