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As a first-year Duke student working towards a career in medicine, Benjamin Asomani was curious about computer science and coding, but wary of diving into coursework without prior exposure to the field. At the suggestion of another student, he participated in the summer 2021 Code+ program, learning CSS and HTML skills as part of an applied group project, while confirming his interest in computer science. This semester, Asomani has begun coursework for a minor in computer science to complement his planned major in biology.

The hands-on learning was a good way to be introduced to coding. I liked the process of making and building something for a project and having instructors who could help us review our work and spot mistakes, said Asomani, who finished the program feeling confident about his abilities in CSS and HTML.

Dukes Center for Computational Thinking (CCT) launched in 2020 to support and coordinate campus-wide resources for faculty, students and staff. Its core priority is to ensure all Duke students can be exposed to computational approaches and learn to use data to create new knowledge.

For students like Asomani, the CCTs network of programs can provide an introduction to computing, and make computational majors more accessible by reducing real or perceived barriers to entry.

For undergraduate Harsha Srijay, the summer 2020 +DataScience Advanced Research Program linked his math and data science majors with his interest in bioinformatics for a project exploring the use of predictive models for diagnosing respiratory diseases. Im more interested in applied work than theoretical modeling, and this project let me focus on using the tools of data science to solve real-world problems, Srijay noted.

To support instruction, the CCT works with faculty and departments across Duke to integrate computing-related content into their courses, and provides learning modules to supplement faculty instruction.

Learning how to draw critical conclusions from data and to take computational approaches to solving complex problems across disciplines are important elements of a 21st century liberal arts education, said Provost Sally Kornbluth. The CCT is connecting existing resources at Duke and responding to gaps in our current offerings to ensure all students and faculty have the opportunity to bring these approaches to their studies and their research.

Kornbluth recently appointed Duke School of Medicine Professor Matthew Hirschey to lead the center, working in close partnership with computing colleagues across campus. A molecular physiologist who embraced data science several years ago to advance his own skills and his labs data analysis capabilities, Hirschey is committed to helping students and colleagues realize the benefits of computational approaches.

As someone who came to computation rather recently, my perspective is that this is something everyone should know, Hirschey said. His vision involves helping students who are already steeped in computing understand its intersections with ethics, policy and other fields. And for liberal arts students and scholars, Hirschey wants the CCT to help them become comfortable and capable with computation and computational tools to extract meaning from data, regardless of their field of study, he noted. Because the current generation of liberal arts students should understand how computational approaches can be used to find patterns in literature, or art, or dance.

In a mini-course on data science led by Hirschey, Ph.D. students Taylor Chavez and Jessica Portillo learned computational skills with immediate application to their research. I come from a wet lab background, and this has provided the foundation and basic components of what I need, and clarified that I do want to do more computational work in the future, said Portillo.

Chavez studies tissue engineering and used course assignments to work with data from her experiments. I have some coding background, but really not enough, she said. This was the first time Id actually taken a class that was meant to teach me how to analyze and visualize experimental data in the context of my science. I brought my own data, and I got to play with different ways to visualize the results in ways that made sense for how I wanted to present my data.

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Computational Thinking Is for Everyone - Duke Today

The School of Humanities and Sciences is pleased to announce that applications are now open for the 2022 H&S Summer Scholars Program.

The H&S Summer Scholars Program provides paid positions in the summer for H&S studentsin all majorsto engage full-time in research, scholarship, or creative inquiry projects in collaboration with an H&S faculty mentor. This year, we are considering projects that can be done either remotely or in-person. The standard Scholar compensation for 2022 is $4,224 for 8 weeks of full-time work beginning on June 1.

Summer Scholars has given me the opportunity to create a project that will propel me into my future after college. During that process I have been able to work on my investigative skills, my writing, and my ability to communicate my thoughts to others. Having so much freedom also allowed me to realize how I work best, which translates into other aspects of my life. Overall, the Summer Scholars program made me a better student, academic, and person. A recent Summer Scholar

All H&S students apply to the H&S Summer Scholars via an online application. Complete information on eligibility and program requirements, as well as links to the online application, are available on theH&S Summer Scholars webpage.

The deadline for submission is Monday, February 28 at 4pm.Decisions will be announced no later than April 2, 2022.

Students applying to the program will be considered for all available positions. Some positions, such as those supported by the Dana Internship program or the Emerson Humanities Collaboration Award, require students to be financial aid eligible, but no additional application materials are required to be considered for these awards. For full consideration, students must have a current FAFSA on file with Student Financial Services at the time of application to receive consideration for positions supported by these programs.

