Top-data-science-courses-and-workshops-2022

Top Data Science Courses and Workshops to see (2022)

Why is it important to know Data Science courses and workshops? The most valuable asset of the present and the future is information. We generate data through our searches, consumption, locations, interactions, and other actions that we all have daily on the Internet. 

Information has revolutionized the world since the arrival of search engines like Google and social networks. That is why whoever wants to capitalize on a market must collect data about their customers, but it is necessary to know what to do with it too. 

This is how data science became one of the most decisive disciplines for the commercial area of all industries in the world. Its mix of technology and software development makes the discipline challenges. 

We created a compendium of top Data Science courses and workshops that we consider valuable for anyone interested in data science because of:

✅Have a digital business

✅Plans to have one

✅Is a digital freelancer

✅IT or Marketing Manager 

✅The leader within a company

✅Participate in decision making

✅Or even want a promotion, making the company you are part of more and more PRODUCTIVE.

But first, let’s talk about what is data science?

It is an artificial intelligence technique where large volumes of information are collected and analyzed and then is determined the best way to handle and interpret it.

What is the purpose of data science?

Discover trends, predict the future, and anticipate it with strategic decisions.

This discipline combines software development techniques, computation, probabilities, management, and even new technologies such as machine learning.

It is presumed that specialists in this field will be the most demanded in a few years, along with software developers and marketers.

Suppose you do not want to be one of them, but you are part of a company. In that case, you must know about data science to take advantage of its potential or hire the right person who will take the productivity of your business to stratospheric levels with the help of the data management of your customers.

As we are clear about the importance of knowledge, we continue to move forward with the proposals you can get today in the data science training market. ​⬇️​

Top 5 Data Science Courses and Workshops this 2022

Data Science Specialization – JHU – Coursera

John Hopkins University supports this training.

There are ten introductory courses to data science as a discipline.

You will learn:

The entire data science process, from acquisition to publication.

You will learn about the Github repository to manage data science projects. And perform regression analysis, least squares, and inference using regression models.

You will learn basic concepts, the right questions to ask to drive the process, and the necessary tools. And you will develop a final project to apply all the skills learned by building a data product using real-world data.

In the end, you will be able to use this first project as a portfolio.

Introduction to Data Science for Metis

Although this course is introductory, it requires participants to have basic knowledge of Python and be familiar with the basic concepts of statistics and linear algebra, such as mean, median, mode, standard deviation, correlation, and the difference between a vector and a matrix.

This is a Bootcamp where you will learn the basics of data science, the leading technologies, the principles of machine learning, and even have a simple but practical coding experience.

It is designed for six weeks and is 100% online.

Like the previous one, you will develop a final project, which you can use as a portfolio.

Data Science: Machine Learning

This course is endorsed by Harvard University.

This introductory course is part of the university’s Data Science Professional Certification Program. In it, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.

Its focus is on machine learning under the same logical scheme that data solutions are built.

You will learn about training data and how to use a dataset to discover potentially predictive relationships.

You will also learn about overtraining and techniques to avoid it, such as cross-validation.

The duration is 8 weeks at 2-4 hours per week.

Do you motivated to give it a try?

Introduction to Machine Learning Course

As we mentioned in the previous course, machine learning principles are related to data science. In fact, it is advisable to learn both together to understand the processes better.

Therefore, we did not want to overlook a course on this discipline in our list of recommendations.

You will learn the complete data research process through a machine learning lens. You will be able to extract and identify useful features that better represent your data, some of the essential machine learning algorithms, and how to evaluate the performance of your machine learning algorithms.

This is a free, 10-week beginner course sponsored by UDACITY.

1st steps in Data Science, ML & AI | Free Workshop | Dividev

We could not leave out our Workshop on Data Science, Machine learning, and AI, all fundamental concepts related to the predictive analysis of data and a company’s success.

Our specialists prepared ten videos in which you can learn basic concepts of these disciplines. Application models, technologies, and many valuable tools to start your career as an analyst and data scientist, or even make the right decision about the team you will have in your company.

As we commented before, it is not depreciable knowledge because it represents the present and future productivity of many companies.

