Technology is never in a state of limbo, it is always evolving. The skills that were in demand last year become old as soon as the new year arrives. Employers expect candidates to possess the technical skills that are in trend. The technology sector is highly competitive. There are thousands of candidates vying for a few lucrative jobs. We all know that change is the only constant. Regardless of your profession and designation, you must adapt to the constant changes taking place at your workplace. You must learn new job skills throughout your work life to keep up with workplace changes, grow your career, and boost career opportunities.
So, here is the list of the top 8 technical skills you need to learn as soon as possible because they are going to rule in 2023. The list goes as follows:
Table of Contents
1. Artificial Intelligence:
Artificial intelligence (AI) is a broad field of computer science involved in building intelligent machines that can perform tasks that usually require human intelligence. Over the past couple of decades, AI has evolved so much that you can find it everywhere. So let’s discover this field a little more in-depth.
Types of Artificial Intelligence :
Technology is never in a state of limbo, it is always evolving. The skills that were in demand last year become old as soon as the new year arrives. Employers expect candidates to possess the technical skills that are in trend. The technology sector is highly competitive. There are thousands of candidates vying for a few lucrative jobs. We all know that change is the only constant. Regardless of your profession and designation, you must adapt to the constant changes taking place at your workplace. You must learn new job skills throughout your work life to keep up with workplace changes, grow your career, and boost career opportunities.
So, here is the list of the top 8 technical skills you need to learn as soon as possible because they are going to rule in 2023. The list goes as follows:
1. Artificial Intelligence:
Artificial intelligence (AI) is a broad field of computer science involved in building intelligent machines that can perform tasks that usually require human intelligence. Over the past couple of decades, AI has evolved so much that you can find it everywhere. So let’s discover this field a little more in-depth.
1. Reactive Machines:
• Purely responsive machines are the most basic type of artificial intelligence.
• These AI machines do not store information or past actions for future reference.
• These machines focus only on the current scenario and react to them according to the best possible actions.
• IBM’s Deep Blue system is an example of a reactive machine.
• Another example of a reactive machine is Google’s AlphaGo.
2. Limited Memory:
• Machines with limited memory can quickly store past experiences and some data.
• These machines can use the saved statistics for a restricted period.
• The self-driving car is one of the best examples of memory-limited systems.
• These cars can store the current speed of nearby vehicles, distance from other vehicles, speed limits, and other information for navigating the road.
3. Theory of Mind:
• AI needs to understand human emotions, people, and beliefs and interact socially like humans.
• This kind of AI machine has not been developed yet, but researchers are making great efforts to establish such an AI machine.
4. Self-Awareness:
• Self-aware AI is the future of artificial intelligence. These machines are brilliant and have their consciousness, emotions, and self-awareness.
• These machines are more intelligent than the human mind.
• Self-aware AI does not yet exist in reality; it is a fictitious concept.
To get the most out of artificial intelligence, many companies are putting significant resources into building data science teams. For the evaluation of data received from a variety of sources, data scientists use skills from a variety of disciplines, including statistics, computer science, and business. Learn bay has a reputation for providing its professionals with the greatest possible education. Everything, including AI, is taught in conjunction with relevant project experience for greater exposure to the material.
Benefits of AI :
1. Reduction in Human Error
One of the biggest advantages of Artificial Intelligence is that it can significantly reduce errors and increase accuracy and precision. The decisions taken by AI in every step are decided by information previously gathered and a certain set of algorithms. When programmed properly, these errors can be reduced to null.
2. Zero Risks
Another big advantage of AI is that humans can overcome many risks by letting AI robots do them for us. Whether it be defusing a bomb, going to space, or exploring the deepest parts of oceans, machines with metal bodies are resistant to nature and can survive unfriendly atmospheres. Moreover, they can provide accurate work with greater responsibility and not wear out easily.
3. 24×7 Availability
Many studies show humans are productive for only about 3 to 4 hours in a day. Humans also need breaks and time off to balance their work life and personal life. But AI can work endlessly without breaks. They think much faster than humans and perform multiple tasks at a time with accurate results. They can even handle tedious repetitive jobs easily with the help of AI algorithms.
