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Stratos Idreos, the Gordon McKay Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), has been named Faculty Co-Director of the Harvard Data Science Initiative (HDSI). Idreos will join Francesca Dominici, Faculty Director of the HDSI, in leading the Initiative.

Since its launch in 2017, the HDSI has united data science research and education efforts across the university. It has brought together leading computer scientists, statisticians, and experts from a range of disciplines including law, business, education, medicine and public health to advance data science in personalized health, public policy, scientific discovery and more.

David C. Parkes, the John A. Paulson Dean of SEAS, served as Faculty Co-Director of the Initiative from 2017 to 2023.

At SEAS, Idreos directs the Data Systems Laboratory. His lab is developing fast self-designing data engines that accelerate research and improve productivity across several data-intensive areas including data analytics, data science and artificial intelligence. Self-designing data engines shape themselves automatically to the data, hardware and application context to achieve the best possible performance.

Idreos joined SEAS in 2014. He completed his undergraduate studies and masters degree at Technical University of Crete in Greece, and his Ph.D. at the University of Amsterdam. He has received the United States Department of Energy Early Career Award, an NSF CAREER Grant, and multiple recognitions from the Association for Computing Machinery's Special Interest Group on Management of Data. In 2023, he was awarded the Capers W. McDonald and Marion K. McDonald Award for Excellence in Mentoring and Advising.

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Stratos Idreos Appointed Faculty Co-Director of Harvard Data Science Initiative - Harvard School of Engineering and Applied Sciences

Ethan Gu, a PhD student in computer science at Marquette University, talks with Onochie Fan-Osuala, an associate professor at UW-Whitewater, at a Northwestern Mutual Data Science Institute event. (Jaclyn Tyler photo)

In 2018, three influential local organizations Northwestern Mutual, Marquette University and the University of Wisconsin-Milwaukee united to form the Northwestern Mutual Data Science Institute (NMDSI) with a shared focus on the ever-evolving and dynamic domains of data science and artificial intelligence.

Today, the NMDSI remains committed to advancing research innovation, creating education pathways and driving community impact; our mission holds greater relevancy than ever before.

Northwestern Mutual, Marquette and UWM all recognize and contribute to Southeastern Wisconsins trajectory as a national hub for technology. With nearly $75 million in investments committed to date, NMDSI continues to push the boundaries for what is possible.

The institute also provides funding for an endowed professorship at each university, research projects/grants, student scholarships, new faculty recruitment, development of expanded curriculum and new degree programs, K-12 STEM and pre-college programming, includinginternships and certificates. Fostering increased collaboration and generating innovative project ideation across the institute and our community partners, our NMDSI-affiliated faculty have garnered more than $17 million in grants to date.

Last fall, as part of our five-year renewed investment, we developed a new Center of Excellence initiative through which we announced three innovative programs and engagement opportunities for our university partners. As a result, we awarded $500,000 in research dollars as part of the Paving ROADS Seed Fund Program, $100,000 on behalf of the Pioneer Curricula Program and $175,000 for the NMDSI Student Research Scholars Program. Moreover, the NMDSI also organizes numerous events that have attracted thousands of attendees since our inception. This is only the beginning of what is possible when industry collaborates with academia.

I am extremely proud of how far we have come over the past six years and am even more excited about our future. We will soon be rolling out our NMDSI Industry Affiliate Program, an opportunity to add additional partners who share in the mission of the NMDSI. In addition to our ongoing monthly speaker series, we have various upcoming engagement opportunities through the end of the year, including a Faculty AI Summit in partnership with the Higher Education Regional Alliance and a national conference focused on the ethics of AI. I encourage you to visit the NMDSI website to stay up to date on all our news/events, sign up for our newsletter, and follow us on LinkedIn.

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Northwestern Mutual Data Science Institute: The promise of corporate-academic partnerships - University of Wisconsin-Milwaukee

One of the most significant challenges in training artificial neural networks is catastrophic forgetting. This problem arises when a neural network trained on one task (Task A) subsequently learns a new task (Task B) and, in the process, forgets how to perform the original task. In this article, we will explore a method to address this issue known as Elastic Weight Consolidation (EWC). EWC offers a promising approach to mitigate catastrophic forgetting enabling neural networks to retain knowledge of previously learned tasks while acquiring new skills.

