Zusatz-Studium „Data Science and Big Data“ an der TU Dortmund

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Jetzt anmelden für das weiterbildendes Studium „Data Science and Big Data“ an der Technischen Universität Dortmund!

Im Februar 2022 startet das berufsbegleitenden weiterbildende Studium „Data Science and Big Data“ an der Technischen Universität Dortmund zum 6. Mal.
Renommierte Wissenschaftlerinnen und Wissenschaftlern vermitteln Ihnen die neuesten datenwissenschaftlichen Erkenntnisse und zeigen, wie dieses Wissen praxisnah im eigenen Big-Data Projekt umgesetzt werden kann. Von der Analyse über das Management bis zur zielgerichteten Darstellung der Ergebnisse lernen Sie dabei Methoden der Disziplinen Statistik, Informatik und Journalistik kennen.

Das weiterbildende Studium richtet sich an alle Personen, die über einen natur-  oder ingenieurwissenschaftlich/ statistische Studienhintergrund verfügen oder aufgrund ihrer mehrjährigen Berufserfahrung mit Fragestellungen zum Thema Datenanalyse vertraut sind.

Mögliche Berufsgruppen sind:

  • Data Analyst
  • Consultant/ Unternehmensberater
  • Business Analyst
  • Software-Entwickler

Das weiterbildende Studium umfasst 10 Veranstaltungstage über eine Dauer von 10 Monaten (Kursabschluss: November 2022). Die Kosten betragen 6.900 € (zahlbar in 3 Raten). Bewerbungsschluss ist der 29. November 2021. Weitere Informationen und Hinweise zur Anmeldung finden Sie unter: https://wb.zhb.tu-dortmund.de/zertifikatskurse/data-science-and-big-data/

Bewerbungsformular für Zusatzstudium an der TU Dortmund

Bewerbungsformular (Download)

 

Bei Fragen können Sie sich gerne an den zuständigen Bildungsreferenten Daniel Neubauer wenden: daniel.neubauer@tu-dortmund.de oder 0231/755-6632

7 Ways To Advance Your Data Science Knowledge and Expertise

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As a data scientist, your knowledge and expertise are what powers industries. Businesses of all sectors of the economy now rely on data to inform their business processes. As many as 53% of companies have already adopted big data analytics, highlighting the upward trend in data science within the private sector.

Businesses rely on data scientists to stay competitive facing in this market. But how can you advance your data science knowledge and expertise to bring the most value to your work?

These seven strategies will help you build your resources and improve your opportunities to grow.

1. Recognize the Need for Growth

It may seem disheartening at first to realize that there is no end to the progress you can make in honing your data science skills. There is simply too much to master in just a few years. However, what this really means is that there is no end to the progress and advancement you can make as a data scientist.

Consider the breadth of what there is to know. Skills to master include probability, new programming languages, data visualization, data intuition, and so much more. Recognize the scope of your field to open the door to learning opportunities in data science.

2. Brush Up on the Latest Trends

Your opportunities as a data scientist are largely dependent on how well you can utilize new software and data analytics trends. Modern data analytics relies on artificial intelligence and machine learning processes to drive insights with unprecedented detail. Meanwhile, data communication and storage platforms like blockchain are emerging to supplement data management infrastructures.

An awareness of these modern developments paired with basic general knowledge and qualifications will be key to getting hired as a data scientist in 2021 and beyond. As companies across industries look to pivot to new tech and competitive data strategies, it is more important than ever to keep abreast of the latest data science trends.

3. Enroll in Data Science Bootcamps

Data science is a constantly changing field, driven by technological innovation. At the same time, the breadth of opportunities that exist in a tech field invite career flexibility. Data scientists can make the most of these advancement and flexibility opportunities by enrolling in boot camps and training courses designed to fill in skills gaps.

These programs cover a range of topics within the field of data science. No matter your level of expertise and education, engaging in supplemental training can help you advance your expertise and bring value-building benefits to your role as a data scientist.