WANTTOKNOWMORE?

Were hosting two zoom information sessions specifically for students designing independent projects in creative arts, humanities, and social science fields:*Monday, January 31 at 3pm Thursday, February 3 at 12:10pmYou must register for the session in order to receive the zoom link.At these sessions, well review application requirements and program expectations.

*Students with majors in the departments of Biology, Chemistry, Computer Science, Environmental Studies & Sciences, and Physics/Astronomy should be in touch with their departments to find out about summer research opportunities with faculty in those fields.

We also welcome individual inquiries via the H&S Deans office athsadmin@ithaca.edu.

Link:

H&S Students: Apply to be a 2022 Humanities and Sciences Summer Scholar! - Ithaca College

Jacob Adams holds a bachelors degree in Mathematics and Computer Science, which incorporated similar concepts to those used in Data Science, but he did not know how to use his knowledge and skills to advance his career.

The Master of Science in Data Science (MSDS) at Texas Tech University changed that. It helped him realise there is a promising future in, what the World Economic Forum calls, the new gold.

Source: Texas Tech University Rawls College Of Business

Data is utilised in every facet of the economy today, and people from all over the world and from every different background can succeed if they want to learn how to improve decision-making in business. The MSDS degree has helped me identify how everything I learned in my undergraduate is being used in the real world, Adams enthused.

Although this programme is offered by the Rawls College of Business, it provides the perfect mix of both technical and business coursework, much to Ritu Jagatpal Tomars delight. The MSDS alumna strongly feels that this balance is the best aspect.

Adams concurs, adding, this programme is not specifically created for technically inclined people. He believes that its strategic combination of courses has allowed him to get ahead of most people in this industry.

The MSDS programme provides flexible learning modes: online or on campus. Source: Texas Tech University

The MSDS programme is flexible; designed to fit a wide range of personal and professional needs. Students learn how to use advanced technologies and statistical methods to manipulate and interpret data into actionable organisational strategies in one accelerated year either online or on campus. A two-year, part-time option is available online only.

Nick Burns, a graduate of the programme, took the one-year option, and has no regrets.

Looking back, the time I put into it was well worth it. If you put in the time and effort, you will definitely reap the benefits, recalls Burns, who worked his way up in the Data Analytics industry after graduation. He is now the CEO of his own coaching business.

Indeed, the MSDS programme is not only flexible, but affordable.

Texas Tech Universitys campus is located in the affordable city of Lubbock, Texas. Source: Texas Tech University

TTUs Rawls College of Business is located in Lubbock, Texas where students can enjoy both big city conveniences and small-town friendliness. Lubbock is ranked 16th among Texass cheapest urban areas and scores an impressive 91.5% for their overall cost of living index (Council for Community and Economic Research 2017), a fact that greatly appealed to Tomar.

Since Im an international student, one of the things that persuaded me to pursue this course was that the cost of living in Lubbock is quite low. You can manage your expenses very well here, Tomar explained.

In addition to the attractive costs, there is another incentive that may be of particular interest to international students. This programme is STEM-designated, which means upon completion, international students may qualify to work in the US under the Optional Practical Training (OPT) programme for up to three years after receiving their degrees.

Furthermore, as one of the first and most well-established Data Science programmes in the country, it is little wonder the online MSDS programme performs well in rankings. It is ranked #6 nationally, and the US News and World Report 2021 gave this programme the #17 spot for Best Online Masters in Business Programmes (Excluding MBA).

As we strive to provide a high-quality education to our students, the rankings show that all the strategic initiatives we have taken over the last few years are making an impact, raved Dr. Mayukh Dass, Associate Dean of Graduate Programmes and Research.

TTU Rawls College of Business faculty members are skilled in research subjects such as computer-aided decision making and information requirements determination. Adams is especially grateful for this.

MSDS graduates are highly esteemed in the industry. Source: Texas Tech University

Our professors are former professionals in their area of expertise, and are always willing to help, Adams chimed in, adding that he and other fellow students can also make use of the renowned of Rawls Career Management Centres useful employment services.

All of this, affordability, sterling rankings, exceptional faculty and student-oriented support services, result in an average starting salary of US$90,000 and an outstanding job placement rate of 90% for graduates. If you are looking for an excellent US postgraduate programme in Data Science, apply here today.

