7 Things you Didn’t Know About Data Science

Discover 7 evidence about the “Oil of the 21st century” data sciences as well as digital data. In the United States, in particular, the world demand for engineering jobs is booming. In this article, we have jotted down some unknown facts about data science that you didn’t know about. So read and find out.

Only 0.5 percent of all information we generate is often processed and Used

There is enormous potential for the analysis of data with the growth of technology, cloud, and open data, but only very small. Le Wagon aims at fulfilling this growing need for new age engineers to discover, clean, analyze and forecast data using our renowned Bootcamp. Our team of talented developers, data scientists, and machine learning engineers combined with industry experts* with such a passion for education and spent almost a year designing the course until it was launched in 2020. The students of Le Wagón at the end of the 9-week Bootcamp acquired vital knowledge of data science and how to create a clear story around data and overcome real business obstacles.

The engineering industry is among the top fifteen jobs leading the employment market for the year 2021 as per LinkedIn, the largest network of professionals.

The market for engineering jobs is booming worldwide, and in 2021, this category of employment would specifically seek new talents throughout the world. Many businesses in all industries know that investing in digital technology is vital to the future of data collection, transformation, understanding, and analysis. Tech functions would be among the most important elements for the revival of business in such a “new normal” economy. As per a recent report, the engineering role of employers would be able to recruit these ‘pandemic-proof’ jobs categories this year. Many companies are honored to be involved in the digital transformation of the USA, and announce that the 9-week full-time data science Bootcamp will officially be launched in Dubai this April 2021.

The salaries of data science are far higher as compared to any other technology creation expert

Data functions are highly flexible, and data science involves a complex array of know-how. Data roles include various functions from simple maths – including statistics, probability to linear algebra – and much more advanced skills, including python programming – including the vocabulary of Python, Python libraries, the Jupyter Notebook. Indeed, most data engineers have been developers in the first backend. Before completing this course, many of our students attended our web-based development Bootcamp or had programming or mathematics skills. Such positions often require that non-technology workers be able to collaborate with teams and know how to interact with data science models. This is why we teach students the basic concept and have strong foundations, and also ensure they learn how to work together with a technology team as well as how their results are communicated to non-technical audiences. 

Data science is already used in sectors, from healthcare to art

“The 21st-century oil” is digital data. There is much available data, and in all sorts of sectors or areas: health care, commerce, agriculture, communication, and banking, there are countless compounds of real-world applications.

All through our data science bootcamps over the past two weeks, students work together on a concrete project of their choosing. In Germany last October, for instance, a student team developed a tool to identify false news, whereas an art-price estimator was created by another team. Last year in Paris, a team set up a model to forecast the time and number of new patients spending in hospitals, as well as another group successfully created a method for cardiologists to identify cardiovascular rhythms. Data science has countless use opportunities!

Data Scientists, Data Engineers, and Data Analysts are not Similar

Data analysts are also the nearest people to the company. The raw data is processed, purified, and activated by the data scientist. Excel, Statistics Data Visualisation, SQL, and Python are all very well known to you.

Mathematical analysis of the data is being carried out by data scientists. They utilize probability theory as well as algorithms to predict outcomes from found data patterns and need business or industry expertise.

Data engineers are quite engineering roles. They compile and ensure that the data is integral. They deploy the application to obtain, save and allow people who really need it to access data appropriately.

You may begin applying for jobs as a Python Data Analyst or as a Junior Data Scientist after our Bootcamp. You can also start at a Junior Data Engineer position, based on your level prior to the Bootcamp.

For a data science job, 75 percent of the data experts utilize Python

Over the last 1980s, Python was built to develop a large, supportive society, and that had plenty of time. Although it is a language that is high-level and could do complex work, with its simple syntax that gives greater importance to natural language, Python is among the most available programming languages. Our students are taught to code in Python and master other important Python-related resources like a Jupyter Notebook or Python Library at Le Wagon 9 weeks full-time Bootcamp.

Computer IT, statistics, domain knowledge, and mathematics are at the crossroads of data science

Data science is an interdisciplinary area that employs a combination of scientific, business as well as mathematical know-how. Our 9-week course covers all three areas, which ensure your readiness to market by the end of the Bootcamp.

