Month: February 2021

Are you the one who is trying to build a futuristic career in a tech world? Then, this is for you. Walk across the promising 3 reasons why you should switch a career to AI.

#1 Work anywhere across the planet

Ever wondered why AI is portrayed as a game changer and driving force of the revolution named Industry 4.0? The reason is that AI has infiltrated the major industries in the planet and transformed the way they work.

Here’s the list of industries deploying AI to enhance their growth rate:

1. Design & Manufacturing

2. Education

3. E-commerce

4. Entertainment

5. Healthcare

6. Information Technology

7. Logistics

8. Marketing

#2 Career opportunities in AI

Here comes the common misconception that artificial intelligence will solely destroy the human workforce. On contrary to this point, AI has opened up a gateway of career opportunities  and will continue to do so in the near future.

Some of the trending and most-wanted job roles offered by AI companies are:

1. Data Analyst

2. Data Scientist

3. Machine Learning Engineer

4. Software Engineer

5. AI Researcher

Read more on Data Analyst vs Data Scientist vs Machine Learning Engineer.

#3 Paid handsomely

Once after the Harvard Business Review called the AI jobs as sexiest job of the century, the career craze for the same went viral among the techies. Organizations started to pay in a handsome fashion for the people with sound AI knowledge.

According to payscale, below is the list of salary ranges for diverse AI job roles:

Job Role	Average annual pay scale in India	Average annual pay scale in US
AI Researcher	₹ 15,60,217	$1,24,098
Data Scientist	₹ 7,12,778	$ 96,289
Machine Learning Engineer	₹ 6,82,843	$1,12,552
Software Engineer	₹ 5,39,889	$103,501
Data Analyst	₹ 4,30,076	$ 75,067

Dreaming to build a career in an AI industry?

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What’s Adaptive Learning?

In layman’s terms, adaptive learning is an educational approach towards providing unique and personalized learning experience to diverse set of learners.
Here’s a popular opinion from global researchers and educationists:

“Study skills varies from one individual to the other. Hence a standardized learning approach to all people seems undesirable”

In order to eradicate such major problem in the educational sector, adaptive learning technology emerged as a great solution.

How does adaptive learning work?

Adaptive learning works with multiple algorithms.
Let’s consider a simple scenario where a student has to answer 10 MCQs. Once the candidate completes the test, the results gets displayed in the dashboard.

From the above dashboard, it can be seen that the student has got 7 correct answers and 3 wrong answers. Now one of the background algorithm prompts the student to have a revision on the topics that went wrong, thereby aiding the learner to gain complete understanding of the subject.

Companies like iamneo.ai have been proven successful by deploying adaptive learning technology to enhance the learning experience in a customized manner.

Adaptive Learning in L&D of Corporates

Yes, adaptive learning has already breached the department of learning and development in the corporate firms. The organizations have started to use the LMS software equipped with adaptive learning technology to provide training to their employees.

Tech-companies like Hexaware, Virtusa, Trimble Technologies are using the adaptive learning powered software offered by iamneo.ai (Formerly Examly) to host training programs for their employees.

Data Analyst

The Data Analyst is the one who plays the game with the large sets of data (aka) Big Data! The everyday lives of data analysts revolve around analysing an enormous amount of data available in various forms.

Data Analysts are responsible for providing relevant insights out of the interpreted data which in turn aids the organization in decision-making and solve complex business problems.

Data Scientist

All data scientists are data analysts but not all data analysts are data scientists.

From the above quote, it is evident that data scientist stands a level up in certain cases. This is due to the fact that in addition to the data analysis, the data scientists perform the programming part. They create the data model with the help of data given by the data analysts.

Data scientists work on top algorithms such as regression, clustering, visualization, K-NN, statistics, time series etc.

Machine Learning Engineer

When the data model created by the data scientists needs to be deployed as a product, the machine learning engineer enters the crease.
Machine learning engineers create the software product (website applications, mobile applications etc ) out of the given data model.

The life of a machine learning engineer can be synchronized to that of a data scientists as their roles overlaps depending upon the organization.

List of Data Science Tools:

A wide range of tools are used in data science industry for various purposes such as statistical analysis, modelling and visualization.

Some of the most widely used data science tools are:

• MySQL
• Tableau
• Microsoft Excel
• Apache Spark
• RStudio
• BigML
• SAS