To be able to predict your customers’ behavior to offer them solutions.
Anticipate some changes in the industry to make strategic decisions that will help you be more efficient in your processes.

These are just some of the advantages we want you to take advantage of with our Workshop.

You can enjoy it HERE.

Data science applies to all industries without exception.

Imagine being able to predict another pandemic and, this time, being prepared? That’s the power of data science and another concept we’ll look at another time: big data.

We invite you to get trained in the subject with any courses and workshops on data science that we recommend. Once you know about it, you can learn about our offerings and consider them based on your knowledge. We are at your service to support you in this area.

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Before&After: Application of Data Science in the Tourism Industry

Imagine that you can know all the critical data about your ideal client, their interests, pain points, desires, emotional states, searches, etc. Then you interpret this information, and you can predict their response because you build a travel offer according to their current state. 

This guarantees a purchase and, more than that, loyalty because you hit the nail on the head with what they were expecting. 

Although this premise seems to be taken out of a science fiction movie, it is possible thanks to artificial intelligence and data analysis as a solution within this intelligent world of technologies. 

In the tourism industry, affected by the effects of the pandemic, this could mean the difference between recovering in the short or long term. Read on to learn more about how you can turn your business around by applying an innovative data analytics solution.

How can data analytics drive the travel industry and potentially your company?

1. Analyze the GDP, which sectors have contributed to the industry, and to what extent.

2. Analyze the critical actions performed by your competitors (market analysis).

3. Analyze your actions and strategies vs. the results obtained to optimize efforts.

4. Your consumers’ behavior in social networks and search engines.

5. Find more easily the actions taken by governments, tourism offices, and entities involved in your industry that may favor your commercial development or harm you.

6. Statistically analyze your growth or loss

7. Make future projections about the behavior of your market based on past information (it happens from the moment you implement an intelligent data analysis solution).

8. Identify which actions are good (to reinforce them) and which are not (to improve them).

9. Discover new routes, destinations, or travel intentions (users are constantly changing).

10. Identify new services that you can include in your commercial value proposition.

11. If you wish, even forecast data on future pandemics or disruptions in the global status quo to make provisions for them.

Data analysis as a technological solution can provide many answers that even our human mind cannot understand, and it would not be the first time this has happened. All artificial intelligence algorithms are developed to improve themselves as they obtain more information and suggest new trends or discover things we never imagined without us explaining it because it self-manage their intelligence from the data it collects. Sounds interesting, doesn’t it?

You can develop a data analysis solution for your tourism business with our team. Please find out how we can help you.

Success stories of data analytics application in the tourism industry

KAYAK integrated with ALEXA skills

This company currently offers its users the possibility to perform a voice search with simple parameters such as:

Alexa, ask KAYAK where can I go on vacation in October for $1,000?”

In response, that person will be able to track flights, book hotels, search for destinations, and take into account the data that Alexa itself collects about him. That’s the promise of KAYAK.

By providing access to information to your customer, you increase the chances of purchase and get valuable information that you can then use to your advantage.

Airlines such as United Airlines and even airports, such as Amsterdam’s Schiphol Airport, use big data and data analysis to detect fraud and errors in flight allocation, analyze customer behavior and even measure customer satisfaction through the data generated every time they use their services.

This may sound invasive, but it is the opportunity to improve your users’ experience through personalization, which seems to be the critical factor for future success.

Do you want to know how we apply AI and data analytics solutions with our partners?

Let us schedule a no-obligation exploratory meeting if you feel attracted by the results you can enjoy. And if not, you can also contact us to know the scope and even the profit you could generate from implementing an intelligent data analysis solution in your tourism company.

We are sure it will be a before and after.

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Data Science, Artificial Intelligence & Dividev Centrifuge

Dividev works with databases enhancement for several verticals, enriching and adding data by getting information from external sources coming up with thousands relevant data points.
This data is used later for many purposes creating a high and accurate segmentation, and the creation of an ongoing enrichment process and the “Dividev Centrifuge“.

The Dividev’s Centrifuge process includes data science for data preparation, exploratory data analysis of existing and new data (in order to make data more consistent), tidying up the data lake, and creating an automated work plan based on a completeness and consistency score of the listings.

