Computer Science & Engineering Course™

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devops professional course

Computer Science & Engineering Course™

This Computer Science & Engineering course is the leading online training, already taken by thousands of professionals worldwide, has become the reference in Medical Tourism education and certification in the industry.

hink about some of the different ways that people use computers. In school, students use computers for tasks such as writing papers, searching for articles, sending email, and participating in online classes. At work, people use computers to analyze data, make presentations, conduct business transactions, communicate with customers and coworkers, control machines in manufacturing facilities, and do many other things. At home, people use computers for tasks such as paying bills, shopping online, communicating with friends and family, and playing computer games. And don’t forget that cell phones, iPods®, BlackBerries®, car navigation systems, and many other devices are computers too. The uses of computers are almost limitless in our everyday lives.

Computers can do such a wide variety of things because they can be programmed. This means that computers are not designed to do just one job, but to do any job that their programs tell them to do. A program is a set of instructions that a computer follows to perform a task. For example, Figure 1-1 shows screens from two commonly used programs, Microsoft Word and Adobe Photoshop. Microsoft Word is a word processing program that allows you to create, edit, and print documents with your computer. Adobe Photoshop is an image editing program that allows you to work with graphic images, such as photos taken with your digital camera.

Programs are commonly referred to as software. Software is essential to a computer because it controls everything the computer does. All of the software that we use to make our computers useful is created by individuals working as programmers or software developers. A programmer, or software developer, is a person with the training and skills necessary to design, create, and test computer programs. Computer programming is an exciting and rewarding career. Today, you will find programmers’ work used in business, medicine, government, law enforcement, agriculture, academics, entertainment, and many other fields.

If you are looking for a career at the cutting edge of Computer Science & Engineering, you can start learning for FREE Now! Click the button below:



Medical Tourism Course™

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devops professional course

Medical Tourism Course™

This Medical Tourism course is the leading online training, already taken by thousands of professionals worldwide, has become the reference in Medical Tourism education and certification in the industry.

Increasing the productivity of production systems has been at the heart of every industrial revolution. The fourth industrial revolution brings an increase in productivity in both production and management systems.

From a business perspective, the goal of the fourth industrial revolution is to be able to manufacture personalized products at mass cost. To achieve this goal, it is necessary to rethink the production tools and bring more automation and productivity to the factories, but also to improve collaboration between supply chain, engineering, and sales and operations.

From experts’ point of view, we’re really entering, at this moment, the fourth revolution of industry, or the cognitive manufacturing era, and it is fully differentiated from any that came before it.
The digital transformation of production processes creates new opportunities to achieve levels of productivity and specialization not previously possible.
Data and, more importantly, analytics, are changing the way we see our machines, processes, products and operations. Analytics combined with big data approaches can identify patterns in the data, uncover model behaviors of equipment and predict failures or product quality issues.
These capabilities, known as predictive maintenance and quality, enabled by Industry 4.0 technologies, have an important place in companies’ strategies. As more factories and equipment are instrumented with Internet of Things (IoT) and connected devices, data will continue to amass.
Conventional computing will struggle to scale with the large influx of data and the complexity of the analytics. Computing must become cognitive to process, analyze and optimize the information at the shop floor level.
In order to truly pave the way forward to Industry 4.0 and beyond, manufacturing must evolve into the concept of an information technology (IT)-based digital factory – into cognitive manufacturing. Manufacturing must enable the
cognitive capabilities inside the factory, particularly around two key issues: production quality insights and production optimization.
Transforming and improving manufacturing through production quality insights and production optimization is realized through the concept of an Industrial Internet of Things (IIoT) platform. This tutorial will attempt to explain the principles of an IIoT platform, as well as explore use cases.
If you are looking for a career at the cutting edge of DevOps, you can start learning for FREE Now! Click the button below:



Robot Process Automation (RPA) Professional Course™

design thinking certification course

Robot Process Automation (RPA) Professional Course™

This Design Thinking course is the leading online training, already taken by thousands of professionals worldwide, has become the reference in Design Thinking education and certification in the industry.