All figures in this article are by author unless otherwise specified

It has been shown that there exist many configurations of optimal parameters with a desired low error on a task gray and yellow regions for tasks A and B respectively in the above figure. Assuming we found one such configuration * for task A, when continuing to train the model from such configuration to a new task B we have three different scenarios:

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Continual Learning A Deep Dive Into Elastic Weight Consolidation Loss - Towards Data Science

Applying existing literature to a practical case Photo by Brett Jordan on Unsplash

Can we predict the extinction of a language? It doesn't sound easy, and it indeed shouldnt, but it shouldnt stop us from trying to model it.

I was recently interested in this topic and started reviewing some of the existing literature. I came across one article[1] that I enjoyed and thought of sharing.

So, in this post, Ill be sharing the insights of that paper, translated into (hopefully) a simple read and applied to a practical case so we can see data science and mathematical modeling in action.

I am Catalan and, for those who dont know, Catalan is a co-official language in Catalonia, Valencian Community, and the Balearic Islands (Spain) along with Spanish. Its also the official language in Andorra, found in the south of France and even in Alghero (Italy).

Its often that we see on local TV or media that the Catalan language is at risk of extinction. Focusing only on Catalonia, we can easily dig deeper into the case because the government takes care of studying the use of the language through whats called the survey of linguistic uses of the population (Enquesta dusos lingistics de la poblaci)[2].

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Modeling the Extinction of the Catalan Language | by Pol Marin | Jun, 2024 - Towards Data Science

There are many programming languages and classes that you could take, so why should you take a course in Python? For starters, Python is one of the fastest-growing programming languages with around 8.2 million users. This vast user community means youll have plenty of company, and a deep network of online forums, local meetups, and the open-source community where youll be able to learn and share. If you are a developer, theres a good chance youll work on projects where Python skills are needed. Python is also one of the easiest languages to learn and use. It was designed to be concise and easy to read, with an efficient syntax that uses fewer lines of code than other languages.

Python has a large collection of frameworks and libraries that speed up your work, and it is compatible across operating systems. Python is extremely versatile and is used for diverse applications, like web development, data science, machine learning, artificial intelligence, and scientific computing. This versatility makes Python an in-demand skill and it means youll be able to choose from a wide variety of career options. In addition, Python is an open-source language, making it license-free and open to contributions from diverse user groups.

Learning Python helps you advance your career as a developer or newly enter the field. If you already have a quantitative background or analytical skills, adding a specialized data science skill set can lead to a high-paying job in fields like data science, advanced analytics, or business intelligence. Employment for software developers is strong and still growing so many opportunities are waiting for people with Python skills.

Python is such a popular programming language that there are many resources available. You can find step-by-step lessons online that introduce the basics or explain specific tasks. This is a great way to become familiar with the capabilities of this robust language. You can also join communities online and on social media where people share what they know and answer questions.

If you want a comprehensive education in Python and a solid set of skills that will help you launch a programming career, Python courses are a great option. They systematically cover the skills youll need with guidance from an instructor whos an expert in the industry. When youre learning Python, its essential to put your budding skills to use and get plenty of practice. The more you practice the better youll become, and building projects is a great way to improve your understanding of the language. Look for classes that incorporate real-world projects, give you hands-on practice, and help you build a portfolio of your skills.

Choosing the best Python course may seem daunting. Some courses are only a few hours and others extend for weeks. Courses may specialize in certain aspects of the language or focus on a particular application, like data science or machine learning. Choosing the right course for you depends on whether you are interested in learning Python as a hobby or for your career, and which field youre trying to enter.

If youre new to Python, look for a course thats designed for beginners. Youll want a basic orientation to the language and the logic behind it so you can start to think like a programmer. For more advanced skills, many classes will teach you to use libraries like Scikit-Learn, Numpy, and MatPlotLib. Advanced courses may focus on Python skills for particular fields like data science or finance. Look for a course with a live instructor who can answer your questions and provide feedback, and check whether youll be able to work on real-world projects that give you practice with Python and help you begin to build a portfolio. Python private tutoring is a good option if youd like one-on-one sessions where you can learn at your own pace and focus on the topics that meet your goals.

What you will learn in a Python course depends on your skill level and the way that you want to use Python. If youre completely new to Python, youll start by learning about the development environment and Python syntax and structure. Then, youll learn to work with different types of data and variables and write control structures like conditional statements and loops. Youll gain an understanding of blocks of code called functions and how to order data into structures. Once you understand how to use Python, you can explore the way that libraries expand its capabilities.