4. Digital Assistance
Some of the most technologically advanced companies engage with users using digital assistants, which eliminates the need for human personnel. Many websites utilize digital assistants to deliver user-requested content. We can discuss our search with them in conversation. Some chatbots are built in a way that makes it difficult to tell whether we are conversing with a human or a chatbot.
We all know that businesses have a customer service crew that must address the doubts and concerns of the patrons. Businesses can create a chatbot or voice bot that can answer all of their client’s questions using AI.
Related Reading: Top Digital Marketing Trends
5. New Inventions
In practically every field, AI is the driving force behind numerous innovations that will aid humans in resolving the majority of challenging issues.
2. Machine learning :
Machine learning (ML) is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.
It is the study of computer algorithms that improve automatically through experience. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as “training data”, to make predictions or decisions without being explicitly programmed to do so.
Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop conventional algorithms to perform the needed tasks.
Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory, and application domains to the field of machine learning. Data mining is a related field of study, focusing on exploratory data analysis through unsupervised learning. In its application across business problems, machine learning is also referred to as predictive analytics.
Benefits of Machine Learning:
The myriad uses of machine learning indicate just how beneficial the technology can be for businesses of all types. No matter where or how it is used, businesses describe its machine-learning benefits in terms of exponential gains and improvements.
Faster decision-making:
By allowing businesses to process and analyze data more quickly than ever before, machine learning enables rapid – even split-second – decision-making. For example, machine-learning-based software trained to identify anomalies in a company’s security environment can automatically detect a data breach instantly and notify that organization’s tech team. By enabling fast decisions about effective remediation, these platforms can help companies safeguard customer data, uphold their business reputations, and avoid costly corrective measures.
Forecasting demand more accurately:
To compete in a rapidly changing business landscape, companies are under increasing pressure to anticipate market trends and customer behavior. By incorporating machine learning models into their data analytics, businesses gain far more accurate and powerful capabilities for forecasting demand, which translates into more effective inventory management and big cost savings.
Personalizing customer engagement:
Personalization has also become a critical strategy for competing in today’s marketplace. With machine learning platforms that analyze user behavior and suggest additional products based on purchase history, online retailers interact with customers in a more personalized way and drive more sales. Global giant Amazon is a prime example, with its use of machine learning to create lists of recommended products and feed suggestions to customers.
Boosting efficiency:
The use of machine learning allows businesses to accelerate repetitive tasks and shift human resources to higher-value activities. For example, machine learning technology can perform exhaustive document searches in a fraction of the time it takes people to perform scanning and cross-referencing tasks. These capabilities allow companies to reduce costs for information retrieval activities related to regulatory compliance and legal research, while also freeing employees to focus their efforts elsewhere.
Capital asset efficiency:
It can be difficult for enterprises to accurately gauge when capital assets will need maintenance work or upgrades, and the costs to do so can be steep. With predictive machine learning models, businesses can automate the collection of performance data from equipment and components and both monitor their conditions and compute the remaining lifetime of the assets.
3. Block Chain :
Blockchain is a system of recording information in a way that makes it difficult or impossible to change, hack, or cheat the system. A blockchain is essentially a digital ledger of transactions that is duplicated and distributed across the entire network of computer systems on the blockchain.
Each block in the chain contains several transactions, and every time a new transaction occurs on the blockchain, a record of that transaction is added to every participant’s ledger. The decentralized database managed by multiple participants is known as Distributed Ledger Technology (DLT). Blockchain is a type of DLT in which transactions are recorded with an immutable cryptographic signature called a hash.
There have been many attempts to create digital money in the past, but they have always failed. The prevailing issue is trust. If someone creates a new currency called the X dollar, how can we trust that they won’t give themselves a million X dollars, or steal your X dollars for themselves.