Increasing the productivity of production systems has been at the heart of every industrial revolution. The fourth industrial revolution brings an increase in productivity in both production and management systems.

From a business perspective, the goal of the fourth industrial revolution is to be able to manufacture personalized products at mass cost. To achieve this goal, it is necessary to rethink the production tools and bring more automation and productivity to the factories, but also to improve collaboration between supply chain, engineering, and sales and operations.

From experts’ point of view, we’re really entering, at this moment, the fourth revolution of industry, or the cognitive manufacturing era, and it is fully differentiated from any that came before it.
The digital transformation of production processes creates new opportunities to achieve levels of productivity and specialization not previously possible.
Data and, more importantly, analytics, are changing the way we see our machines, processes, products and operations. Analytics combined with big data approaches can identify patterns in the data, uncover model behaviors of equipment and predict failures or product quality issues.
These capabilities, known as predictive maintenance and quality, enabled by Industry 4.0 technologies, have an important place in companies’ strategies. As more factories and equipment are instrumented with Internet of Things (IoT) and connected devices, data will continue to amass.
Conventional computing will struggle to scale with the large influx of data and the complexity of the analytics. Computing must become cognitive to process, analyze and optimize the information at the shop floor level.
In order to truly pave the way forward to Industry 4.0 and beyond, manufacturing must evolve into the concept of an information technology (IT)-based digital factory – into cognitive manufacturing. Manufacturing must enable the
cognitive capabilities inside the factory, particularly around two key issues: production quality insights and production optimization.
Transforming and improving manufacturing through production quality insights and production optimization is realized through the concept of an Industrial Internet of Things (IIoT) platform. This tutorial will attempt to explain the principles of an IIoT platform, as well as explore use cases.
If you are looking for a career at the cutting edge of Design Thinking, you can start learning for FREE Now! Click the button below:



DevOps Professional Course™

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devops professional course

DevOps Professional Course™

This Design Thinking course is the leading online training, already taken by thousands of professionals worldwide, has become the reference in DevOps education and certification in the industry.

Increasing the productivity of production systems has been at the heart of every industrial revolution. The fourth industrial revolution brings an increase in productivity in both production and management systems.

From a business perspective, the goal of the fourth industrial revolution is to be able to manufacture personalized products at mass cost. To achieve this goal, it is necessary to rethink the production tools and bring more automation and productivity to the factories, but also to improve collaboration between supply chain, engineering, and sales and operations.

From experts’ point of view, we’re really entering, at this moment, the fourth revolution of industry, or the cognitive manufacturing era, and it is fully differentiated from any that came before it.
The digital transformation of production processes creates new opportunities to achieve levels of productivity and specialization not previously possible.
Data and, more importantly, analytics, are changing the way we see our machines, processes, products and operations. Analytics combined with big data approaches can identify patterns in the data, uncover model behaviors of equipment and predict failures or product quality issues.
These capabilities, known as predictive maintenance and quality, enabled by Industry 4.0 technologies, have an important place in companies’ strategies. As more factories and equipment are instrumented with Internet of Things (IoT) and connected devices, data will continue to amass.
Conventional computing will struggle to scale with the large influx of data and the complexity of the analytics. Computing must become cognitive to process, analyze and optimize the information at the shop floor level.
In order to truly pave the way forward to Industry 4.0 and beyond, manufacturing must evolve into the concept of an information technology (IT)-based digital factory – into cognitive manufacturing. Manufacturing must enable the
cognitive capabilities inside the factory, particularly around two key issues: production quality insights and production optimization.
Transforming and improving manufacturing through production quality insights and production optimization is realized through the concept of an Industrial Internet of Things (IIoT) platform. This tutorial will attempt to explain the principles of an IIoT platform, as well as explore use cases.
If you are looking for a career at the cutting edge of DevOps, you can start learning for FREE Now! Click the button below:



Design Thinking Course™

design thinking certification course

Design Thinking Course™

This Design Thinking course is the leading online training, already taken by thousands of professionals worldwide, has become the reference in Design Thinking education and certification in the industry.

Increasing the productivity of production systems has been at the heart of every industrial revolution. The fourth industrial revolution brings an increase in productivity in both production and management systems.