4. Look for Guidance Online

Because of the increasingly virtual nature of all kinds of work and education, opportunities for data science growth may be better sought out online. There are many ways you can go about increasing your data science expertise on a virtual platform. From finding a mentor through social media like LinkedIn to participating in training courses crafted by other data science professionals, you can expand your knowledge base.

First, however, ensure that you have a productive workspace at home that will allow you to learn and grow while staying motivated. This means setting up a home office to accommodate the virtual shift, complete with a comfortable chair and desk set up to avoid neck strain and health problems.

With virtual guidance in a productive environment, you can advance your expertise to secure the value of your position.

5. Expand Your Horizons

Data science is a multifaceted arena. The role of a data scientist typically consists of harnessing and categorizing raw data to draw out useful and predictive insights. Meanwhile, other positions in analytics and IT lend to more powerful data results.

Customer analytics, for example, is another subset of data science that involves harnessing information to describe and predict customer journeys. This entails focusing on customer demographics and behaviors to assemble more carefully targeted buyer personas, which can then be used to increase customer engagement and conversion rates.

Through broadening your data skills to account for areas like customer analytics, you can advance your professional opportunities.

6. Let Your Passions Inspire You

Every data scientist has a reason they got into their field. Your passions and inspirations can inform new avenues of exploration into the many designations surrounding data science. For example, big data analysts, machine learning specialists, and data visualization experts all play vital roles in modern business.

Finding your niche and specialization can come down to what drove you into data science in the first place. Perhaps you have a talent for creating comprehensive visuals that expertly summarize the point you want to be taken from your graphic. Alternatively, diving deep into the ins and outs of algorithmic functions may be what inspires you most.

Explore your passions and commit to a lifetime of learning and growing.

7. Never Stop Improving

With rapid technological change, data scientists must maintain their awareness of new systems and processes at all times. Innovations in AI, for example, have created a skills gap in the market. Eighty percent of business leaders say that lack of talent is the biggest obstacle in AI implementation.

For data scientists, closing this skills gap can be a simple matter of improving your technological training over time. Learning how machine learning functions, for example, can assist in your application of this tech to increase the value you add to your business.

Never stop improving through new courses and credentials that explore changing technology and how these changes affect the world of data science. With a commitment to lifelong learning, your skills as a data scientist will never go out of vogue.

These seven strategies can help you formulate a plan to expand your expertise into new territory, leading to new opportunities and a lucrative financial future.

Data Security for Data Scientists & Co. – Infographic

Data becomes information and information becomes knowledge. For this reason, companies are nowadays also evaluated with regard to their data and their data quality. Furthermore, data is also the material that is needed for management decisions and artificial intelligence. For this reason, IT Security is very important and special consulting and auditing companies offer their own services specifically for the security of IT systems.

However, every Data Scientist, Data Analyst and Data Engineer rarely only works with open data, but rather intensively with customer data. Therefore, every expert for the storage and analysis of data should at least have a basic knowledge of Data Security and work according to certain principles in order to guarantee the security of the data and the legality of the data processing.

There are a number of rules and principles for data security that must be observed. Some of them – in our opinion the most important ones – we from DATANOMIQ have summarized in an infographic for Data Scientists, Data Analysts and Data Engineers. You can download the infographic here: DataSecurity_Infographic

Data Security for Data Scientists, Data Analysts and Data Engineers

Data Security for Data Scientists, Data Analysts and Data Engineers

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Infographic - Data Security for Data Scientists, Data Analysts and Data Engineers

Infographic – Data Security for Data Scientists, Data Analysts and Data Engineers

Role of Data Science in Education

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Data science is a new science that appeared thanks to a lot of reasons. The first reason is that nowadays, we have enough capacity to gather data and later work with it. The second reason is that society accumulates a lot of information every minute, and gadgets can save and then send it to data centers without any communication between people. But saving data is just one step in the world of science. The main task is how to analyze and show the results and later make a conclusion and prognoses. A team of online essay experts from a professional academic writing company SmartWritingService.com say that requests for academic papers for data science research topics increase extremely. It happens because data science analysts’ knowledge is useful in a lot of spheres, and the demand for such specialists is very high. Data science is an important part of sociology, political forecasting, the theory of games, statistics and others. Students need to study it and use it for future research. That’s why the universities added the courses of big data to be modern and meet requirements. Let’s try to discover the role of data science in education to make your own conclusion about its importance.

