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Aspiring data scientists, statisticians, mathematicians, econometricians, and practicing data analysts, analytics managers, business analysts will benefit from this community communications, activities, training for Diploma in Data Sciences and Technology, and meetups.

Get the vistas of data sciences, be in the network of people who are data scientists and thought leaders, and become the leader that you want to be.

Get trained in core data sciences subjects and get the job you would love to do.

Upcoming events (5)

Advanced Data Sciences - Neo4J - Graph Database and Cypher SQL

Data Science foundations have roots in Statistical, Mathematical, and Computational Topics. Often you have to think differently as data science is mostly about unstructured data, a fair statement and data that are coming not in a designed way! It is a joy to spend time with you all who aspire to commit or are committed to the nucleus of data science...Statistical-Mathematical-Computational foundations... ==============Get the password one day before from================ One day before the meeting day, get your password from https://www.Instituteofanalytics.com/meetup ==============Join the meeting using the following================== Join me with the link https://global.gotomeeting.com/join/758565061 =================================================================== In this weekly series, I will bring out how to think differently and hence expose how simplicity in the vast topics in the congruence of these topics can be the power that will encourage to learn a vast amount of topics in data science I may select examples and properties of various statistical, mathematical, and computational (SMC) constructs from books or published articles but interpretations and simplicity are the purposes, I will adhere to ... We in data science are biased towards in prioritizing the uncertainty in observations as the lead to bring together other tools and constructs such as mathematics and computational methods. We will not forget the importance of automation of algorithms...

Big Data Engineering - Streaming Data from Twitter using PySpark, Zepplin

This is a continuation of working with scala, python, and R applications in one zeppelin notebook in Cloud Environment. As a start, we will use AWS. Zeppelin notebooks are ideal to move data across multiple data science programming paradigms and use the right programming paradigm for the right purposes. We will introduce the full life cycle of reading data in scala, summarizing in python, visualizing in R, and going back to scala or python for ML. Data Scientists have to use Spark, the great open-source platform for big data for all its data-wrangling - It is 100 times faster than Hadoop and scala is 10 times faster than Python. So for direct data wrangling with big data, use Scala. They also have to use Python the easier programming language of choice for data analysis after it sizes down leveraging all the packages that make analysis easier, and R, the statistician's choice of programming that also has powerful visualization, for anything else or as a substitution for Python. On top of these, we would love to use easy to use interactive visualization notebook. ZEPPELIN Notebook is your answer. Get your password using the link: https://www.instituteofanalytics.com/meetup Join at 9 AM EST, 6 AM PST, 6:30 PM IST, our regular GoToMeeting meetup https://global.gotomeeting.com/join/758565061

Think Different Meetup...Statistical, Mathematical, and Computational Topics...

Data Science foundations have roots in Statistical, Mathematical, and Computational Topics. Often you have to think differently as data science is mostly about unstructured data, a fair statement and data that are coming not in a designed way! It is a joy to spend time with you all who aspire to commit or are committed to the nucleus of data science...Statistical-Mathematical-Computational foundations... ==============Get the password one day before from================ One day before the meeting day, get your password from https://www.Instituteofanalytics.com/meetup ==============Join the meeting using the following================== Join me with the link https://global.gotomeeting.com/join/758565061 =================================================================== In this weekly series, I will bring out how to think differently and hence expose how simplicity in the vast topics in the congruence of these topics can be the power that will encourage to learn a vast amount of topics in data science I may select examples and properties of various statistical, mathematical, and computational (SMC) constructs from books or published articles but interpretations and simplicity are the purposes, I will adhere to ... We in data science are biased towards in prioritizing the uncertainty in observations as the lead to bring together other tools and constructs such as mathematics and computational methods. We will not forget the importance of automation of algorithms...

Think Different Meetup...Statistical, Mathematical, and Computational Topics...

Data Science foundations have roots in Statistical, Mathematical, and Computational Topics. Often you have to think differently as data science is mostly about unstructured data, a fair statement and data that are coming not in a designed way! It is a joy to spend time with you all who aspire to commit or are committed to the nucleus of data science...Statistical-Mathematical-Computational foundations... ==============Get the password one day before from================ One day before the meeting day, get your password from https://www.Instituteofanalytics.com/meetup ==============Join the meeting using the following================== Join me with the link https://global.gotomeeting.com/join/758565061 =================================================================== In this weekly series, I will bring out how to think differently and hence expose how simplicity in the vast topics in the congruence of these topics can be the power that will encourage to learn a vast amount of topics in data science I may select examples and properties of various statistical, mathematical, and computational (SMC) constructs from books or published articles but interpretations and simplicity are the purposes, I will adhere to ... We in data science are biased towards in prioritizing the uncertainty in observations as the lead to bring together other tools and constructs such as mathematics and computational methods. We will not forget the importance of automation of algorithms...

Photos (13)