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Distributed ML with Apache Spark Mini Bootcamp

Distributed ML with Apache Spark Mini Bootcamp

  • About

    Whether you’re training machine learning algorithms or performing a complex Analysis of data using statistical techniques the Quality and Quantity of your data determines the performance of your ML Model.

    Today, organizations have a difficult time working with huge amount of datasets such as IoT, Click Stream, Mobile and Sensor Data etc.., In addition, big data processing and analyzing needs to be done in real time to gain valuable insights quickly. This is where Distributed Machine Learning comes in.

    Understanding how to extract, process and analyze such huge amount of data will only become an ever more important skill for any data analyst / data scientist.


    This training course is for you because…

    • You are an aspiring or beginning data scientist/engineer.
    • You have a comfortable intermediate-level knowledge of Python/Java/Scala and a very basic familiarity with statistics and linear algebra.
    • You are a working programmer or student who is motivated to expand your skills to include machine learning and BigData.
    • You have some familiarity with the fundamentals of machine learning or have taken the Beginning Machine Learning.

    Prerequisites

    • A first course in Python and/or working experience as a programmer
    • College level basic mathematics
    • Recommended: Attend or view Beginning Machine Learning
  • Curriculum
    • Fundamentals of Apache Spark and Machine Learning
    • Analyzing massive amounts of data using Spark SQL
    • Learning different Data Quality and Data Cleaning techniques
    • Learning how to implement Spark ML pipelines
    • Hands on experience with some Kaggle Projects
  • Schedule
    • Start learning the Distributed Machine Learning with Apache Spark with outside of business hours schedule!
    • The 12 hours of schedule is as follows:
    • April 12 – 19 – 26 and May 3
    • Sundays, from 9:00 am to 12:00 pm
  • Location

    The venue for the bootcamp is Magnimind Academy Sunnyvale Campus: 830 Stewart Dr #182, Sunnyvale, CA 94085. The capacity is limited to 20 people.

  • Online

    Distributed ML with Apache Spark Mini Bootcamp is now also available online. Anyone who wants to attend this mini bootcamp can join online live webinars where the same course content will be taught. Online sessions will be distributed through zoom conferences. Students will have access to the screen of the instructor, external camera showing class atmosphere, whiteboard, and be able to ask questions through chat. You may attend this mini bootcamp no matter where you are.

  • Tuition
    Tuition fee

    Distributed Machine Learning with Apache Spark Mini Bootcamp has a $300 tuition fee.

    For the “Early Bird” applicants (January 15 – April 5), the tuition fee is $250.

    Payment process

    After you finish filling your application form, the website will direct you to the payment page. There, you can select available payment options.

    Cancellation

    If you’re not satisfied with the course you may cancel your application.

  • Application

    The application process starts at magnimindacademy.com. You can view the course pages and learn more about your intended course. You can apply by clicking the “Buy now” button and then fill out the application form.

  • Instructor

    Mr. Mudasser Shaik is highly motivated Principal BigData Engineer in industry. He has been sharing his passion for Data for nearly a decade now. He is passionate about Distributed Machine Learning and the intersection of Big Data & Data Science (AI/ML/DL).

    He possesses extensive working experience in designing and building Distributed Pipelines, Streaming Analytics, Scalable Machine learning Models and solving Data Quality Issues. He presently works as Senior Big Data Engineer at Ultimate Software, where he is responsible for developing, maintaining and evaluating Big data solutions for Data Science Teams

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Comments / 2

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