Why is data science necessary and how to become good in it?

The improvement of the studying process.

All students are different. They use different skills for studying and perceive information differently according to a lot of nuances. For some of them, the best way of getting information from lectors is listening without interruption. Other students prefer discussion during lectures. Some prefer to make notes. Others like to listen carefully and make notes later using the audio version of the lecture. Every group is different but has the same goal, and this goal is to absorb as much information as possible. The best assistant for this goal is data science that will show the teacher the best ways of communicating with students.

Using big data for personal needs. 

Have you ever thought that every one of us is a data scientist? We all use data, analyze it, and act according to conclusions. For example, shopping. Every time you go to the grocery, you notice how many people are there and how long the line is. When you plan your next shopping, you make a prognosis according to that data — the time you need to spend in the market and make a decision if it is optimal to go right now or it is better to visit the shop later when it is almost empty. The same thing works when we talk about studying. According to your observation and experience (that are both data), you make a conclusion on how much time you need to spend on every task.

Learning data science as an additional course. 

To know data science as an additional profession nowadays is very helpful. For the employer, it will be a bonus that can be a decisive factor. The skill to analyze is essential for every profession and helps to understand the market now and necessary for sales. The hardest thing for a data scientist is to ask the right questions for collecting data, and if you are good at it, your salary will increase immensely.

How to become a data science specialist?

Big data and artificial intelligence (AI). The importance of development. We believe that AI is the future of studying. First of all, the machine can collect the information and repeat it as much as the student needs. It is studying with the group, and the quality of communication grows rapidly. The base for machine learning in AI is data science. The analysis of data gives the set of possible reactions and actions to AI that can be changed or improved according to new data that was processed by AI. But from the beginning, AI is a huge set of data. It consists of reactions to life situations, speed and timbre of the voice of the interlocutor, country, the hour of the day, and a lot of other data that finally lead to the reaction of AI to the situation. The development of AI is a question of time, and it will help us to move faster in all spheres of life.

Can we ignore data analytics and don’t take a part in it?

The only way to ignore data science is to throw away all gadgets and become citizens of the wood cabin. And even this step won’t help. Those interested in the amount of population of people who live in the woods will be happy to add you to their list and analyze your +1 using data science technology. Every time you buy bread or don’t buy something on the internet, you are counted. Later they will analyze why you became or not their customer and save for statistics you age, sex, country of request, and all other parameters they can catch. We can only accept this reality and try to use it to our needs.

Don’t be afraid to become a subject for data science. It doesn’t affect your privacy a lot because there are billions of us, and we are only one point for statistics. Thanks to such analytics, scientists can make better specific offers and content for you. On the one hand, it is a kind of manipulation, but it saves time and resources for research from another hand. Use it to make your life more comfortable but remember that there are no coincidences when we talk about data.

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Zertifikatsstudium „Data Science and Big Data“

Jetzt bewerben für das Zertifikatsstudium „Data Science and Big Data“ an der Technischen Universität Dortmund 

Im Februar startet das erfolgreiche berufsbegleitende Zertifikatsstudium „Data Science and Big Data“ an der Technischen Universität Dortmund zum fünften Mal.
Renommierte Wissenschaftlerinnen und Wissenschaftlern vermitteln Ihnen die neuesten datenwissenschaftlichen Erkenntnisse und zeigen, wie dieses Wissen praxisnah im eigenen Big-Data Projekt umgesetzt werden kann.
Von der Analyse über das Management bis zur zielgerichteten Darstellung der Ergebnisse lernen Sie dabei Methoden der Disziplinen Statistik, Informatik und Journalistik kennen.

