We present Marcel, a lightweight and open-source conversational agent designed to support prospective students with admission-related inquiries. The system aims to provide fast and personalized responses, while reducing workload of university staff. We employ retrieval-augmented generation to ground answers in university resources and to provide users with verifiable, contextually relevant information. We introduce a Frequently Asked Question (FAQ) retriever that maps user questions to knowledge-base entries, which allows administrators to steer retrieval, and improves over standard dense/hybrid retrieval strategies. The system is engineered for easy deployment in resource-constrained academic settings. We detail the system architecture, provide a technical evaluation of its components, and report insights from a real-world deployment.

CXOToday has engaged in an exclusive interview with Dr. Abhijit Dasgupta, SP Jain Global school of Management I have had experience as a Visiting Faculty at IIT Bombay, NIFT New Delhi, SPJIMR etc. during the last 25 years while I was having Leadership roles in Corporates in India / overseas. Since 2018, I am a full-time academic. Youthfulness and excitement to learn new things of students and the requirement to stay updated on the topics that I am teaching (among others) keeps me motivated – these are a couple of things that keeps me connected to the education sector. Till date it has been an intellectually satisfying experience for me. My first engagement with Analytics started way back in 2003, when as a CIO, the organization that I was working with during that time, invested in SAS suite of products to generate effective business intelligence.

'Off-scale salaries' and other components of pay, which would yield compensation that is higher than the published system-wide salary at the designated rank and step, are offered when necessary to meet competitive conditions. Apply by this date to ensure full consideration by the committee. Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled. The School of Information at UC Berkeley welcomes applications for a full-time, non-tenure-track position at the Assistant Adjunct Professor level in the area of Data Engineering, Machine Learning and/or Natural Language Processing. This faculty member will teach in and be an integral part of the Master of Information and Data Science program and will conduct research in one of, or at the intersection of, data-driven engineering, machine learning, and natural language processing.

The Accreditation Board for Engineering and Technology, the nation's most prominent accreditor of programs in science, technology, and engineering, according to an announcement, said that Northern Kentucky University's bachelor's degree in data science will be the first of only two data science programs in the U.S. to earn the organization's accreditation. As data science has emerged as an important field over the last decade, ABET announced that it would be creating accreditation standards for it, according to the organization. NKU was selected in 2020 to be one of only two universities to undergo the inaugural accreditation process. NKU's data science program was only the third such bachelor's program in the U.S. when it launched in 2013. The program focuses on big-data analytics and machine learning, combining a background in computer science and statistics with real-world capstone projects.

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. The era of Big Data has helped democratize information, creating a wealth of data and growing revenues at technology-based companies. But for all this intelligence, we're not getting the level of insight from the field of machine learning that one might expect, as many companies struggle to make machine learning (ML) projects actionable and useful. It starts with strong data infrastructure. Data needs to be accessible across systems and ready for analysis so data scientists can quickly draw comparisons and deliver business results, and the data needs to be reliable, which points to the challenge many companies face when starting a data science program.

Artificial intelligence-inspired policing technology and techniques like facial recognition software and digital surveillance continue to find traction and champions among law enforcement agencies, but at what cost to the public? Some cities like Wilmington, North Carolina, have even adopted AI-driven policing, where technology like ShotSpotter identifies gunshots and their locations. The software also recommends to patrol officers "next best action" based on their current location, police data on past crime records, time of day, and housing and population density. Renée Cummings, data activist in residence at the University of Virginia's School of Data Science, warns that the rules of citizenship are changing with the development of AI-inspired policing technologies. She explains, "If the rules are changing, then the public needs to have a voice and has the right to provide input on where we need to go with these technologies as well as demand solutions that are accountable, explainable and ethical." As artificial intelligence is used toward the development of technology-based solutions, Cummings' research questions the ethical use of technology to collect and track citizen data, aiming to hold agencies more accountable and to provide citizens greater transparency.

Both Data Science and machine learning are very inter-related. It's hard to distinguish them at least at the Masters level. So, don't bother to differentiate them. Between data science and data analytics, it all depends on your existing skills and learning objectives. The course pattern, structure, syllabus everything is quite similar and is interrelated.

As more companies realize the great need for data scientists to develop, experiment, and deploy artificial intelligence (AI), IBM designed a certification program. It offered it to the company workforce, and incentivized employees completed the program through coursework, skills training, and apprenticeships. IBM's certification and related programs "will speed the journey to AI and help improve business performance, efficiency and growth," said Martin Fleming, IBM vice president and chief economist. The demand for data scientists is recognized in the tech industry which "actually identifies the demand for data scientists as one of the industry's most pressing needs." Fleming cites social-media career platform LinkedIn's 2018 report, which found 151,000 US data scientist positions unfilled. "More companies are looking inward for ways to build the skills among their existing workforces," he said.

The 3D X-ray microscopy of frozen hydrated biological specimens is currently approaching a limit to specimen thickness, the surpassing of which violates the pure projection approximation (PPA) needed for standard tomographic imaging. Sufficient understanding of the underlying problem has enabled development of a novel approach to beyond-pure-projection X-ray image construction utilizing powerful--but computationally demanding--methods. This project aims to scale up these methods to meet the challenge of high-resolution X-ray imaging beyond the PPA, benefitting not just cell and brain imaging but the full range of future nanoscale imaging activities at DOE light sources. The discovery of 2D ferromagnetic materials in 2017 ushered in a new era of studies on magnetic order. Using a data-driven approach, this project will combine machine learning and high-throughput density functional theory calculations to study van der Waals layered materials and predict their magnetic and thermodynamic properties.

A recent article in Bloomberg magazine called data science "America's hottest job." In response to increasing demand by industry, government and academia for highly trained data scientists, the University of Virginia's Data Science Institute is launching an online version of its Master of Science in Data Science program next summer. Through a collaboration with Noodle Partners, a company that provides online education management support, the degree can be earned entirely online, and will mirror the curriculum of the Data Science Institute's residential M.S.D.S. program. Currently, 49 students are enrolled in UVA's residential program and 20 more are working toward joint MBA/M.S. in Data Science degrees. The online M.S.D.S. program initially will enroll about 30 students, and that number is likely to grow each semester as the program modestly expands.