All these techniques and actions help companies to have larger and richer data sets, for many purposes including customer analysis, demand & supply projections, launching more personalized and targeted marketing campaigns, etc. Also all this information could be enhanced with the integration of a larger data set and business partners, creating synergies and enriching each particular media channel, and use artificial intelligence techniques whenever possible.

Dividato is playing a key role in the waves of exponential tech advancements, as Peter Diamandis identifies as current metatrends. For example the disruption of advertising.

As artificial intelligence becomes increasingly embedded in everyday life, your custom artificial intelligence will soon understand what you want better than you do. In turn, we will begin to both trust and rely upon our AIs to make most of our buying decisions, turning over shopping to AI-enabled personal assistants. Your AI might make purchases or influence your customers based upon past desires, current shortages, conversations allowed by the AI system to listen to, or by tracking where your pupils focus on a virtual interface (i.e., what catches your attention). As a result, the advertising industry—which normally competes for your attention (whether at the Superbowl or through search engines)—will have a hard time influencing your AI“.

Diamandis adds that this metatrend is driven by the convergence of machine learning, sensors, augmented reality, and 5G/networks. And Dividato Centrifuge is ready to work on that.

Case Study: For the tourism & travel industry, Dividato has worked for a media & events company in the New York area, where enriched and added data by getting information from more than 20 automated external sources, including names, email addresses, physical addresses of all stakeholders belonging to selected origins. Dividato’s team worked during a short period of time to come up with thousands relevant data points. This data was used later for promotional activities creating a high and accurate segmentation, and the creation of an ongoing enrichment process and the “Dividev Centrifuge”

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The big reset: Data-driven marketing in the next normal

While other organizations may have retreated to mass marketing, those that upgrade their modeling can be far more effective in generating revenue. Here’s what they need to do.

Tap new (and better) data

Precision marketing is only as good as the data behind it. New models with old data are still likely to provide inaccurate results. To hone their insights, leaders in the new normal will take a wide-angle approach to data collection by gathering not only behavioral trends and location-based insights but also third-party analytics on their business, customers, and competitors to complement their in-house customer data. Companies starting this journey are finding the most value in incorporating epidemiological data from government sources and customer-mobility and sales data from third-party providers into their models. Companies that extend their data gathering in these ways can identify upticks in demand and where new customers are coming from, as well as assess which customers in their existing base have increased spending and where lapsed customers have gone.

Before it updated its modeling approach, for example, a retail chain could only tell how many customers it was gaining or losing. The company then decided to pull in cell-phone data to scan changes in their competitors’ net traffic. That analysis showed that many of the customers they were gaining during the pandemic were coming from more expensive, specialty players, while those they were losing were heading to cheaper, larger-format players. On the basis of this information, the retailer transformed its onboard and churn-prevention campaigns. They sent emails advertising higher-end offerings to customers transitioning from specialty stores while touting bargain-oriented products to value-oriented customers at risk of churn.

Robust data can also allow companies to generate better competitor insights.

By comparing third-party assortment, sales, and promotional data to their own figures, for instance, marketers can evaluate the strength of different value propositions and see which elements resonate with different groups of customers. They can then provide these groups with tailored messaging, content, and offers.

Invest in tech that learns at scale

The increased uncertainty in the new normal requires marketers to get better at testing and faster at reacting. A more agile operating model is a key element in this, but it is also increasingly necessary to work with technology that learns at scale. This requires developing technology capabilities that can read and interpret signals of consumer intent and consumer responses to marketing messages and then feed them back into the marketing engine so it can learn what works and what doesn’t.

Marketers who really push the limits are using artificial intelligence (AI) to monitor campaigns and interrogate responses at a detailed level, to learn not only what works and what doesn’t but for which segments, at what times, and over which channels—and then to adjust their strategy based on those insights. Deriving those specific insights using standard analytics might take the average marketing organization several days. But AI-enabled monitoring can do this in minutes, sometimes seconds.