Das Zertifikatsstudium richtet sich an alle Personen, die über einen natur-  oder ingenieurwissenschaftlich/ statistische Studienhintergrund verfügen oder aufgrund ihrer mehrjährigen Berufserfahrung mit Fragestellungen zum Thema Datenanalyse vertraut sind.

Mögliche Berufsgruppen sind:

  • Data Analyst
  • Consultant/ Unternehmensberater
  • Business Analyst
  • Software-Entwickler

Das weiterbildende Studium umfasst 10 Veranstaltungstage über eine Dauer von 10 Monaten (Kursabschluss: ca. November 2021). Die Kosten betragen 6.900 € (zahlbar in 3 Raten). Bewerbungsschluss ist der 4. Dezember 2020. Weitere Informationen und Hinweise zur Anmeldung finden Sie unter: http://www.zhb.tu-dortmund.de/datascience

Bei Fragen können Sie sich gerne an den zuständigen Bildungsreferenten Daniel Neubauer wenden: daniel.neubauer@tu-dortmund.de oder 0231/755-6632.

Hinweis:

Ergänzend bieten wir einen R-Basis- und R-Vertiefungskurs an. Wenn Sie sich für das Zertifikatsstudium bewerben und für einen Kurs bzw. beide Kurse, erhalten Sie pro R-Kurs einen Rabatt von 250 €. Weitere Informationen finden Sie unter: https://dortmunder-r-kurse.de/kursangebot/

Wir behalten uns vor, das weiterbildende Studium je nach Entwicklungen der Corona-Pandemie als Online-Kurs durchzuführen

Online-Kurse zur Statistiksoftware R

R – ein unverzichtbares Werkzeug für Data Scientists. Lassen Sie sich auf den neusten Stand in der Open Source Statistiksoftware R aus der modernen Datenanalyse bringen.

Zielgruppe unserer Fortbildungen sind nicht nur Statistikerinnen und Statistiker, sondern auch Anwenderinnen und Anwender jeder Fachrichtung aus Industrie und Forschungseinrichtungen, die mit R ihre Daten effektiv analysieren möchten. Sie erwerben durch die Teilnahme Qualifikationen zur selbstständigen Analyse Ihrer eigenen Daten sowie Schlüsselkompetenzen im Umgang mit Big Data. Dafür bieten wir den R-Basiskurs und den R-Vertiefungskurs im November als Online-Veranstaltungen an.

Termine:

R-Basiskurs:  4. – 6. November (jeweils 9:00 – 13:00 Uhr) – Der Kurs richtet sich an Anfänger ohne Erfahrungen mit R sowie an Nutzer mit rudimentären oder eingerosteten R-Wissen. Entsprechend sind keine Vorkenntnisse über R notwendig. Zusätzlich zu den 3 Online-Tagen erhalten die Teilnehmenden Zugang zu 1,5 Stunden Videomaterial.

R-Vertiefungskurs: 17. – 20. November (jeweils 9:00 – 13:00 Uhr) – Der Vertiefungskurs richtet sich an fortgeschrittene R Nutzer sowie Absolventen des Basiskurses. Er ist ideal für Mitarbeiter aus Unternehmen, die ihre Analysen effizient mit R durchführen möchten.

Weitere Informationen zu den Inhalten und zur Anmeldung finden Sie unter: https://dortmunder-r-kurse.de/kursangebot/

Bei Fragen können Sie sich gerne an den zuständigen Bildungsreferenten Daniel Neubauer wenden: daniel.neubauer@tu-dortmund.de oder 0231/755-6632.

