How Can Data Scientist Become IoT Experts?

Gartner predicts that the number of total IoT devices will exceed 11.2 billion this year, the most of which are in the consumer sector. The same report predicts that the endpoint spending will surpass $2 trillion, in software and hardware combined.

This huge demand for IoT development is reduced by the lack of experienced developers. The arena is so new that there is no definite curriculum. Those looking to get into this niche generally come from a data science or engineering background. How can this skill gap be closed and what should an IoT developer concentrate on first?

The IoT Developer Skill Set

To handle these differences, it follows that coding knowledge is not sufficient. Successful IoT development needs a wider and more varied set of skills and a flexible attitude.

Data scientists can become experts in the IoT niche by transforming their Big Data analysis skills. They will have to consider the source and occurrence of data. The task is to create systems, containing chips, sensors, and communication gateways that are energy efficient, lightweight, and reliable. Then, connect these with computational machines that can respond instantly.

The real challenge is that being adept in only one area, as a coding language is not sufficient anymore. The next generation of developers will have to be multilingual in more tools and technologies.

Skills that will be in the highest demand for IoT developers:

Machine Learning - this is essential to produce smart applications using data recovered from sensors. The aim is to develop prediction models built on patterns from data.

AutoCAD - this skill is more associated with engineering, but it will be important to develop devices that follow concrete design principles and are customizable.

Node.js - this is an exchangeable skill which can act as a conduit between the old and new programming domains. The environment is considered stable and fit for IoT enabling devices such as Raspberry Pi and Arduino.

Cloud computing and management - this is another important data scientist skill that can be reinterpreted for IoT purposes. A reputed data science consulting company InData Labs highlights that operating with ETL (Extract, Transform, Load) on unstructured data is an obligatory requirement for IoT. This becomes clear when the information flow comprises sound and picture files.

Blockchain knowledge - This decentralized system could aid secure IoT devices via smart contracts. This “truth machine” can decrease the expenses of security for large networks of IoT devices.

Other relevant skills that are not core knowledge for developers but will make a variance in the IoT world comprise UI/ UX skills to make the device as user-friendly as possible, information security protocols to improve vulnerability assessments and mobile development as most devices will be handled through smartphones or tablets.

Data science for IoT course from a top-rated institution can help data scientists learn all the essential skills required to become IoT experts. Quality institutions with their experienced faculty and state-of-the-art resources help students master the fundamentals of the subject-matter.