For example, a consumer services company launched consumer-retention campaigns as communities came out of lockdown. Their customary analytics, which could only assess campaigns in the aggregate, was only marginally effective. However, the organization piloted a new AI engine that could look deeply enough to evaluate responses at the core base statistical area (CBSA), which showed that the campaign was highly effective in specific niches with similar economic and epidemiological profiles. This AI engine will identify how the campaign’s performance patterns evolve, allowing marketers to configure the system so that nightly AI-driven analytics feed directly into the campaign’s targeting logic. This and similar campaigns are a crucial element in a broader data-driven marketing program that has helped the company increase its rate of testing more than fivefold.

Two keys to success: Investing savings and being agile

In order to derive value from these upgraded models, two actions are crucial.

Generate savings to invest in tech

While some companies are simply cutting budgets and retrenching across the board, others are finding it can be more beneficial to reduce spend in unproductive areas and reallocate the savings—as much as 10 to 20 percent of the overall budget, in some cases—into analytics. This requires a thorough but fast reevaluation of all marketing spend to see how the COVID-19 environment has affected ROI. Event sponsorships, traditional TV advertising, and programmatic display based on outdated terms are just a few areas where marketing performance is likely to have shifted significantly. One apparel retailer, for instance, found that the effectiveness of paid search has diminished sharply during the crisis, while social-media activity has been far more productive. Marketing leaders can free additional investment by also reusing and repurposing existing assets. The savings can then be redeployed to fund data-driven growth programs.

Deploy agile marketing in a remote setting

Agile practices are effective in allowing marketing teams to test consumer behaviors and react quickly to changes. While traditionally, agile teams were thought to perform best when working in the same place, the exigencies of the pandemic have required this approach to be rewired for remote work. Leading companies are converting physical war rooms into virtual ones, creating additional points of contact to support adherence to agile protocols (such as sprint check-ins by video, for example) and the use of collaboration tools. The best companies have gone a step further by integrating some of their vendor teams into their remote practices, including working with IT to create shared tools and compatibility guidelines to account for vendors’ different technologies.

Budgeting and operating practices need to be continually reviewed to support this remote agile model. Instead of quarterly or semi-annual planning sessions, marketing leaders should assess performance monthly to ensure that funding and resources are aligned with the biggest opportunities.

Organizations that prioritize their precision-marketing efforts can turn the COVID-19 crisis into a time of transformation. By capturing new data, searching for new behavioral relationships, and enabling rapid experimentation, marketers can seize granular growth opportunities and enter the recovery with significantly greater ROI and resilience.

Have questions on how to apply Data Driven Marketing principles?

Meet how our software development, Machine Learning and Data Science services can help your business:

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5 Ways Businesses Can Use AI to Grow

Artificial intelligence can help with more than just security. The power and promise of AI for businesses keeps growing, and many of them can look towards artificial intelligence for inspiration and solutions to the most common problems they have. Artificial intelligence is already a part of your everyday lives, from social media feeds, song and movie recommendations, driving directions, and even the voice on your phone assistant are all examples of how artificial intelligence already has a role in our daily lives.

1. Improve Customer Services

With AI slowly getting into everyday use, it can help with major business improvements. By using a virtual assistant program, businesses can get real-time support to users and significantly improve their customer support.

With their usual workload, sales and customer support teams have a lot to work on. But, AI has made a lot of changes and improvements to helping people by tackling manual and tedious tasks. The automation of these tasks will allow people to focus on more important projects and lighten the workload.

Customer support representatives can be sure that their clients get all the necessary information they want and need with the help of AI. Artificial intelligence can maximize the use of a product or service a business offers. And artificial intelligence can also help with follow-ups by automatically scheduling any follow-up email that can help companies be sure that there are no leads that have not been contacted.

Apart from these tasks, AI can help businesses customize their websites based on how customers engage and behave online. Buyers want to see tailored experiences for any interaction they have with a business. And because of that, it is important to tailor your website towards potential customers. And you can do that with the help of AI tools that can automatically update website messaging based on the users that view the page.

2. Automate and Optimize Workload

With the help of machine learning, retails and other businesses can help with better inventory management. Machine learning can help automate any refilling requests and even optimize the supply chain with a breeze.