Bitcoin was designed to solve this problem by using a specific type of database called a blockchain. Most normal databases, such as an SQL database, have someone in charge who can change the entries (e.g. giving themselves a million X dollars). Blockchain is different because nobody is in charge; it’s run by the people who use it. What’s more, bitcoins can’t be faked, hacked, or double-spent – so people that own this money can trust that it has some value.
Benefits of Block Chain:
Immutability:
Blockchain supports immutability, meaning it is impossible to erase or replace recorded data. Therefore, the blockchain prevents data tampering within the network. Traditional data do not exhibit immutability. The conventional database uses CRUD (create, read, update and delete) at the primary level to ensure proper application operation, and the CRUD model enables easy erasing and replacement of data. Such data can be prone to manipulation by rogue administrators or third-party hacks.
Transparency:
Blockchain is decentralized, meaning any network member can verify data recorded into the blockchain. Therefore, the public can trust the network. On the other hand, a traditional database is centralized and does not support transparency. Users cannot verify information whenever they want, and the administration makes a selected set of data public. Still, however, individuals cannot verify the data.
Censorship:
Blockchain technology is free from censorship since it does not have control of any single party. Therefore, no single authority (including governments) can interrupt the operation of the network. Meanwhile, traditional databases have central authorities regulating the operation of the network, and the authority can exercise censorship. For instance, banks can suspend users’ accounts.
Traceability:
Blockchain creates an irreversible audit trail, allowing easy tracing of changes on the network. The traditional database is neither transparent nor immutable; hence, no permanent trial is guaranteed.
4. Database Management :
A Database Management System (DBMS) is software designed to store, retrieve, define, and manage data in a database. Database management refers to the actions a business takes to manipulate and control data to meet necessary conditions throughout the entire data lifecycle.
A database management system (DBMS) is a software package designed to define, manipulate, retrieve and manage data in a database. A DBMS generally manipulates the data itself, the data format, field names, record structure, and file structure. It also defines rules to validate and manipulate this data. A DBMS relieves users of framing programs for data maintenance. Fourth-generation query languages, such as SQL, are used along with the DBMS package to interact with a database.
A DBMS always provides data independence. Any change in storage mechanism and formats are performed without modifying the entire application. There are four main types of database organization:
Relational Database:
Data is organized as logically independent tables. Relationships among tables are shown through shared data. The data in one table may reference similar data in other tables, which maintains the integrity of the links among them. This feature is referred to as referential integrity – an important concept in a relational database system. Operations such as “select” and “join” can be performed on these tables. This is the most widely used system of database organization.
Flat Database:
Data is organized in a single kind of record with a fixed number of fields. This database type encounters more errors due to the repetitive nature of data.
Object-Oriented Database:
Data is organized with similarity to object-oriented programming concepts. An object consists of data and methods, while classes group objects having similar data and methods.
Hierarchical Database:
Data is organized with hierarchical relationships. It becomes a complex network if the one-to-many relationship is violated.
Benefits of Database Management:
Improved data sharing and data security:
Database management systems help users share data quickly, effectively, and securely across an organization. By providing quick solutions to database queries, a data management system enables faster access to more accurate data. End users, like salespeople, can speed up sales cycles and get more accurate in their sales prospecting.
Effective data integration:
Implementing a database management system will promote a more integrated picture of your operations by easily illustrating how processes in one segment of the organization affect other segments.
Consistent, reliable data:
Data inconsistency occurs when different versions of matching data exist in different places in an organization. For example, one group has a client’s correct email, and another the correct phone number.
Increased productivity:
Deploying a DBMS typically results in increased productivity because a good DBMS empowers people to spend more time on high-value activities and strategic initiatives, and less time cleaning data and manually scrubbing lists.
Better decision-making:
Decisions built on data are only as good as the information used. A database management system helps provide a framework to facilitate data quality initiatives. Better data management procedures generate higher-quality information, which leads to better decision-making across an organization.
5. Cyber Security :
Just like physical security refers to protecting valuables in the real world, cybersecurity is the practice of protecting devices, data, and networks from unauthorized access and subsequent misuse.