Weeks 1-2: Basic Data Science. Python and Mathematics are fundamental in data science.

Week 3: Science of Decision. You would learn how to plan and convey your results to non-technical audiences with Python.

Weeks 4-5: Machine Learning. Throughout this module, you’ll understand the various classes of machine learning, diving into one of the most utilized libraries of Machine Learning: scikit-learn.

Sixth Week, deep research. We will discuss Neural Network building blocks and consider the building blocks of its Neural Networks and what parameters they use.

Week 7: Information engineering Week 7. You will learn all the best practices for experimenting and using machine learning to solve a fascinating problem.

8-9 weeks: Final Projects for Data Science. During the last two weeks, pupils will be working on and presenting a concrete data science experiment on a demo day.

Final Words

So these were some of the common facts about data science that you need to know about.

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13 Facts to Know about Artificial Intelligence

Scientists and innovations have been attempting to build a machine that thinks like a person since the advent of modern computer technology. In order to develop a mechanical process to human thinking and decision-making, algorithms and networks became the foundation of what is now called artificial intelligence.

AI is now a proper, practical tool, once laughed at as just the story of science-fiction movies. Mostly on the basis of bringing AI technology to the masses, several new startup companies are being created, and bigger companies enter the discussion as well.

Although there is a rapid growth of the AI industry, the technology continues to face challenges, including constant misunderstanding. In this article, we have jotted down some of the important facts about AI that you should be aware of.

AI has Deep Roots in the History

The thought of AI conjures up for many of us visions of a robot or other anthropomorphic machines which can both think and think and understand as well. Some Greek Myths, including the golden robots of Hephaestus, have already seen the concept of a machine-man. In addition, medieval myths about alchemy referred to the placement of the human brain in inanimate artifacts. Some also claim that statues hold human thinking and feeling, as they worship actual statues.

Alan Turing has Contributed a lot to the Development of AI

In 1950, Alan Turing released his paper “Computer Machinery and Intelligence,” in which he sought to determine whether a machine could win the “Emission Game,” which was also the name of the recent Turing film. The test tried to differentiate between the gender of two players from a machine. The paper implemented the Turing test for the first time. Computer machinery and information are widely considered to be the most important work on AI.

Formal Research on AI Begin During the 1950s

Even when AI was done previously, till the 1956 Dartmouth Conference, it did not become a formal academic discipline. The organizer, John McCarthy, promoted the use of the term “artificial intelligence.” Until his death in 2011, McCarthy continued to contribute to AI’s work in several universities.

Natural Processing of Language is Essential to AI

One of AI’s main aims is to realize the area of natural language processing in such a computer and to interact in natural languages. The machine should be able to process natural languages such as Spanish or English.

Autonomous vehicles require AI

The development of autonomous vehicles or vehicles which can pilot themselves have become one of the greatest technological advances in transport in recent years. With many of the top AI technologies we now have, new cars such as Google driverless cars and also some autonomous drones will not be feasible.

Investors Have Came Forward to Fund Upcoming AI companies

What is usually considered a “hot” market for startups, but AI is certainly a hot market. The number of new startups funded in the area is rising as per CB Insights. After a couple of years in service, businesses including Sentient Technologies raised over 100 million USD in funding.

Big tech Businesses are Gambling on AI 

The AI boom is not exclusively attributable to small startups. Major technological giants invest in space and even acquire AI firms. IBM’s Watson does everything from work for hospitals to preparing meals. Google made headlines when it bought AI’s 400 million USD DeepMind startup, and recently Facebook bought Wit.ai.

AI-powered robots can think together Robots Powered by AI 

The CoCoRo project has created artificial intelligence robots in Europe which can act as a fish school together. The robots could search an area, scan the environment and submit data.

Some Robots has Featured to Socialize

A robot named Kismet could communicate by recognizing the language and a lot of the human body as well as reposting it in accordance with the feedback from MIT’s Artificial Intelligent Lab. Throughout the 1990s, Cynthia Breazeal was created by Kismet.