Artificial Intelligence can help with improving the maintenance and safety of the equipment a business has. It can improve the maintenance schedules that will offer better control of the manufacturing and transportation sectors.

By collecting and analyzing data, with the help of machine learning algorithms, businesses can categorize work, optimize logistics, automatically route service requests and improve the execution of manual tasks for any industry.

3. Predict Performance

The application of artificial intelligence in business can help predict performance and user behavior. Specific AI tools can help identify patterns that can potentially disrupt your business, like IT outages. There are tools that can also help determine when you can reach certain goals you set. You can watch and predict when you can reach a certain response time to help desk calls.

And with the help of different ML algorithms, a business can analyze patterns of online behavior and use this data to serve tailored product offers or target appropriate adverts. AI can even help a business forecast the revenue it will generate, which can help companies understand what will help them meet their quarterly and yearly goals.

4. Analyze Data

With many improvements in network and storage technology, it’s easy to collect data. However, just data is nothing without analyzing it. With high amounts of data, it can be very time-consuming to analyze big amounts of data one by one. That’s where AI can help. Machine and deep learning algorithms can help analyze any large amounts of data and interpret it.

So far, AI-powered systems have been used to analyze data from hundreds of sources to offer predictions and information about what works and what doesn’t. And it has helped unify data across platforms to put all customer data together into a single place.

5. Improve Marketing and Advertising

Businesses can use artificial intelligence to improve their marketing and advertising efforts. By adding automation to the marketing processes, a business can increase its presence and land more sales. A business can customize marketing and sales informationand allow AI-based applications to handle routine tasks to allow a better experience for consumers.

By using AI-based applications, businesses can start handling routine tasks. It can automate any routine marketing task and save time to focus on other things. And artificial intelligence can effectively track any user behavior on websites or social media. It can also deep dive into data about customers and clients to give predictions about product development, consumer preferences, and marketing channels.

With the help of machine learning, a business can get help with price-optimization for various markets. There are platforms that can leverage data about competitors, consumers, and suppliers, and use that data to automatically create different pricing models for individual market segments. This AI-based approach can contribute to and optimize the profit margins of a business.

Make Use of AI Technologies For Your Business

There are a lot of ways artificial intelligence can help businesses improve different aspects of their business and tasks that need to be done. Artificial intelligence will allow businesses and people to focus on important tasks, while AI takes care of their routine and time-consuming tasks.

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Role of big data with predictive analytics in the retail market

Role of big data with predictive analytics in the retail market

The ecosystem of business has turned out to be extremely complicated, which makes the sustenance difficult on a competitive landscape for the retailers.
Retailers need to keep developing, innovating, and diversifying. It can help them in understanding the customer demands better and fulfill their expectations, while providing them an elevated customer experience. It makes the operations of retail extremely difficult for their survival, as well as stops attracting new customers.

Nevertheless, disturbing trends related to the retailers and the customers have resulted in a massive explosion of data, which, when processed and evaluated, can help the retailers with a sizeable opportunity to gather valuable insights.

Understanding customer behavior can help the retailers to leverage that information in better decision-making.

On the other hand, processing such a large set of data has become a great challenge for companies now.

As per Gartner, data volume is ready to rise by 800 percent in the coming years, having 80 percent of unstructured data within it. In order to make sense of the capital of big data, retailers need to have a robust data management solution that can lend a hand in retrieving and processing data from multiple places. It will help the retailers need to have a robust data management solution that can lend a hand in retrieving and processing data from multiple places.

It will help the retailers to draw real-time insights for quick decision-making, as well as, generate the actual business value. Predictive analytics has evolved as a clear solution for every data faced by businesses. By predicting the customer requirement based on post-interaction, historical, and real time analysis of big data, it can be satisfied quickly and efficiently.

The blend of machine learning and artificial intelligence with predictive analytics helps in bringing better accuracy and insightful data. Leveraging a predictive analytics solution can help businesses to make their sales and marketing teams more practical by allowing them to access data such in a precise way. It can enable the marketing and sales teams to resolve, as well as determine a customer’s potential lifetime value.