In addition, organizations transmit sensitive data across networks to other devices which put the information at increased risk of online threats in a nutshell, cybersecurity refers to the technologies, methods, and processes aimed at protecting the integrity and confidentiality of networks, data, and computer systems of organizations from internal and external threats.
As the intensity, frequency, and sophistication of cybercrimes and scams grow, businesses and organizations incur huge losses. Consequently, they are compelled to channel their resources into sophisticated information security technologies to reinforce the security infrastructure.
Types of Cybersecurity:
While there are different ways to break down the types of cybersecurity, here are the most common types that you are more than likely to encounter in the field:
Application security:
Application security refers to using hardware and software methods to address threats that may arise during the development stage of applications. In other words, it looks for defects and breaches in the application code to enhance the security of apps. Firewalls, antivirus programs, and encryption programs are examples of application security.
Information security:
Also referred to as data security, it is a set of practices to secure data from unauthorized access while it is being stored or transmitted from one device or physical location to another.
Network security:
Network security ensures that internal networks are secured from unauthorized intrusion, exploitation, modification, and other malicious intent. New passwords, extra logins, anti-spyware software, antivirus programs, and firewalls are examples of network security implementation.
Critical infrastructure security:
Modern society relies on critical infrastructural facilities such as water purification, electricity grid, hospitals, traffic lights, etc., that are equally vulnerable to cyber-attacks. The security of the such vital infrastructure is essential for the well-being and safety of society and the businesses concerned with them.
Cloud security:
Data stored in cloud resources are at an equal risk of cyber threats. Consequently, cloud security is a software-based security tool aimed at protecting and monitoring data in the cloud. Cloud security offers similar perks as the traditional on-premises data centers with the added advantages of minimal security breaches and reduced time and costs involved in maintaining huge data facilities.
Benefits of Cyber Security:
The importance of cyber security comes down to the need and requirement to keep information, data, and devices secure. In today’s world, people store vast quantities of data on computers, servers, and other connected devices. Much of this is sensitive, such as Personally Identifiable Information (PII) including passwords or financial data. And then there’s Intellectual Property (IP).
If a cybercriminal was to gain access to this data, they can cause havoc. They can share sensitive information, use passwords to steal funds, or even change data so that it benefits them, the attacker. Organizations need to have security solutions that enable them to be compliant.
By implementing security solutions, businesses and individuals (such as MSSPs) can protect themselves and others against the full range of cybersecurity threats outlined below.
With cyber security, companies have peace of mind that unauthorized access to their network or data is protected. Both end users, organizations, and their employees benefit.
It isn’t just detection that cybersecurity strengthens, it’s also mitigation and response. Should an attacker utilizing advanced techniques be successful the recovery process is far quicker. In addition, companies will often notice that customers and developers are more confident in products that have strong cybersecurity solutions in place.
6. RPA (Robotic Process Authentication) :
Governed by business logic and structured inputs, robotic process automation (RPA) is an automation technology that helps organizations partially or fully automate standardized tasks.
Robotic process automation software robots, or “bots” can mimic the actions of humans to perform jobs such as data entry, transaction processing, response triggering, and communicating with other digital systems. RPA systems range from the simple website “chatbots” that can answer standard queries to deployments of thousands of bots that can automate credit card processing and fraud detection jobs.
Typically, organizations begin with small robotic process automation pilot programs and then move to more comprehensive programs over time. Often, enterprises will bring developers on board to create more sophisticated solutions.
These will usually involve the implementation of dedicated PCs or virtual clients – increasingly located in the cloud – that are used exclusively by the software bots. These large-scale deployments typically involve hundreds or thousands of software bots to handle vast numbers of routine tasks.
RPA technologies are meant to enhance – not replace – the human workforce, and can:
Boost efficiency:
RPA helps humans shift focus and resources away from low-value, high-volume tasks such as data entry and focus on ideas, innovation, and higher-value work. This, in turn, can help reduce employee burnout and workforce churn.
Reduce operational risk:
By eliminating human errors due to everything from lack of sleep to hunger to carelessness, RPA ensures heightened accuracy and consistency of outputs.
