Which is the best course in Azure?

Azure is a cloud service platform by Microsoft, which offers services in various domains such as compute, storage, database, networking, developer tools and other functionality which help businesses to scale and grow.

Azure services are also broadly categorized as the platform as a service (PaaS), software as a service (SaaS) and Infrastructure as a service (IaaS). This can be used by developers and software employees to create, deploy and manage services and applications through the cloud and emerges as one of the biggest commercial cloud service providers.

There are several cloud computing technologies in the market. You will come across an overwhelming number of cloud service providers, hybrid solutions, products, services, features and more. There are two public cloud behemoths that have captured a majority of the market - Microsoft Azure and Amazon AWS. So, if you are planning to grow your career in public cloud computing, you need to choose between these two providers. Making a choice between these two providers is not an easy job! Both of these companies are leaders in their own rights, so none has an unprecedented edge over the other. It is important to understand both these technologies in detail, take into consideration multiple factors before making a decision. Both Amazon AWS and Microsoft Azure offer similar capabilities revolving around storage, security, and networking.

It’s the best time for you to move your career in cloud computing and I would suggest you take a look at Technogeeks Cloud Computing programs by working with IT professionals.

What should I learn, AI or blockchain?

Artificial Intelligence is the science and engineering of making computer machines able to perform tasks which normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

The ultimate effort is to make a computer programs that can solve problems and achieve goals in the world, as well as humans.

There is a scope in developing the machines in game playing, speech recognition machine, language detection machine, computer vision, expert systems, robotics and many more.

70% of the companies in the world believe that they need to adopt Artificial Intelligence, in some way or another, to remain competitive by 2020. While most of them have already started using Artificial Intelligence to automate most of their work-force. The use of Artificial Intelligence has helped companies in being more productive in less time.

The biggest challenge corporates across the globe are facing is the lack of Artificial Intelligence professionals. The rate at which the field of Artificial Intelligence is growing the demand for Artificial Intelligence professionals are growing at the same rate or even faster.

Blockchain has given rise to a new field of development called blockchain development. Blockchain development involves developing and optimizing blockchain protocols and crafting the architecture of blockchain systems. A blockchain developer is responsible for creating integrated smart contracts and web applications using blockchain technology. The two types of blockchain developers are:

·        Core Blockchain Developers: They develop and design the architecture and protocols of a blockchain system and design consensus protocols and high-level development decisions related to blockchain.

·        Blockchain Software Developers: They use the protocols and architecture designed by core blockchain developers to build decentralized applications.

As Blockchain technology continues to evolve, so will its professional opportunities. The Blockchain is here with us to stay which means that Blockchain Expertise is to be in high demand for years and years to come. So, whether you are a techie or not, a career in Blockchain is a new and exciting opportunity worth exploring.

The combination of AI and blockchain holds many exciting potential applications. It’s worth remembering, though, that these technologies are still very young. Most of these hybrid applications will take years to develop or may not even develop at all. They’re certainly powerful ideas, but researchers and developers should take great care when working on such projects. The ethical implications of both blockchain and AI are massive, and the stakes are high for the economy, governance, and society as a whole.

If you are looking to learn these technologies then I would recommend you to enrol in Technogeeks training program under a working IT professional.

What is The Hot Research Topics in Data Science?

 The hot research topics in data science: -

Artificial Intelligence:

AI has become the mainstream technology for both small and large businesses, and it will bloom in the next few years. At present, we are at the initial stage of using artificial intelligence, but in 2021, we will see more advanced applications of AI in all fields. The reason AI is growing rapidly is that it allows enterprises to improve their overall business processes, and provides a better way of handling both customer and client’s data.

Though utilizing AI will still remain a challenge for many, as exploring the advancement of this technology is not that simple. In 2021, we will find more advanced apps developed with AI, Machine learning, and other technologies that can improve the way we work. Another trend that will take over the market is automated machine learning that will be helpful in transforming data science with better data management. So, you might need specialized training for executing deep learning.

Natural Language Processing:

Natural Language Processing (NLP) has made its way firmly into Data Science after huge breakthroughs in Deep Learning research.

Data Science first began as an analysis of purely raw numbers since this was the easiest way to handle it and collect it in spreadsheets. If you needed to process any kind of text, it would usually need to be categorized or somehow converted into numbers.

Yet it’s quite challenging to compress a paragraph of text into a single number. Natural language and text contain so much rich data and information - we used to be missing out on it since we lacked the ability to represent that information as numbers.

Huge advancements in NLP through Deep Learning are fuelling the full-on integration of NLP into our regular Data Analysis. Neural Networks can now extract information from large bodies of text incredibly quickly. They’re able to classify text into different categories, determine sentiment about a text, and perform analysis on the similarity of text data. In the end, all of that information can be stored in a single feature vector of numbers.

As a result, NLP becomes a powerful tool in Data Science. Huge datastores of text, not just one-word answers but full-on paragraphs, can be transformed into numerical data for standard analysis. We’re now able to explore datasets that are far more complex.

Data Science has become one of the growing fields in all industries, especially the IT industry. Thus, businesses adopting data science techniques and technologies must stay up-to-date with the latest trends. If you are looking to learn data science and want to work on data science trends then I would recommend you to take a look in Technogeeks Data Science program by working IT professionals.