From a business perspective, the goal of the fourth industrial revolution is to be able to manufacture personalized products at mass cost. To achieve this goal, it is necessary to rethink the production tools and bring more automation and productivity to the factories, but also to improve collaboration between supply chain, engineering, and sales and operations.

From experts’ point of view, we’re really entering, at this moment, the fourth revolution of industry, or the cognitive manufacturing era, and it is fully differentiated from any that came before it.

The digital transformation of production processes creates new opportunities to achieve levels of productivity and specialization not previously possible.

Data and, more importantly, analytics, are changing the way we see our machines, processes, products and operations. Analytics combined with big data approaches can identify patterns in the data, uncover model behaviors of equipment and predict failures or product quality issues.

These capabilities, known as predictive maintenance and quality, enabled by Industry 4.0 technologies, have an important place in companies’ strategies. As more factories and equipment are instrumented with Internet of Things (IoT) and connected devices, data will continue to amass.

Conventional computing will struggle to scale with the large influx of data and the complexity of the analytics. Computing must become cognitive to process, analyze and optimize the information at the shop floor level.

In order to truly pave the way forward to Industry 4.0 and beyond, manufacturing must evolve into the concept of an information technology (IT)-based digital factory – into cognitive manufacturing. Manufacturing must enable the
cognitive capabilities inside the factory, particularly around two key issues: production quality insights and production optimization.

Transforming and improving manufacturing through production quality insights and production optimization is realized through the concept of an Industrial Internet of Things (IIoT) platform. This tutorial will attempt to explain the principles of an IIoT platform, as well as explore use cases.

If you are looking for a career at the cutting edge of Design Thinking, you can start learning for FREE Now! Click the button below:

Additive Manufacturing (3D Printing) Course™

additive manufacturing certification course

Additive Manufacturing Course™

This Additive Manufacturing course is the leading online training, already taken by thousands of professionals worldwide, has become the reference in nanotechnology education and certification in the industry.

Increasing the productivity of production systems has been at the heart of every industrial revolution. The fourth industrial revolution brings an increase in productivity in both production and management systems.

From a business perspective, the goal of the fourth industrial revolution is to be able to manufacture personalized products at mass cost. To achieve this goal, it is necessary to rethink the production tools and bring more automation and productivity to the factories, but also to improve collaboration between supply chain, engineering, and sales and operations.

From experts’ point of view, we’re really entering, at this moment, the fourth revolution of industry, or the cognitive manufacturing era, and it is fully differentiated from any that came before it.

The digital transformation of production processes creates new opportunities to achieve levels of productivity and specialization not previously possible.

Data and, more importantly, analytics, are changing the way we see our machines, processes, products and operations. Analytics combined with big data approaches can identify patterns in the data, uncover model behaviors of equipment and predict failures or product quality issues.

These capabilities, known as predictive maintenance and quality, enabled by Industry 4.0 technologies, have an important place in companies’ strategies. As more factories and equipment are instrumented with Internet of Things (IoT) and connected devices, data will continue to amass.

Conventional computing will struggle to scale with the large influx of data and the complexity of the analytics. Computing must become cognitive to process, analyze and optimize the information at the shop floor level.

In order to truly pave the way forward to Industry 4.0 and beyond, manufacturing must evolve into the concept of an information technology (IT)-based digital factory – into cognitive manufacturing. Manufacturing must enable the
cognitive capabilities inside the factory, particularly around two key issues: production quality insights and production optimization.

Transforming and improving manufacturing through production quality insights and production optimization is realized through the concept of an Industrial Internet of Things (IIoT) platform. This tutorial will attempt to explain the principles of an IIoT platform, as well as explore use cases.

If you are looking for a career at the cutting edge of Smart Cities Transportation, you can start learning for FREE Now! Click the button below:

Smart Cities Transportation Course™

smart cities transportation certification course

Smart Cities Transportation Course™

This Smart Cities Transportation course is the leading online training, already taken by thousands of professionals worldwide, has become the reference in nanotechnology education and certification in the industry.