Data Science – A Beautiful Data Driven Journey

Data Science is a profession related to processing algorithms and extracting deep insights from raw data. It depicts the importance of data and how it can be used in business and to make IT strategies. For recognizing the new ventures available in the market, identifying the patterns and to make better business decisions, data science is of utmost significance.  It is the duty of data scientists to convert raw data into relevant business information. They hold a center stage in developing the data products by carrying out experiments, analyzing them by using scientific methods and using their skill set. Spotting the growing trends and capitalizing on it before the competition to gain advantage.

TRAITS REQUIRED FOR DATA SCIENCE:

Data Scientists are not born intellectuals; they continuously work to gain all the skills expected by the companies as the demand surpasses the supply of applicants. Here are a few skills of data scientists:

  • Curiosity and Intuition to identify the hidden meaning of data and able to visualize.
  • Need to have leadership skills and have a business savvy mind to identify risks and opportunities.
  • A bachelor’s degree in math, IT, statistics along with a letter of recommendation which will help in knowing your acquired range of knowledge.
  • Specialized skills in machine learning, clustering and segmentation, exploration of data, Statistical research which helps in finances and increasing the profits of companies including modeling.
  • Familiarity and strong hold with programming languages such as hadoop, python, perl, R, etc.

BENEFITS OF DATA SCIENCE:

There are many advantages depending on the aim and interest of the company. Sales and Marketing departments, for example collect information from a particular industry and determine which products interest the customer the most and recommend for their production, be it online shopping goods, some online series or which shipment companies are best. They also help in detection of bank fraud. Data Science currently is a raging industry with well paid professionals. The amount of knowledge acquired through this course makes it a bonus for a better and lucrative career.

APPLICATIONS OF DATA SCIENCE:

Data Science has become a significant field in almost all sectors ranging from healthcare, internet searches, e-commerce sites, cell phones by increasing the features. By making use of statistical measures they predict the future events and try to avoid them by giving optimal solutions. Speech recognition has made it easy to search information or do stuff without typing the best eg being google voice, siri. learn data science training in hyderabad

ROLES OF DATA SCIENTIST IN THE INDUSTRY:

This course is a boon for aspirants who wish to build a career in: Data Science, Machine Learning, Data Visualization, Business Intelligence, Big data, etc. This course is a combination of knowledge and money providing both these aspects in abundant measure. There are many boot camps and courses that provide certifications and provide you with the skills. A data scientist must have enough business domain expertise to analyze the risks, profits and achieve the department goals.

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Data Science is an amazing course enriching your education bank..If you are thinking how to learn data science then some of the best online data science courses are available to give a start to your incredible journey filled with incredible knowledge learning experience.

Click here for more about the data science course in Bangalore.

Zertifikatsstudium „Data Science and Big Data“ 2021 an der TU Dortmund

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Komplexe Daten aufbereiten und analysieren, um daraus zukünftige Entwicklungen abzulesen: das lernen Sie im berufsbegleitenden Zertifikatsstudium „Data Science and Big Data“ an der TU Dortmund.

Jetzt bewerben!

Data Science & Big Data 2021

Die Zielgruppe sind Fachkräfte, die sich in ihrer Berufspraxis mit Fragestellungen zum Thema Datenanalyse und Big Data befassen, jedoch nun tiefergehende Kenntnisse in dem Themenfeld erhalten möchten. Von der Analyse über das Management bis zur zielgerichteten Darstellung der Ergebnisse lernen die Teilnehmenden dabei Methoden der Disziplinen Statistik, Informatik und Journalistik kennen.

Renommierte Wissenschaftlerinnen und Wissenschaftler vermitteln den Teilnehmerinnen und Teilnehmern die neuesten datenwissenschaftlichen Erkenntnisse und zeigen, wie dieses Wissen praxisnah im eigenen Big-Data Projekt umgesetzt werden kann.

Die nächste Studiengruppe startet im Februar 2021, der Bewerbungsschluss ist am 2. November 2020. Die Anzahl der verfügbaren Plätze ist begrenzt, eine rechtzeitige Bewerbung lohnt sich daher.