Artificial Intelligence is Polarizing

There is no technology as controversial as AI. On the one hand, leading firms and universities are contributing money to AI R&D. Conversely; scientist Stephen Hawking cautioned that the end of the human race might be AI. Bill Gates and Elon Musk have expressed both negative views about AI. Whatever camp you go through, a unified view about AI is probably not going to be forthcoming.

Many AI Devices has Female Voice

Have you really wondered why so many “females” are virtual helpers? Take a glance at Siri, Cortana, Google Assistant, and Alexa, although they are not clearly named after women. They are all very nice and polite voices, and you could easily recognize them.

There may be a couple of explanations. The first point is that the voice of the woman is louder and also has a higher pitch, making it easier for users to equate with male voices to understanding. In addition, women’s voices are more appealing than men’s.

Even so, this may also be due to the fact that experts working on artificial intelligence are also mostly men, and while that artificial intelligence practitioners, just 22% are women, and also that women were secretaries and assistants. However, we need to make it clear that actually several virtual assistants, such as Google Assistant, have their male counterparts.

Future of AI in art

The only people who could really create art were considered. But this assertion is a little controversial with the emergence of AI. The new artificial intelligence breakthroughs have given him creative strength. AI will create not less impressive masterpieces than those of famous artists. Artificial intelligence has become very impressive and exceptional to compose a screenplay, to make music, or to paint portraits. Take a glance at such an algorithm developed by Edmond Belamy.

Two other examples of artificial intelligence which can create art that cannot be distinguished from those of a person are Google Deep Dream and The Next Rembrandt.

Robots have Features to Heal themselves

You don’t think that even if robots could fix themselves, it’d be much safer, and we haven’t spent too much time searching for the right service company? Ok, maybe it isn’t just a fantasy of piping. The creation of artificial intelligence has allowed robots to repair themselves automatically. It isn’t that you realize that you’re broken, but you can find out that your performance is incorrect and, therefore, can easily fix yourself when needed.

Final Words

So these were some of the most interesting facts about Artificial Intelligence that you need to know about. It can be concluded that AI has a huge impact on today’s world, and it is of great importance.

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Best Applications of Robotics in Modern Times

In industries such as production, entertainment, agriculture, etc., there are several jobs which demand tedious, monotonous work which also takes much precision. The robot is better suited than human beings in such circumstances because they’re accurate, intelligent, and not bored as human beings! Often, work is very risky and uncertain for people, such as space and underwater exploration. Here too, robots will suit better because they’re never tired, as well as a robot won’t be killed! Due to these advantages, almost in every industry, you could imagine, there are several applications for robots. But let us now look at the top applications in these eight sectors.

Security

Imagine if robots are really the security guards? Even the robbers will be frightened! That is why robots are suggested as security officers to protect people because they are not at risk as human safety guards would’ve been. Robot guards and human safety consultants are currently employed together by robotic enterprises. Knightscope is a top-rated company in the United States with autonomous security robots which can provide real-time, operational intelligence to justify the human security guards. These robots could assist in crimes like armed robbery, household abuse, hunger, hitting, theft, and running, etc.

Space Exploration

There seem to be a lot of things in space that astronauts can do very dangerously. Human beings cannot roam all day on Mars to gather ground samples of work to fix a spacecraft when it is deep! Robots are really a perfect option in these cases as there is no possibility of losing human lives. Space agencies such as NASA also use robots and autonomous vehicles to do tasks people cannot do. For instance, Mars Rover is also an autonomous robot traveling on Mars and taking pictures of interesting or significant Martian rock formations and sending them back to earth to NASA scientists.

Entertainment

And in the entertainment industry, robots are indeed a great attraction. Although they cannot precisely be actors and actresses, they could be used for the control of the camera, special effects, etc., behind sets in series or films. They could be used for repeated boredom which is not appropriate as cinema would be a creative industry for human beings after all. Robots still could be used for stunning work, which is very harmful to humans and, in an action movie, looks pretty good. Theme parks like Disney World often use self-supporting robots to increase their customers’ magical experience.

