360DigiTMG Data Science Course in Malaysia

What is data science & why we need it?

Data science deals with the procurement & processing of meaningful data & patterns extracted from a large collection of data belonging to an enterprise, which helps in generating knowledge of business value.

The need for data science arose with the growth of big data & its challenges. In traditional systems, data is structured & easy for enterprises to analyze using BI (Business Intelligence) tools. But as the amount of data collected by an organization grows in size, the data largely remain unstructured & BI tools are not sufficient anymore to process the data. That’s where Data Science comes into the picture. We use more efficient tools of Data Science such as Weka, BigML, R & RapidMiner to process data. Learn Data Science Course Malaysia

Some common areas where data science is employed are:

1. Search engines like Google, DuckDuckGo etc. make use of Data science algorithms to search & display results related to our queries.
2. Speech recognition technologies such as Cortana, Siri, Amazon’s Alexa employ data science in which voices are picked up by a microphone, transcribed into text & respective actions are taken by the machine.
3. Self-driving cars, drones & autopilot mode in aircrafts.
4. In social media forums to gather information like detecting the devices you use to access your accounts, whom you interact with & the location from where your account has been accessed.
5. Spam filters used by e-mail services.
6. Prediction of diseases in medicine field & gathering information on heart rate, stress levels & blood glucose in humans through wearables such as Fitbit.

 

What you will be learning in Data Science training

1. Data acquisition
2. Predictive analytics
3. Machine Learning algorithms
4. Data Mining, Data Structures & data manipulation
5. Big Data & Hadoop integration with R
6. Data scientist roles & responsibilities

 

Prerequisites for learning data science Course

Data Science has learners from diverse educational backgrounds, and all that is needed to understand the concepts well are, a good command over mathematical & statistical concepts such as algebra, calculus & probability.

 

Technologies used in Data Science

Some common data science technologies, tools & languages used are:

• Python, R, Java TensorFlow and SQL.
• Spark/MLib, Amazon Machine Learning, Hadoop.
• Amazon Web Services, Julia, Google Cloud Compute.

 

Career opportunities in data science

There’s a big demand for data scientists & it is going to further surge in near future. There are 4 kinds of data science roles:

1. Data Analyst:

A data analyst retrieves & gathers data, organizes it and uses it to arrive at important & meaningful conclusions.

 

1. Data Engineer:

A data engineer is an infrastructure engineer who builds, controls and maintains software infrastructure. A data engineer has good knowledge of distributed systems.

 

1. Machine Learning engineer:

A machine learning engineer builds, optimizes & deploys machine learning models. These models are treated as components or APIs and plugged into hardwares & apps.

 

1. Data science generalist:

A generalist does everything starting from retrieval of data, processing it to the final analysis.

But it takes many years of experience to get hired as a data science generalist.

 

Data science is the need of the hour & finds its use in every major field. According to IBM predictions, the demand for Data Scientists will surge to 28% by 2020. Learning data science may not be a walk in the park, but it definitely is thrilling & challenging. So here’s your chance to master the art! Join data science course in and become expert.