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Top 5 Data Science Trends in 2021

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Top 5 Data Science Trends in 2021 are: 

  • AI in Data Science
  • Deep Learning in Data Science 
  • ML in Data Science
  • Python, the fastest-growing major programming language
  • Demand for Data Security Professionals

In today’s exponentially growing data-driven world, organizations are going through major transformations. Organizations rely on digital technologies. Data science has become an integral part of the organizations now. The decisions are taken based on the real data-driven facts. The main aim of data science is to integrate the data into the business process.

According to Google Search Trends,

The interest in Data Science has increased significantly in the past 5 years

Google search trends -Data Science

The Top 5 Data Science Trends in 2021 are: 

  • AI in Data Science
  • Machine Learning in Data Science
  • Deep Learning in Data Science 
  • Python, the fastest-growing major programming language
  • Demand for Data Security Professionals

AI in Data Science 

Artificial intelligence in Data Science is used to acquire insights from data through intelligence.  AI is a tool that helps data science get results and solutions for specific problems. Data storing, cleaning, exploring and modeling the data takes a lot of time. Artificial intelligence helps organizations in handling the data and improve the overall business process.  In the future, advanced AI will be applied in all fields. Artificial Intelligence makes the use of algorithms to perform autonomous actions. 

According to McKinsey,

Amazon has achieved impressive results from its $775 million acquisition of Kiva, a robotics company that automates picking and packing.

Netflix has also achieved impressive results from the algorithm it uses to personalize recommendations to its 100 million subscribers worldwide.

Machine Learning in Data Science 

Machine Learning automates the data analytical model building by turning the information to knowledge. With the explosion of data in recent times, it is difficult to bring new predictive models. Machine learning is used to analyze a large number of data. Machine learning develops fast algorithms and data-driven models for real-time processing data.  

The adoption of Machine learning is reaching new heights. 

According to Statista.com,

  • 1/3 of IT leaders are planning to use ML for business analytics. 
  • 25% of IT leaders plan to use ML for security purposes 
  • 16% of IT leaders want to use ML in sales and marketing

Deep Learning in Data Science 

 

Deep learning is a technique of machine learning. ML uses deep learning as the powerhouse between Artificial Intelligence and Data Science. It strengthens the process of AI. The process of deep learning requires a lot of learning and implementation. Google uses deep learning to deliver solutions. The various applications google use deep learning is 

Google Deepmind’s AlphaGo

DeepMind’s WaveNet

Google Translate 

Google PlaNet

According to teks.co.in,

  • The estimated value of the US deep learning software market in 2025 is $935 million
  • The estimated compound annual growth rate of the US deep learning market in 2025 is 42% 

Python, the fastest-growing major programming language 

Python is in a leading position in the language used by data science professionals. It is the de facto language for data science. 

According to Stack Overflow’s annual developer survey

“Python, the fastest-growing major programming language, has risen in the ranks of programming languages in our survey yet again, edging out Java this year and standing as the second most loved language (behind Rust).” 

 

Python is an open-source platform designed to run on Windows and Linux environments. There are python libraries developed for,

  • Data manipulation
  • Data Visualization
  • Statistics
  • Mathematics
  • Machine Learning
  • Natural Language Processing 

Python is considered as the top skill required for data science:

 

Demand for Data Security Professionals 

In any organization, data privacy and data security is very important. The more the data, the more concerned about data theft. Data generation is very high due to IoT.  In order to control data thefts and its impact, the GDPR – General Data Protection Regulation, was passed by states of the European Union in May 2018. It has also been reported that such regulation for data protection shall again be passed by California in 2020.

Due to this, there is a huge demand for Data Security Professionals. 

According to ZDNet,



 

For more information on how iCert Global can help you to achieve your Data Science Certification goals, please visit our Data Science Certification Training Courses on our website.

The Data Scientist certification validates data scientist’s knowledge on SAS, R, Hadoop, Python and Spark and how to use data concepts such as data exploration, visualization hypothesis testing, and predictive analytics. There is a huge demand for Data Scientists in industries like Aerospace industry, IT industry, e-commerce industry, and healthcare industry.

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