In this course we refer to transportation as any and every system that moves people around a city. Think of a city’s streets, vehicles, railways, subways, buses, bicycles, streetcars, ferries and so on. All play an essential role in the hustle and bustle of today’s cities in commuting to work, running errands, attending classes, enjoying a night out, shipping and receiving products, delivering pizzas. We rely on the vast web of transportation networks in our cities. We trust that they will get us where we need to be in an efficient, safe manner for a reasonable price.

But that’s not always the case. Transportation networks in cities around the world struggle with serious problems, like congestion. A recent study calculated that traffic congestion in 2019 wasted $121 billion in the United States alone in time, fuel and money. Another study predicts that emissions from vehicles idling in traffic jams will result in 1,600 premature deaths and $13 billion in “total social costs” in the U.S. by 2025.

Fortunately, there are a lot of ways cities can fix traffic congestion by deploying ICT, as you’ll read about in the sections that follow.

The promise of smart transportation and the reality of city congestion means that this market subsector is growing rapidly. A 2019 study by MarketsAndMarkets found that global spending on smart transportation initiatives will quadruple to more than $102 billion in 2025 from almost $27 billion in 2020.

As you explore this course you’ll discover there are four targets that cities need to achieve to put smart transportation into high gear. We’ll also briefly discuss how the universal targets apply to transportation. But first, a quick look at transportation dependencies and then we’ll highlight the incredible benefits in livability, workability and sustainability that smart transportation networks provide.

If you are looking for a career at the cutting edge of Smart Cities Transportation, you can start learning for FREE Now! Click the button below:

Augmented Reality (AR) in Sports Course™

Augmented Reality in Sports Certification Course

Augmented Reality (AR) in Sports Course™

This Augmented Reality (AR) course is the leading online training, already taken by thousands of professionals worldwide, has become the reference in nanotechnology education and certification in the industry.

Increasing the productivity of production systems has been at the heart of every industrial revolution. The fourth industrial revolution brings an increase in productivity in both production and management systems.

From a business perspective, the goal of the fourth industrial revolution is to be able to manufacture personalized products at mass cost. To achieve this goal, it is necessary to rethink the production tools and bring more automation and productivity to the factories, but also to improve collaboration between supply chain, engineering, and sales and operations.

From experts’ point of view, we’re really entering, at this moment, the fourth revolution of industry, or the cognitive manufacturing era, and it is fully differentiated from any that came before it.

The digital transformation of production processes creates new opportunities to achieve levels of productivity and specialization not previously possible.

Data and, more importantly, analytics, are changing the way we see our machines, processes, products and operations. Analytics combined with big data approaches can identify patterns in the data, uncover model behaviors of equipment and predict failures or product quality issues.

These capabilities, known as predictive maintenance and quality, enabled by Industry 4.0 technologies, have an important place in companies’ strategies. As more factories and equipment are instrumented with Internet of Things (IoT) and connected devices, data will continue to amass.

Conventional computing will struggle to scale with the large influx of data and the complexity of the analytics. Computing must become cognitive to process, analyze and optimize the information at the shop floor level.

In order to truly pave the way forward to Industry 4.0 and beyond, manufacturing must evolve into the concept of an information technology (IT)-based digital factory – into cognitive manufacturing. Manufacturing must enable the
cognitive capabilities inside the factory, particularly around two key issues: production quality insights and production optimization.

Transforming and improving manufacturing through production quality insights and production optimization is realized through the concept of an Industrial Internet of Things (IIoT) platform. This tutorial will attempt to explain the principles of an IIoT platform, as well as explore use cases.

If you are looking for a career at the cutting edge of Augmented Reality (AR) in Sports, you can start learning for FREE Now! Click the button below:

Augmented Reality (AR) in Logistics Course™

augmented reality in logistics certification course

Augmented Reality (AR) in Logistics Course™

This Augmented Reality (AR) in Logistics course is the leading online training, already taken by thousands of professionals worldwide, has become the reference in nanotechnology education and certification in the industry.

Augmented reality can be a real game changer for warehouse owners and workers alike. Read on to learn how AR can streamline warehouse workflows and feel free to check out our AR development services offer.

