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
12 hours, 3 hours per week.
All Zoom lectures are monitored by trained staff.
Instructors from Facebook, Google, Standford University, University of California, Berkeley, and University of Maryland
Students will be awarded different certifications in each batch
Adults
● 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
Price & More Info
To know the price and get more information about the program fill out the form, and we will get in contact with you.