Follow Texas Tech University Rawls College of Business on Facebook, Twitter, YouTube, Flickr, Instagram and LinkedIn

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Master of Science in Data Science at Texas Tech University: The best of both worlds - Study International News

In 1998, a computer science PhD student called Larry Page submitted a patent for internet search based on an obscure piece of mathematics. The method, known today as PageRank, allowed the most relevant webpages to be found much more rapidly and accurately than ever before. The patent, initially owned by Stanford, was sold in 2005 for shares that are today worth more than $1bn. Pages company, Google, has a net worth of well over $1tr.

It wasnt Page, or Googles cofounder Sergey Brin, who created the mathematics described in the patent. The equation they used is at least 100 years old, building on properties of matrices (mathematical structures akin to a spreadsheet of numbers). Similar methods were used by Chinese mathematicians more than two millennia ago. Page and Brins insight was to realise that by calculating what is known as the stationary distribution of a matrix describing connections on the world wide web, they could find the most popular sites more rapidly.

Applying the correct equation can suddenly solve an important practical problem, and completely change the world we live in.

The PageRank story is neither the first nor the most recent example of a little-known piece of mathematics transforming tech. In 2015, three engineers used the idea of gradient descent, dating back to the French mathematician Augustin-Louis Cauchy in the mid-19th century, to increase the time viewers spent watching YouTube by 2,000%. Their equation transformed the service from a place we went to for a few funny clips to a major consumer of our viewing time.

From the 1990s onwards, the financial industry has been built on variations of the diffusion equation, attributed to a variety of mathematicians including Einstein. Professional gamblers make use of logistic regression, developed by the Oxford statistician Sir David Cox in the 50s, to ensure they win at the expense of those punters who are less maths-savvy.

There is good reason to expect that there are more billion-dollar equations out there: generations-old mathematical theorems with the potential for new applications. The question is where to look for the next one.

A few candidates can be found in mathematical work in the latter part of the 20th century. One comes in the form of fractals, patterns that are self-similar, repeating on many different levels, like the branches of a tree or the shape of a broccoli head. Mathematicians developed a comprehensive theory of fractals in the 80s, and there was some excitement about applications that could store data more efficiently. Interest died out until recently, when a small community of computer scientists started showing how mathematical fractals can produce the most amazing, weird and wonderful patterns.

Another field of mathematics still looking for a money-making application is chaos theory, the best-known example of which is the butterfly effect: if a butterfly flaps its wings in the Amazon, we need to know about it in order to predict a storm in the North Atlantic. More generally, the theory tells us that, in order to accurately predict storms (or political events), we need to know about every tiny air disturbance on the entire planet. An impossible task. But chaos theory also points towards repeatable patterns. The Lorenz attractor is a model of the weather that, despite being chaotic, does produce somewhat regular and recognisable patterns. Given the uncertainty of the times we live in, it may be time to revive these ideas.

Some of my own research has focused on self-propelled particle models, which describe movements similar to those of bird flocks and fish schools. I now apply these models to better coordinate tactical formations in football and to scout players who move in ways that create more space for themselves and their teammates.

Another related model is current reinforced random walks, which capture how ants build trails, and the structure of slime mould transportation networks. This model could take us from todays computers which have central processing units (CPUs) that make computations and separate memory chips to store information to new forms of computation in which computation and memory are part of the same process. Like ant trails and slime mould, these new computers would benefit from being decentralised. Difficult computational problems, in particular in AI and computer vision, could be broken down in to smaller sub-problems and solved more rapidly.

Whenever there is a breakthrough application of an equation, we see a whole range of copycat imitations. The current boom in artificial intelligence is primarily driven by just two equations gradient descent and logistic regression put together to create what is known as a neural network. But history shows that the next big leap forward doesnt come from repeatedly using the same mathematical trick. It comes instead from a completely new idea, read from the more obscure pages of the book of mathematics.

The challenge of finding the next billion-dollar equation is not simply one of knowing every page of that book. Page spotted the right problem to solve at the right time, and he persuaded the more theoretically inclined Brin to help him find the maths to help them. You dont need to be a mathematical genius yourself in order to put the subject to good use. You just need to have a feeling for what equations are, and what they can and cant do.

Mathematics still holds many hidden intellectual and financial riches. It is up to all of us to try to find them. The search for the next billion-dollar equation is on.

David Sumpter is professor of applied mathematics at the University of Uppsala, Sweden, and author of The Ten Equations that Rule the World: And How You Can Use Them Too

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Equations built giants like Google. Wholl find the next billion-dollar bit of maths? - The Guardian