‘Augmented vision’ can be highly useful for various industries, especially for logistics and warehouse management. Of all the tasks associated with warehouse management, the area where AR enhancements can be most effective and promising is item picking. By guiding warehouse employees through order picking operations, handheld mobile devices and smart glasses with augmented reality software reduce time expenditures and the error rate. What’s more, such guidance can noticeably shorten training for new employees and let them work efficiently from the very start.

In this tutorial, we share with you how exactly augmented reality services streamline item picking and discuss the issues of device choice, AR training, and the integration of AR software with your in-house systems, including warehouse management system (WMS) and CRM.

Picking challenges can differ depending on multiple factors, including the square footage of your warehouse and the vertical space available in it, the use – or lack of – automated storage and retrieval systems (AS/RS), the number of people on your staff and their work experience. When choosing the functionality pack for your AR software, pay attention to the features that address the most acute challenges you currently face. You’ll be able to expand the functionality and add new features later on when you see the positive effect of AR-supported item picking firsthand.

This feature is a must for warehouses that are larger than 100,000 square feet, where employees use warehouse vehicles to move around faster. Medium-sized warehouses may also consider this feature since it jump-starts the work of employees in training, who don’t feel familiar with the place.

The way AR navigation works is quite straightforward. First, an employee uses smart glasses or a smartphone to open a list of the items to pick from. They can do it in less than a minute by simply uploading the list from the WMS integrated with the app. Software then analyzes the list along with reading the up-to-date warehouse layout data, and creates the most convenient and fast route for collecting all items.

Once the route is created, the app gives instructions on how to get to the next location. The instructions take the form of pointing arrows that appear as a virtual layer on the screen of the glasses or smartphone, augmenting the reality captured by the camera lens. A supplementary voice-over with basic navigating commands can be added as well.

If you are looking for a career at the cutting edge of Augmented Reality (AR) in Logistics, you can start learning for FREE Now! Click the button below:

Augmented Reality (AR) in Education Course™

augmented reality in education certification course

Augmented Reality (AR) in Education Course™

This Augmented Reality (AR) course is the leading online training, already taken by thousands of professionals worldwide, has become the reference in nanotechnology education and certification in the industry.

Increasing the productivity of production systems has been at the heart of every industrial revolution. The fourth industrial revolution brings an increase in productivity in both production and management systems.

From a business perspective, the goal of the fourth industrial revolution is to be able to manufacture personalized products at mass cost. To achieve this goal, it is necessary to rethink the production tools and bring more automation and productivity to the factories, but also to improve collaboration between supply chain, engineering, and sales and operations.

From experts’ point of view, we’re really entering, at this moment, the fourth revolution of industry, or the cognitive manufacturing era, and it is fully differentiated from any that came before it.

The digital transformation of production processes creates new opportunities to achieve levels of productivity and specialization not previously possible.

Data and, more importantly, analytics, are changing the way we see our machines, processes, products and operations. Analytics combined with big data approaches can identify patterns in the data, uncover model behaviors of equipment and predict failures or product quality issues.

These capabilities, known as predictive maintenance and quality, enabled by Industry 4.0 technologies, have an important place in companies’ strategies. As more factories and equipment are instrumented with Internet of Things (IoT) and connected devices, data will continue to amass.

Conventional computing will struggle to scale with the large influx of data and the complexity of the analytics. Computing must become cognitive to process, analyze and optimize the information at the shop floor level.

In order to truly pave the way forward to Industry 4.0 and beyond, manufacturing must evolve into the concept of an information technology (IT)-based digital factory – into cognitive manufacturing. Manufacturing must enable the
cognitive capabilities inside the factory, particularly around two key issues: production quality insights and production optimization.

Transforming and improving manufacturing through production quality insights and production optimization is realized through the concept of an Industrial Internet of Things (IIoT) platform. This tutorial will attempt to explain the principles of an IIoT platform, as well as explore use cases.

If you are looking for a career at the cutting edge of Augmented Reality (AR), you can start learning for FREE Now! Click the button below:

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