Object-oriented programming is useful to know because many other programming languages use it in addition to Python. OOP allows you to write concise, legible code and create secure and reliable software. You can interact with databases using libraries like SQLite or SQLAlchemy, and you can manipulate and visualize data using libraries like Pandas, Matplotlib, or Seaborn, making your data more meaningful and shareable. If you are using Python for web development, youll explore web frameworks like Flask or Django and learn to create simple web applications. You can also automate tasks using Python scripts and libraries like selenium. Last but not least, youll learn to test your programs and use debugging techniques and tools.

By the end of a comprehensive Python course, you should be able to write Python scripts, use Pythons powerful libraries and frameworks, and develop simple applications or perform data analysis tasks.

Python is widely used in NYC across various industries and by numerous companies, making it a valuable skill to learn. Financial firms like Goldman Sachs and JP Morgan Chase use Python for developing trading algorithms, risk management systems, and quantitative analysis, and they use Pythons libraries to process and visualize large datasets that guide investment decisions. NYCs thriving ecosystem of AI startups relies on Python libraries like TensorFlow, Keras, and Scikit-Learn to build machine learning models and AI-driven applications. Python frameworks like Django and Flask allow them to develop robust and scalable applications quickly.

At media companies like Spotify and The New York Times, Pythons versatility with big data makes it ideal for analyzing user data and improving content recommendations and ad targeting. E-commerce companies like Etsy and Warby Parker also use Python to develop recommendation systems for consumers. Python is invaluable for analyzing sales data, managing inventory, and predicting consumer trends using data analytics.

Pythons powerful data analysis capability is also widely used in the booming field of life sciences, where it powers bioinformatics and healthcare research by companies like Pfizer and Memorial Sloan Kettering Cancer Center, and it helps to analyze patient data and improve healthcare. Pythons simplicity and readability make it a popular choice for educational software development at platforms like Khan Academy and Coursera. Real estate firms like Zillow and Compass use Python to analyze market trends and property values, and it excels at automating tasks like property listings and data collection.

A Python bootcamp is worthwhile if you want to build your skills in this versatile and widely-used programming language. When you complete a Python bootcamp, youll learn essentials like basic syntax and data structures and get hands-on experience building programs. A bootcamp can help you leap forward from basic programming skills to specialties like data science and machine learning, and it often includes mentoring, career coaching, and networking opportunities. A Python bootcamp will give you the confidence to tackle real-world projects and boost your job prospects in tech-savvy cities like NYC. A Python bootcamp can be a great investment in your tech career.

Enrolling in a career-focused Python bootcamp can help you prepare for a future career in one of several different industries. Python is heavily utilized in the field of data science, so if you are interested in becoming a data scientist or a data analyst, learning the skills youll pick up in a data book camp will greatly improve your chances of finding work. Since data has become such an essential part of virtually every industry, these skills are highly marketable, especially in a city like NYC where so many finance and investing firms are located (FinTech is a huge part of data science after all). In NYC, data scientists can expect to earn over $100,000 a year.

Beyond working in data science, Python is an important part of the emerging technological revolutions in machine learning and artificial intelligence. Python is utilized to write the algorithms that allow for LLMs, Chatbots and other artificial intelligence applications to operate and it is an important part of the learning process, allowing machines to read and interpret large amounts of data with the help of a human operator. It is difficult to tell what the future holds for this emerging technology, but it is certainly having an impact across a range of industries (including finance, commerce and advertising, all of which are key parts of the NYC economy). Learning how to program these algorithms is an important aspect of leveraging this technology and businesses are paying a premium for skilled Python Developers who can help them take advantage of these automated systems.

Even if you arent aiming for a career in Python, learning how to manipulate, collect and query data is useful for any aspiring professional looking to grow their brand, get attention to their start-up or otherwise work with investors to get a project off the ground. Learning how to use basic Python programming skills and techniques will ensure that you arent leaving valuable information on the table, particularly as data analysis becomes increasingly important for anyone to get an edge in the market. You dont want to get left behind and taking a Python bootcamp can help ensure that you are able to leverage data to suit your needs.

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The best Python classes, certificates and bootcamps in NYC - Time Out