Top Trending 8 Technologies To Learn In 2020 | Trending Technologies

1. Artificial Intelligence

Artificial Intelligence Training – Explore the Curriculum to Master AI.

Artificial intelligence (AI) has received increased attention in recent years. Innovation, made possible through the Internet, has brought AI closer to our everyday lives. These advances, alongside interest in the technology’s potential socio-economic and ethical impacts, bring AI to the forefront of many contemporary debates. Industry investments in AI are rapidly increasing, and governments are trying to understand what the technology could mean for their citizens.

The collection of “Big Data” and the expansion of the Internet of Things (IoT), has made a perfect environment for new AI applications and services to grow. Applications based on AI are already visible in healthcare diagnostics, targeted treatment, transportation, public safety, service robots, education, and entertainment, but will be applied in more fields in the coming years. Together with the Internet, AI changes the way we experience the world and has the potential to be a new engine for economic growth.

Current Uses of AI:

Although artificial intelligence evokes thoughts of science fiction, artificial intelligence already has many uses today, for example:

Email filtering: Email services use artificial intelligence to filter incoming emails. Users can train their spam filters by marking emails as “spam”.

Personalization: Online services use artificial intelligence to personalize your experience. Services, like Amazon or Netflix, “learn” from your previous purchases and the purchases of other users in order to recommend relevant content for you.

Fraud detection: Banks use artificial intelligence to determine if there is a strange activity on your account. Unexpected activity, such as foreign transactions, could be flagged by the algorithm.

Speech recognition: Applications use artificial intelligence to optimize speech recognition functions. Examples include intelligent personal assistants, e.g. Amazon’s “Alexa” or Apple’s “Siri”.

The Internet Society recognizes that understanding the opportunities and challenges associated with AI is critical to developing an Internet that people trust. This is particularly important as the Internet is key for the technology behind AI and is the main platform for its deployment; including significant new means of interacting with the network. This policy paper offers a look at the key things to think about when it comes to AI, including a set of guiding principles and recommendations to help make sound policy decisions. Of particular focus is machine learning, a specific approach to AI and the driving force behind recent developments.

Artificial Intelligence Training – Explore the Curriculum to Master AI and Deep Learning.

2. Virtual Reality and Augmented Reality

Virtual Reality (VR) immerses the user in an environment while Augment Reality (AR) enhances their environment. Although VR has primarily been used for gaming thus far, it has also been used for training. The popular Pokemon Go is an example of AR.

Both VR and AR help in training, entertainment, education, marketing, and even rehabilitation after an injury. Either could be used to train doctors to do surgery.

Now a days most of computer are able to support VR. There are major players in the VR market, like Google, Sony, and Oculus, there are lots of demand for professionals with VR and AR skills. Getting started in VR doesn’t require a lot of specialized knowledge. Basic programming skills required to start your career. 

3. Cybersecurity

Cybersecurity very essential as all work are going on internet from phone bills to huge transaction of company.

Cybersecurity might not seem like emerging technology, given that it has been around for a while, but it is evolving just as other technologies are. That’s in part because threats are constantly new. The malevolent hackers who are trying to illegally access data are not going to give up any time soon, and they will continue to find ways to get through even the toughest security measures. It’s also in part because new technology is being adapted to enhance security. As long as we have hackers, we will have cyber security as an emerging technology because it will constantly evolve to defend against those hackers.

Numbers of jobs are creating day by day in Cybersecurity. 

4. Machine Learning

Machine Learning is a subset of AI. With Machine Learning, computers are programmed to learn to do something they are not programmed to do: they learn by discovering patterns and insights from data. In general, we have two types of learning, supervised and unsupervised.

While Machine Learning is a subset of AI, we also have subsets within the domain of Machine Learning, including neural networks, natural language processing (NLP), and deep learning. Each of these subsets offers an opportunity for specializing in a career field that will only grow.

Machine Learning is rapidly being deployed in all kinds of industries, creating a huge demand for skilled professionals. The Machine Learning market is expected to grow more than $9 billion by 2022. Machine Learning applications are used for data analytics, data mining, and pattern recognition. On the consumer end, Machine Learning powers web search results, real-time ads, and network intrusion detection, to name only a few of the many tasks it can do.

Machine Learning  demand jobs include engineers, developers, researchers, and data scientists.

5.Blockchain

Blockchain Training – Explore the Curriculum to Master Blockchain.

The blockchain is not just the technology behind the Bitcoin cryptocurrency; it also has the potential to revolutionize many areas of our everyday lives. But there is still a long way to go.

The blockchain is the leading digital assets platform which records and controls the monetary information. It is basically an endless data chain. Like a booking system, it captures and stores any and all activity in the system, whether money transfers, land registry entries or concluded contracts.

This is a short report that looks at the potential in research and education of blockchain, the technology that underpins the Bitcoin virtual currency.

The blockchain is currently at the peak of the hype cycle, so I spend a little time looking at how we can identify what’s realistic and avoid inflated expectations.