Furthermore, predictive analytics is beneficial when it comes to identifying issues and trends that have a significant impact on business operations. It can help the retailers to predict when and why the customers might leave the brand behind. Such information will allow the businesses to take necessary actions to improve customer experience and flawlessly serve their expectations.

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How big data impacts the finance and banking industries

How big data impacts the finance and banking industries

Did you know that big data can impact your bank account, and in more ways than one? Here’s what to know about the role big data is playing in finance and within your local bank.

Nowadays, terms like ‘Data Analytics,’ ‘Data Visualization,’ and ‘Big Data’ have become quite popular. These terms are fundamentally tied predominantly to matters involving digital transformation as well as growth in companies. In this modern age, each business entity is driven by data. Data analytics are now very crucial whenever there is a decision-making process involved.

Through this tool, gaining better insight has become much easier now. It doesn’t matter whether the decision being considered has huge or minimal impact; businesses have to ensure they can access the right data to move forward. Typically, this approach is essential, especially for the banking and finance sector in today’s world.

The Role of Big Data

Financial institutions such as banks have to adhere to such a practice, especially when laying the foundation for back-test trading strategies. They have to utilize Big Data to its full potential to stay in line with their specific security protocols and requirements. Banking institutions actively use the data within their reach in a bid to keep their customers happy. By doing so, these institutions can limit fraud cases and prevent any complications in the future.

Some prominent banking institutions have gone the extra mile and introduced software to analyze every document while recording any crucial information that these documents may carry. Right now, Big Data tools are continuously being incorporated in the finance and banking sector.

Big data has numerous perks relating to the financial and banking industries. With the ever-changing nature of digital tech, information has become crucial, and these sectors are working diligently to take up and adjust to this transformation. There is significant competition in the industry, and emerging tactics and strategies must be accepted to survive the market competition.

Using big data, firms can boost the quality and standards of their services.

Perks Associated with Big Data

Analytics and big data play a critical role when it comes to the financial industry. Firms are currently developing efficient strategies that can woo and retain clients. Financial and banking corporations are learning how to balance Big Data with their services to boost profits and sales. Banks have improved their current data trends and automated routine tasks. Here are a few of the advantages of Big Data in the banking and financial industry:

Improvement in risk management operations

Big Data can efficiently enhance the ways firms utilize predictive models in the risk management discipline. It improves the response timeline in the system and consequently boosts efficiency. Big Data provides financial and banking organizations with better risk coverage. Thanks to automation, the process has become more efficient.Through Big Data, groups concerned with risk management offer accurate intelligence insights linked to risk management.

Engaging the Workforce

Among the most significant perks of Big Data in banking firms is worker engagement. The working experience in the organization is considerably better. Nonetheless, companies and banks that handle financial services need to realize that Big Data must be appropriately implemented. It can come in handy when tracking, analyzing, and sharing metrics connected with employee performance. Big Data aids financial and banking service firms in identifying the top performers in the corporation.

Client Data Accessibility

Companies can find out more regarding their clients through Big Data. Excellent customer service implies outstanding employee performance. Aside from designing numerous tech solutions, data professionals will assist the firm set performance indicators in a project. It will aid in injective analytic expertise in multiple organizational areas. Whenever there is a better process, the work processes are streamlined. The banking and financial firms can leverage improved insights and knowledge of customer service and operational needs.

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How Artificial Intelligence and Software can defeat COVID-19

We are facing one of the worst pandemics the world has suffered in recent decades, and yet we have never been better prepared to stop an illness. And not only because we have the best doctors or brilliant scientists on our side, but because for the first time technology is going to become a fundamental ally. The fact is something called “Artificial Intelligence” and that it has already been shown to work is one of our best weapons. But how can AI help us deal with a virus? Here are some hints.

AI to identify, track and prevent future outbreaks

The better we are at identifying and following the “movements” of the virus, the better we will be at fighting it. By analyzing news sources, content published on social networks or publications made by different governments, we will first learn to detect new outbreaks of the disease, before we can act. One of the most advanced companies in this field is the startup BlueDot, whose AI algorithms were in fact able to detect the presence of the virus in Wuhan several days before it was confirmed by Chinese authorities.

