Data Science Bootcamp XIV: Learning How to Fuse Big Data with Complex Algorithms with Malik Usmah Haleem

big data bootcamp diary
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Week 7 – Journey of Learning How to Fuse Big Data with Complex Algorithms – Data Science Bootcamp XIV

 

“Once upon a time, computers were created with a singular purpose; churn through large data sets to assist with solving data analysis queries. Today, with drastically faster processing speeds and the twin powers of Data Science and Machine Learning, computers are becoming our advisors.”

By fusing data with microprocessors, I have worked at the cutting edge of physics and innovated technology solutions that to most people are pure science fiction and then transformed business performance to make these technology solutions available to international governments when it matters the most.

Why, then, am I not satisfied?

My past successes, no matter how remarkable, have been based on identifying a proverbial needle in a haystack of information. The proliferation of information through the digital revolution has disrupted data science; I must now fuse big data with complex algorithms. My future successes will depend on unconventional machine learning models that solve wicked problems.

big data

To avoid the pitfalls associated with processing big data, I must evolve my analytical skills and embrace the prowess of data science and need do it now to remain at the forefront of technology innovation/delivery.

In IE’s prestigious global multidisciplinary environment, I discovered the Data Science Boot Camp; an ensemble of world class entrepreneurial data scientists symphonising R & Python programming languages with machine learning that teach students how to process big data, build algorithms, analyse results and deliver transformational business solutions.

After six weeks of swimming through sql, dplyr, tidyr, data.table, lubridate, numpy, pandas, os, ggplot, seaborn, bokeh, wordcloud, statistical models, hypothesis testing…etc., the focus of the course shifts to building models in week seven. Despite the concepts of Machine Learning being alien to me, the building blocks that have been embedded over the previous weeks now enable me to carry out regression, classification, KNN, decision trees…etc.

big data

The volume of theoretical information that we absorb on a daily basis is immense and is solidified through numerous tutorials that strengthen our practical programming skills. In parallel we tackle a real industry big data query, where we put into practice all that we learn on the course and gain customer insights from master classes with key industry data science players.

The dynamic format of IE Universities Data Science Diploma and exponential pace has provided me with the continual simulation in which I thrive and endowed me with the essential analytical tools to understand the ever changing landscape of data science and the practical expertise to operate within it.

“The goal of computers is to empower people by complementing their abilities. I am learning to build machine learning models that go beyond executing tasks; this will provide insights that empower transformational decision-making. It’s an exciting time to be alive!”

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