Nähere Informationen finden Sie unter: http://www.zhb.tu-dortmund.de/datascience

Einführung und Vertiefung in R Statistics mit den Dortmunder R-Kursen!

Im Rahmen der Dortmunder R Kurse bieten wir unsere Expertise in Schulungen für die Programmiersprache R an. Zielgruppe unserer Fortbildungen sind nicht nur Statistiker, sondern auch Anwender jeder Fachrichtung aus Industrie und Forschungseinrichtungen, die mit R ihre Daten analysieren wollen. Die Dortmunder R-Kurse werden ausschließlich von Statistikern mit langjähriger Erfahrung angeboten. Die Referenten gehören zum engsten Kreis der internationalen R-Gemeinschaft. Die angebotenen Kurse haben sich vielfach national und international bewährt.

Unsere Termine für die Online-Durchführung in diesem Jahr:

8., 9. und 10. Juni: R-Basiskurs (jeweils 9:00 – 14:00 Uhr)

22., 23., 24. und 25. Juni: R-Vertiefungskurs (jeweils 9:00 – 13:00 Uhr)

Kosten jeweils 750.00€, bei Buchung beider Kurse im Juni erhalten Sie einen Preisnachlass von 200€.

Zur Anmeldung gelangen Sie über den nachfolgenden Link:
https://www.zhb.tu-dortmund.de/zhb/wb/de/home/Seminare/Andere_Veranst/index.html

R Basiskurs

Das Seminar R Basiskurs für Anfänger findet am 8., 9. und 10. Juni 2020 statt. Den Teilnehmern wird der praxisrelevante Part der Programmiersprache näher gebracht, um so die Grundlagen zur ersten Datenanalyse — von Datensatz zu statistischen Kennzahlen und ersten Visualisierungen — zu schaffen. Anmeldeschluss ist der 25. Mai 2020.

Programm:

  • Installation von R und zugehöriger Entwicklungsumgebung
  • Grundlagen von R: Syntax, Datentypen, Operatoren, Funktionen, Indizierung
  • R-Hilfe effektiv nutzen
  • Ein- und Ausgabe von Daten
  • Behandlung fehlender Werte
  • Statistische Kennzahlen
  • Visualisierung

R Vertiefungskurs

Das Seminar R-Vertiefungskurs für Fortgeschrittene findet am 22., 23., 24. und 25. Juni (jeweils von 9:00 – 13:00 Uhr) statt. Die Veranstaltung ist ideal für Teilnehmende mit ersten Vorkenntnissen, die ihre Analysen effizient mit R durchführen möchten. Anmeldeschluss ist der 11. Juni 2020.

Der Vertiefungskurs baut inhaltlich auf dem Basiskurs auf. Es besteht aber keine Verpflichtung, bei Besuch des Vertiefungskurses zuvor den Basiskurs zu absolvieren, wenn bereits entsprechende Vorkenntnisse in R vorhanden sind.

Programm:

  • Eigene Funktionen, Schleifen vermeiden durch *apply
  • Einführung in ggplot2 und dplyr
  • Statistische Tests und Lineare Regression
  • Dynamische Berichterstellung
  • Angewandte Datenanalyse anhand von Fallbeispielen

Links zur Veranstaltung direkt:

R-Basiskurs: https://dortmunder-r-kurse.de/kurse/r-basiskurs/

R-Vertiefungskurs: https://dortmunder-r-kurse.de/kurse/r-vertiefungskurs/

Image Source: Pixabay (https://pixabay.com/photos/classroom-school-education-learning-2093744/)

The Data Surrounding Higher Education and COVID-19

Just a few short weeks ago, it would have seemed impossible for some microscopic pathogen to upend our lives as we knew it, but the novel Coronavirus has proven us breathtakingly wrong.