Reduce costs:
RPA speeds transactional work and enhances the productivity of the human workforce – helping organizations do more with less.
Accelerate scale:
Since robots don’t take breaks and can work 24x7x365, processes can be scaled easily across countries and business units or entities.
Simplify compliance:
By minimizing human access to sensitive systems and information, RPA can help reduce the number of compliance and audit challenges and help streamline audits.
According to the Deloitte Global RPA Survey, 2018, RPA can improve workforce productivity by 86 percent, improve quality and accuracy by 90 percent and improve compliance by 92 percent.
7. Computer Programming :
A computer program consists of code that is executed on a computer to perform particular tasks. This code is written by programmers.
Programming is the process of giving machines a set of instructions that describe how a program should be carried out. Programmers will spend their whole careers learning a variety of programming languages and tools so they can effectively build computer programs.
Programmers will start by using a code editor or IDE to write what is called source code. This is a collection of code written in a programming language that other programmers can read.
Source code needs to be converted into machine language so machines can understand the instructions and execute the program. This process of converting source code into machine language is known as compiling.
Examples of compiled programming languages would be C and C++.
Other languages do not use compilers. Instead, these languages will use an interpreter that will read and execute the code.
Examples of interpreted programming languages would be JavaScript and PHP.
Once the code is executed, then the computer program can run. The different types of computer programs include Word processors, Database systems, video games, and websites. These computer programs allow us to interact with different software devices and services like phones, websites, and the computers themselves.
Here are a few popular programming languages.
- Python
- JavaScript
- C/C++
- Java
- C#
- Ruby
- PHP
Benefits of learning Computer Programming:
In today’s technological age, computer programming skills have become a necessity for everyone including students. Apart from offering a distinct advantage in the career market, programming kills have many other advantages.
However, for an ordinary user of the computer, programming is not mandatory though complementary. To run the applications on a computer, one doesn’t need to know what the computer is doing, however, a better understanding of the processes that happen inside the computer will ensure better results.
Learning coding will increase problem-solving skills and analytical thinking. Even simple programs like Scratch or Kodu can make a significant change in the skill sets of students even if they are ready to delve into advanced programming languages like PHP.
Computers can be utilized as a fabulous educational medium through programming languages that will inspire students to explore, experiment, and arrive at conclusions. Apart from fine-honing logical thinking, programming will develop the learning behavior of the students.
Being a programmer will make it possible for you to create your websites, become a coder by profession or start an IT business of your own among others. No matter whether you learn coding as a hobby or as a career choice, it will come with loads of benefits that probably not many other courses cannot do.
Here are some advantages of learning computer programming.
Create Your Website:
Ever since the web ever evolved in 1991, it has had an overwhelming influence on everyone’s lives. Most businesses do business through their websites thanks to the raging popularity of eCommerce and to maintain a website, you may need at least a basic knowledge of HTML and CSS code, on which all websites run.
A lucrative career option:
Computer programmers can choose from a range of career paths, including healthcare, Research, and development in various latest subjects like Machine learning and Computational biology among others.
Job Satisfaction:
IT sector jobs offer excellent working conditions and salary packages with average working hours of 40-50 hrs in climate-controlled office environments. Computer programmers often enjoy the benefit of working from home as they need only a computer and an Internet connection to do the job.
High Demand:
There is a huge demand for computer-related professions, which is expected to increase by 32 percent by 2018. Programmers with expertise in niche areas like the Internet, intranet, and Web 2.0 applications will be in particular demand.
8. Augmented Reality (AR) and Virtual Reality (VR) :
Augmented reality (AR) is a technology that layers virtual enhancements atop our existing reality. AR is developed into apps and used on mobile devices to blend digital components. As technology gets better this will be integrated into contact lenses and glasses for consumers to consume and interact with.
Virtual Reality (VR) is an artificial environment that seeks to synthetically introduce stimuli to your senses. This means that one’s sight, sound, touch, smell, and even taste can be artificially stimulated.