Blockchain’s Bitcoin origins

The early history of Bitcoin is worth reflecting on:

2007: “Satoshi Nakamoto” allegedly begins development of the Bitcoin virtual currency

2009: Version 0.1 of Bitcoin is released on SourceForge, and the first transaction takes place

2010: Programmer buys pizza for 10,000BTC (now worth $39,454,600!)

2011: Silk Road “dark web” marketplace opens

2011: 25% of the 21 million possible Bitcoins now generated through mining operations

Let’s unpack this a little. Bitcoins are generated from thin air by computers solving complex mathematical puzzles - a process known as “mining” - and there are a finite number of them. Not only this, but the puzzles get more complicated as more Bitcoins are mined.

Blockchain Training – Explore the Curriculum to Master Blockchain.

6.Cloud

Cloud Computing – Explore the Curriculum to Master Cloud Computing.

Simply put, cloud computing is the delivery of computing services—servers, storage, databases, networking, software, analytics and more—over the Internet (“the cloud”). Companies offering these computing services are called cloud providers and typically charge for cloud computing services based on usage, similar to how you are billed for water or electricity at home.

Still foggy on how cloud computing Services works and what it is for? This beginner’s guide is designed to demystify basic cloud computing jargon and concepts and quickly bring you up to speed.

AWS Training Explore the Curriculum to Master Blockchain.

7. Devops

Devops Training – Explore the Curriculum to Master Devops.

DevOps is a word that is used to describe a set of modern IT practices which seek to more closely bring together software developers and operations staff to work on the same project in a more collaborative manner. The desire is that by breaking down barriers which have traditionally existed between these two sides of the IT department, organizations can reduce the time and friction involved in deploying new versions of software. This effort will ideally lead to shorter development cycles which ideally may save time and money, and give the organization a competitive edge against others with longer, more traditional development cycles.

Why pursue a DevOps strategy?

Rapid innovation is no longer optional. No matter what industry your organization operates in, it is almost certainly an industry that is seeing upheaval of traditional business practices due to the move towards a software-defined economy. From transportation to manufacturing, mining to farming, finance to healthcare: big data, cloud computing, mobile applications, and a slew of other technology are making software the key differentiator between those businesses and organizations that get ahead and those that fall behind.

Even if your organization wasn't competing in the software market a decade ago, today it is, and the way to get ahead is to bring better solutions forward fasters.

How do I get started?

The first steps into DevOps are about examining your culture and practices, identifying the barriers to cross-team communication and coordination, and taking the steps necessary to bridge communication between your development and operations teams. Achieving this is a challenge, but you don't have to get there overnight. Begin by taking a look at your current methodologies and ask yourself what's not working, and where the opportunities for better cross-pollination may exist.

While DevOps is in many ways about organizational culture, identifying the right software tools is an important step as well. Is your organization using for source control and revisioning tools like Git to help you manage code? Are you adopting continuous integration and build tools to make the movement from source to testing as seamless as possible? What about tools for automating the testing and packaging of their software, or for deployment and security testing? Are you looking at ways to manage your infrastructure like code with configuration management tools, to easily scale and replicate environments? And what about monitoring tools to keep an eye on the whole process from development to production?

DevOps benefits from finding the right tools to keep your development and operations teams working together and moving faster.

Where can I learn more?

Opensource.com has published a number of articles on DevOps; check out our tag set or some of our more popular articles below.

What's the point of DevOps?: A brief history of DevOps demonstrates the need to think differently about collaborative IT work.

3 steps to secure, open source DevOps:

The key to secure app development is to "shift left"—move security testing away from late-stage production and back towards design and development.

Top 5 programming languages for DevOps: We round up five of the top programming languages for DevOps and a few handy learning resources for each.

A developer's journey through DevOps: The days of siloed development and operations teams is over.

Secured DevOps for micro services: Containers and micro services have revolutionized application development and infrastructure management.

DevOps Training – Explore the Curriculum to Master DevOps tools.

8. IoT

Internet of Things (IoT)

IOT Training – Explore the Curriculum to Master IoT.

This includes everything from network-based cameras, digital video recorders, to digital personal assistants. These devices can be categorized for commercial use like biometric door looks to home use like Bluetooth door lock keypads and thermostats. While these types of devices have existed for years, they have only recently been grouped and labeled IoT based on their mass adoption and, more importantly, their mass identification of security risks and privileged attack vectors. Therefore, as IoT devices become more commonplace, there is a need to ensure that they do not represent an unnecessary security risk to standard business operations. Unfortunately, it has already been proven that many of these devices are insecure by design, have unresolvable flaws, and can be leveraged to compromise an entire organization with something as simple as a default credential.

lot Training – Explore the Curriculum to Master DevOps tools.

Intelligent Apps (I – Apps)

I-Apps are pieces of software written for mobile devices based on artificial intelligence and machine learning technology, aimed at making everyday tasks easier.

This involves tasks like organizing and prioritizing emails, scheduling meetings, logging interactions, content, etc. Some familiar examples of I-Apps are Chatbots and virtual assistants.

As these applications become more popular, they will come with promise of jobs and fat paychecks.