It has suddenly and unexpectedly changed everything we had thought was most stable and predictable in our lives, from the ways that we work to the ways we interact with one another. It’s even changed the way we learn, as colleges and universities across the nation shutter their doors.

But what is the real impact of COVID-19 on higher education? How are college students really faring in the face of the pandemic, and what can we do to support them now and in the post-pandemic life to come?

The Scramble is On

Probably the most significant challenge that schools, educators, and students alike are facing is that no one really saw this coming, so now we’re trying to figure out how to protect students’ education while also protecting their physical health. We’re having to make decisions that impact millions of students and faculty and do that with no preparation whatsoever.

To make matters worse, faculties are having to convert their classes to a forum the majority have never even used before. Before the lockdown, more than 70% of faculty in higher education had zero experience with online teaching. Now they’re being asked to convert their entire semester’s course schedule from an in-class to an online format, and they’re having to do it in a matter of weeks if not days.

For students who’ve never taken a distance learning course before, these impromptu, online, cobbled-together courses are hardly the recipe for academic success. The challenge is even greater for lab-based courses, where content mastery depends on hands-on work and laboratory applications. To solve this problem, some of the newly-minted distance ed instructors are turning to online lab simulations to help students make do until the real thing is open to them again.

Making Do

It’s not just the schools and the faculty that have been caught off guard by the sudden need to learn while under lockdown. Students are also having to hustle to make sure they have the technology they need to move their college experience online. Unfortunately, for many students, that’s not always easy, and for some, it’s downright impossible.

Studies show that large swaths of the student population: first-generation college students, community college students, immigrants, and lower-income students, typically rely on on-campus facilities to access the technology they need to do their work. When physical campuses close and the community libraries and hotspots with them, so too does the chance for many students to take their learning online.

Students in urban environments face particular risks. Even if they are able to access the technology they need to engage in distance learning, they may find it impossible to socially isolate. The need to access a hotspot or wi-fi connection might put them in unsafe proximity to other students, not to mention the millions of workers now forced to telecommute.

The Good News

America’s millions of new online learners and teachers may have a tough row to hoe, but the news isn’t all bad. Online education is by no means a new thing. By 2017, nearly 7 million students were enrolled in at least one distance education course according to a recent survey by the National Center for Education Statistics.

It isn’t as though the technology to provide a secure, user-friendly learning experience doesn’t exist. The financial industry, for example, has played a leading role in developing private, responsive, and highly-customizable technology solutions to meet practically any need a client or stakeholder may have.

The solutions used for the financial sector can be built on and modified for the online learning experience to ensure the privacy of students, educators, and institutions while providing real-time access to learning tools and content to classmates and teachers.

A New Path?

As challenging as it may be, transitioning to online learning not only offers opportunities for the present, but it may well open up new paths for the future. While our world may finally be approaching the downward slope of the curve and while we may be seeing the light at the end of the tunnel, until there’s a vaccine, we haven’t likely seen the last of COVID-19.

And even when we lay the COVID beast to rest, infectious disease, unfortunately, is a fact of human life. For students just starting to think about their career paths, this lockdown may well be the push they need to find a career that’s well-suited to this “new normal.”

For instance, careers in data science transition perfectly from onsite to at-home work, and as epidemiological superheroes like Dr. Fauci and Dr. Birx have shown, they are often involved in important, life-saving work. These are also careers that can be pursued largely, if not exclusively, online. Whether you’re a complete newbie or a veteran to the field, there is a large range of degree and certification programs available online to launch or advance your data science career.

It might be that your college-with-corona experience is pointing your life in a different direction, toward education rather than data science. With a doctorate in education, your future career path is virtually unlimited. You might find yourself teaching, researching, leading universities or developing education policy.

What matters most is that with an EdD, you can make a difference in the lives of students and teachers, just as your teachers and administrators are making a difference in your life. You can be the guiding and comforting force for students in a time of crisis and you can use your experiences today to pay it forward tomorrow.