Agriculture

Agriculture seems to be the sector that forms the cornerstone of human culture. Agriculture is nevertheless also a seasonal sector that relies on optimum soil conditions etc. In addition, in agriculture, several repetitive activities are only a waste of farming time and are much more suitable for robotic applications: seeding, control of weeds, harvest, etc. Robots are generally used to collect crops that enhance the efficiency of farmers. Ecorobotix is indeed an illustration of a robot that is used in farms to eradicate weeds. It is fuelled by solar power and could be used with a complex camera system to target and spray weeds.

Health Care

Healthcare has improved a lot from robots. And everything for the better! They could help physicians conduct operations most accurately, use them as prosthetic limbs, provide patients with therapy, etc. There are no limits to the opportunities. The da Vinci robot, which can assist surgeons with complex operations related to the heart, neck, mind as well as other sensitive regions, is one illustration of this. There are many other robotic types of equipment, such as exoskeletons, which could be used to help rehabilitated people after spinal injuries, strokes, etc.

Underwater Exploration

Robots are really a perfect way to explore areas human beings cannot easily access, such as the ocean depths. In the ocean, there is indeed a lot of water depth, which means that people can’t go down, and devices like submarines can also only reach a certain center. A deep submarine is a mysterious place to explore with specially built robots. These robots are remotely controlled and can enter the ocean to capture data and photographs about the water and animal life. These robotics are remotely controlled.

Food Preparation

Wouldn’t want to cook? Do not worry, robots will cook for you and produce full meals! These robot chefs will produce food with hundreds of recipes. Everyone has to select the recipe they need and give the robot all of the ingredients required for this recipe with pre-packed containers. Therefore the robot will cook the food alone. Moley Robotics is indeed a robotics firm that developed a robot kitchen, like a master chef, with just a robot that really can cook! Therefore, don’t worry if you can’t cook food. 

Manufacturing

Throughout the manufacturing sector, there are several repeated and common activities that involve no use of the mind, such as welding, assembly, packaging, etc. Robots can quickly perform these tasks whereas leaving people with a mentally difficult and imaginative job. Those robots could be trained accurately under a person’s supervision and guidance to perform these repetitive, monotonous tasks. This alternative also is the safest way to use unsafe and risky manufacturing methods.

Final Words

You have already seen the numerous robotic applications in various industries. These days, robots are being used for everything, including security guards, doctor helpers, cooks, customer services, and even a warring one-person army. Due to its accuracy and its programming, several other applications of robotics perform different tasks which are hazardous, dull, or tedious for humans. Robots will do all the hard- or impossible physically challenging tasks for humans; however, with the advancements in artificial intelligence, they may even become smarter and cleverer. In summary, robots could support humans perfectly and solve several problems in various industries. Therefore in the future, robots will be seen in every sector, and they will do every work effectively and efficiently.

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Types of Smart Sensors Capable of Improving Agriculture

Agriculture today faces a major challenge to meet the needs of the world population as a whole without depleting the available resources mostly on the planet. Technology and creativity are undoubtedly the much more valued aliens, though they can contribute to more productive agricultural holdings and much more sustainable production systems.

The creation of sensors able to accurately examine the circumstances of the soil and to provide farmers with information could be of great assistance in this regard.

Now we will present you to four types of sensors that you might not be informed of for agricultural purposes.

Iot and Agriculture

Sensors in agricultural operations have been introduced for a long time. However, the issue with the conventional sensor technology approach was that we could not obtain live sensor data. We could then use the sensors to log the information into their attached memory.

Introducing industrial IoT in agriculture allows the use of far more sophisticated sensors. A cellular-satellite network now connects the sensors towards the cloud. This enables us to know the sensor data in real-time and make successful decision-making.

IoT apps have helped farmers track water tank levels in real-time in agriculture to improve efficiency in the irrigation process. In every phase of farming, the progress of IoT technology has resulted in using sensors, such as how long and how much energy a seed takes for a fully grown plant.