AI to aid in the diagnosis of the disease

Another key to stopping the virus is being able to carry out early tests, so that the first symptoms can be directly related to those of the disease. Companies like Infervision are working in this field with the Chinese giant Alibaba.

Thanks to the use of Big Data, the patient’s history, the community in which he is, the initial symptoms he presents, etc. can be determined with a success rate greater than 90% if that person has already been infected or is willing to have it, so treatment procedures can be started even before obtaining the results from medical laboratories.

AI to identify affected individuals

It is perhaps the most controversial use of this technology, but it works and it is very useful. This solution aims to develop or adapt facial recognition systems to be able to identify on the street or in closed spaces (a shopping center for example), if a person shows external signs of being able to suffer from this disease. By crossing this facial recognition as the person’s background and all available information about the area in which they live, a reasonable probability estimate can be made.

A similar technology is the one included in the “smart helmets” worn by policemen in Sichuan province and that allows them to identify people with fever; or the already famous smart code that has been assigned to each citizen of the affected provinces in the Asian country and that thanks to the use of Big Data identifies the potential risk of suffering the disease based on the person’s travel history.

Big data is presented as a tool to help doctors and patients overcome diseases or pandemics

Asian discipline and its conviction for digital technology have led big data to be the ideal weapon to beat COVID-19. The Asian giant, China, has put its entire technological arsenal at the service of health. With more than 1,300 million inhabitants, the penetration of smartphones among its population is high. The easiest way to control citizens is through an application.

In it, citizens must fill in some personal data, explain if they have any symptoms or if they have been somewhere affected by the epidemic for the last fourteen days.

The system generates a QR code according to the level of risk you have of contracting the infection. In addition, it also records the location of the users, so that the authorities can know at any time if someone infected is moving freely around the city.

Use of COVID-19 technology in South Korea

Another country that has used the technology to combat the coronavirus has been South Korea. Since the outbreak began in China, South Korea immediately implemented the application that detects by means of a QR code whether a person is infected or not. In this way they can monitor people the 14 days of quarantine daily.

At airports, authorities made people download the app immediately, before leaving the scene.

Despite being the main focus of those affected outside China, in South Korea the virus has advanced more slowly, and its mortality is very low compared to other countries. Its success is due in large part to such application and accounts for how the technology paid off against the coronavirus.

Using this application, which allowed them to monitor visitors from dangerous areas, was so useful that the government used it to manage the quarantine of more than 30,000 people spread across the country.

Being able to control patients, through this application, at all times during the day and without mobilizing medical personnel was very helpful. In addition, the GPS location ensures that people do not leave the assigned place of isolation.

How DiviDev is already implementing these types of solutions?

Along with municipal and other government authorities in the central region of Argentina, we are already contributing our AI capabilities by developing algorithms and applications in order to mitigate the impact and progress of this disease, helping these institutions with data analysis and predictions to assist in decision-making and execute them before possible overflows of public infrastructure. This prediction will help create field hospitals in a timely manner; and with the necessary dimensions on what is predicted. In addition, it allows planning the affected health personnel based on these results.

In these solutions, we use time series forecasting algorithms for the prediction in timelines “take the current cases of: suspects, positives, close contacts, deceased and recovered” and generate a prediction for the next 12 days.

In addition, we are working on other specific software solutions such as the development of mobile applications to combat Coronavirus, similar to those successfully implemented in South Korea (previously mentioned), in order to track infected patients and prevent spread in the region.

DiviDev can help you apply artificial intelligence to combat COVID-19

DiviDev offers you end-to-end solutions or complete and extended teams that can be easily integrated and work hand in hand with you to offer highly valuable features of your product.

We have certified experts who can help you explore the best artificial intelligence opportunities to combat COVID-19 or help companies in their transformations caused by this change in habits and routines revolutionized by this pandemic. Likewise, it can help capture new markets, increase revenue, improve profitability, and expand brand reach. As an end-to-end software development provider, we recognize the promise of this intelligent game-changing platform integration, designed to maximize internal efficiency, analyze data effectively, and improve customer experience.

DiviDev is ready to serve clients interested in taking advantage of this technology.

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