The Sensorama Machine, invented in 1957 and then patented in 1962 was the first interactive film experience in which viewers were invited to watch a film that would use all of their senses. This multi-sensory experience was also the first ‘3D film’, designed for a single viewer and enabled the viewer to become immersed through multiple senses in the media. For example, he used an oscillating fan so that the viewer could feel the wind blowing on their face.
The first HMD that we would recognize was built by Ivan Sutherland in 1968 with the help of his students and was nicknamed the ‘Sword of Damocles’ as it was so heavy it had to be suspended from the ceiling by a metal pole.
By today’s standards, it seems rather primitive, only displaying wireframe models for graphics and no text at all.
And it looked awesome. It looks like the images are being piped into your brain via the eyes. This has to go down as the most cyberpunk-looking VR head-mounted display ever.
From this point in VR’s history, it is ‘just’ resolution and fidelity boosts to get to our modern consumer-based headsets. We can see many peripherals and equipment that was created in the 90s that foreshadowed our systems today with life-size accessories and controller methods to further immerse the content consumer in the scene. Unfortunately, due to the primitive state of graphics at this point, the full benefit of such systems had yet to be realized.
Benefits of AR and VR:
Providing Training in a Safe and Affordable Manner:
Some industries need to train their employees in the processes and operations before they assume full responsibility. For instance, employees working in power plants or manufacturing units need to know how to operate machines properly on the site. Unless they get a good knowledge of things, they cannot be allowed to take over.
A Better Way of Practicing Skills:
Practicing your skills is the best way to sharpen them. According to studies, we retain much more information when we combine our learning with “doing.” Hands-on practice is the best way to retain information compared to discussions, lectures, reading, or even audio-visual learning. It has a retention rate of 75% compared to lectures with 5% retention capabilities.
Developing Soft Skills and Expertise:
VR and AR can help enterprises develop their employees’ soft skills and expertise. Walmart, for example, has been using VR to train its employees to handle customers better. The retail giant even used VR to get employees familiar with dealing with Black Friday customers. Such opportunities help enterprises get employees ready to provide increased customer satisfaction.
Employers can create VR simulations for specific situations the employees are likely to encounter. This makes the employees more comfortable in the actual situations and enables them to provide better service to the customers. Walmart, in this case, uses the Oculus VR headset to impart the training. These technologies are ideal for letting employees develop soft skills.
Getting Employees Ready for Emergencies:
VR and AR are ideal for training employees to handle real-life situations. Currently, some airports are using this technology for airport safety training. The International Air Transport Association has long used a VR platform to train employees in on-ground operations.
The technique allowed the association to cut back damage to aircraft and equipment and reduce the cost of training. Some companies are using VR to train employees to handle emergencies. Walmart seems to be a pioneer in VR learning, using the technology to train employees for real-time threats. The organization used VR to train the staff to learn how to control a shooting situation.
Enhance the Effectiveness of Learning Materials:
Employers can develop solutions where pointing your phone camera at a specific text of a training manual leads to additional materials or resources popping up on the users’ screen. This technique can be used by enterprises to train employees about certain products, services, or solutions. Research also shows VR teaching to be more effective than traditional methods. According to a study, the VR/AR learners had a recall rate of 80% even after 1-year of training. Traditional learning, on the other hand, has a recall rate of only 20% after 1-week.
Helping Employees Develop Technical Skills:
VR and AR are ideal for developing soft skills and practice-based learning. However, the same technologies can also help develop technical skills. The healthcare industry has already started using VR to train doctors and nurses. In one study by Yale University, the VR learners performed surgeries 29% faster and with 6 times fewer mistakes than the traditional learning group.
The Best Way for Gamification:
Gamification has been used for a while to train and onboard employees. The approach helps employees learn better and show an increased success rate. VR and AR can now take gamification to a completely new level.
Enterprises can now use VR to develop advanced gamification techniques for improved learning. The process is perfect for getting your employees on board and cutting the tiresome process in half. You can even present the best of your company and develop a highly engaging learning experience.
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