The Agriculture Internet of Things has emerged as the second green revolutionary wave. The advantages of IoT adaptation for farmers are double. It helped farmers to reduce cost and increase yields while enhancing the decision-making process for farmers with accurate information.

IoT Application in Agriculture Sector

Smart agriculture is a high-tech, effective framework for sustainable agriculture and food production. That is an application in agriculture of the joint implementation of connected devices and emerging technologies. Intelligent farming mainly depends on IoT to remove the need for farmers’ and farmers’ physical work and therefore to increase production in any way possible.

The Internet of Things has brought significant benefits such as effective water usage, input optimization, and plenty more with recent farming trends depending on agriculture. The enormous advantages have changed, and in recent days, agriculture has become revolutionary.

Smart Farming, based on IoT, enhances the whole system of agriculture by real-time field monitoring. The web of agricultural subjects not just to save farmers time and also minimized the extravagant use of resources like water and electricity by means of sensors and interconnectivity. It monitors different variables such as humidity, soil, temperatures, etc., and provides a direct observation in real-time.

Sensor 1

A sensor that can search from the sky will be the first in the chart of sensors in agriculture.

There are many physical mechanisms in nature that are not seen in plain sight by our restricted human eyes. Parrot launched Sequoia, a mini multispectral sensor capable of tracking the nuances that our eyes cannot notice in the ground, to aid farmers in evaluating the conditions of their field.

Sequoia is a device that can take aerial pictures attached to a drone. It has a 16 MP camera as well as a GPS solar sensor. It consists of two elements. Bathing from the electromagnetic spectrum to ultraviolet or infrared rays that is impossible for people is both multi-spectral and, in other terms, registered. This configuration enables the field to be collected as well, as the sun behavior is compared to the crop state in real-time. With these criteria in mind, farmers may classify drier regions, nutrient-free areas, or plagues.

Sensor 2

The intelligent agricultural sensors are followed by one that monitors cows’ status.

One of the hardest jobs in the primary sector seems to be the management of a dairy farm. Farmers must oversee the production of cows from dusk to late at night to ensure the quality of the milk. However, these habits can now adjust, and while they may proceed to check their stocks’ welfare in the morning, they can also easily make it via their mobile, thanks to the Internet of Things-based HealthyCow solution introduced by SCR Dairy.

We are talking about a collar with moving sensors and microphones which can track the behavior as well as the time of the cows. Whenever the activity increases, for example, the animal’s heat or decreases, that can imply some other kind of health problem, the device sends notifications to the farmer’s smartphone.

This knowledge helps the farmer to improve milk production, decrease the risk of birth or track the health of the cows, thereby saving valuable time and preventing trips to just the facilities in small hours.

Sensor 3

One sensor which senses the atmosphere is another used in the agriculture sector.

Kilimo Salama is a Kenya-based project aimed at reducing the collateral effects of inclement weather on farming throughout the area based on the principle of “healthy agriculture.” The fields are monitored by a linked weather station. Therefore, during times of drought or floods, small farmers would have better access to harvest insurance. This project creates a stable network and enhances an investment in agriculture.

We have already witnessed how technological advances enable growers to become knowledgeable of soil anatomy. In that regard, the pH level of just about any given field can be measured, or the clay seems to be the dominant factor in it can be measured by remote sensors.

This knowledge is extremely important if we are to know how much water drainage or acidity the soil needs to adapt to irrigation as well as the most useful cultivation type.

Sensor 4

Sensors of agriculture can be of considerable help not just in seed tracking or maintenance harvesting but also for seed collection storage. This is the case for BeanIoT, bean-like thumb-like plastic products thrown into grain silos to track its situation while it is processed.

How do they do that? The inbuilt moisture sensors, electronic compass, gyroscopes, and Bluetooth are provided for each plastic bean. The measurements of the temperature, air quality, humidity, gas, altitude, and grain within the silo could be achieved thanks to all of these components. BeanIoT sensors send a feed to a smartphone if irregular values are detected. They stay sleeping to conserve energy the rest of the time. They charge wirelessly as well as the battery lasts 14 months, as per their maker.

Final Words

So these were some of the most important sensors that are very effective in the field of Agriculture.

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