This intermediate-level course introduces the mathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique. We'll cover some basic statistics of data sets, such as mean values and variances, we'll compute distances and angles between vectors using inner products and derive orthogonal projections of data onto lower-dimensional subspaces. Using all these tools, we'll then derive PCA as a method that minimizes the average squared reconstruction error between data points and their reconstruction. At the end of this course, you'll be familiar with important mathematical concepts and you can implement PCA all by yourself. If you're struggling, you'll find a set of jupyter notebooks that will allow you to explore properties of the techniques and walk you through what you need to do to get on track.

Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. Understanding the importance and challenges of learning agents that make decisions is of vital importance today, with more and more companies interested in interactive agents and intelligent decision-making. This course introduces you to the fundamentals of Reinforcement Learning. When you finish this course, you will: - Formalize problems as Markov Decision Processes - Understand basic exploration methods and the exploration/exploitation tradeoff - Understand value functions, as a general-purpose tool for optimal decision-making - Know how to implement dynamic programming as an efficient solution approach to an industrial control problem This course teaches you the key concepts of Reinforcement Learning, underlying classic and modern algorithms in RL.

A team of researchers using what they call "state-of-the-art artificial intelligence techniques" has reportedly created a system capable of identifying a human's political ideology by viewing their brain scans. This is either the most advanced AI system in the entire known universe or it's a total sham. You don't even have to read the researcher's paper to debunk their work. All you need is the phrase "politics change," and we're done here. But, just for fun, let's actually get into the paper and explain how prediction models work. A team of researchers from Ohio State University, University of Pittsburgh, and New York University gathered 174 US college students (median age 21) -- the vast majority of whom self-identified as liberal -- and conducted brain scans on them while they completed a short battery of tests.

For many in the field of technology and computer science, the future doesn't exist without artificial intelligence. That was the topic of discussion and interest at the AI & the Future of Houston Conference in April, where professionals and science educators, including University of Houston-Victoria faculty, gathered to discuss the future of the field. The two-day conference was held April 29-30 in Houston and hosted by Houston Community College. Representatives from HCC, Houston-area universities, businesses and health care facilities and HCC students attended the event. UHV participated in the conference as sponsors and vendors, and UHV faculty also spoke at the event.

Microsoft, NASA, and students from two HBCUs in the Reston/DC area have completed the maiden mission of a new Microsoft/NASA partnership, STEM Educational Project: AI looking for new Earths. Using methodology developed by The Microsoft Garage over years of running hackathons, in just one month – and while completing their final exams – the student hackers learned and deployed several new technologies, and quite literally reached the stars by showing they could deploy code to the International Space Station. According to Piali Ghose, Director of The Garage Reston/DC and host of the event, "This hackathon amplifies the cultural priorities closest to our hearts here at Microsoft and at The Garage because it allows us to continue fulfilling our stated commitments to making a difference, seeking diversity and being inclusive in our work, bringing multiple teams together as'One Microsoft' while collaborating with federal and academic partners, and doing all of this with a growth mindset." The partnership emerged from a shared goal of fostering the future STEM workforce by exposing university students to science, tools, and expertise "at the intersection of Space Cloud." By structuring the project as a month-long hackathon, participating students learned how real data scientists work as a team to ideate, develop, and validate their work with a proof of concept.

The Core courses give them sufficient expertise in the areas of Algorithm Analysis and Design, Modern Computer Architecture, Artificial Intelligence Foundations, Data Science and Machine Learning, Parallel and Distributed Data Management etc. Elective courses include various application domains of AI such as Robotics, Video/Image Analytics, Medical Signal Processing, Agents Based Systems, Data Mining and Business Analytics, Natural Language processing, Wireless Sensor Networks, Internet of things etc. Once they complete the course, students get opportunities to get fully paid Internships and placement offers at MNCs and IT/ITES companies like Intel, Cerner, Robert Bosch, DELL etc. Also, they could publish quality research papers of the case studies/dissertations done as part of their M. Tech. Along with regular M. Tech, this program also provides opportunities to do Dual Degree Program (M. Tech from Amrita and MS from International universities) or One Semester/ One Year abroad programs offered by premiere universities like KTH (Sweden), Politecnico Di Milano (Italy), University of New Mexico (USA) and RWTH (Aachen University Germany).

We're delighted to welcome University of Central Florida students to our next round of lightning talks. Intelligent Tutoring Systems: Why use one model when you can use them all? Adaptation is a key element that enhances students' learning experience in Intelligent Tutoring Systems (ITS). In ITS, student responses serve as input for predictive student performance models that trigger adaptation. Our research proposes that a customized prediction model (i.e., customized to each student) performs better than one-size-fits-all models. Another tangent of our research focuses on the impact of choice in ITS.

Join us for a free webinar (in English) during which the Consul Generals of Mexico and the United States will moderate a discussion with panelists in the AI sector. Panelists will discuss topics on gender, inclusion and ethical issues related to the field. This event is open to the public and there will be a Q&A portion for participants to interact with the panelists.

These AI powered facilities will make online learning so much easier by technological integrations, and also reforge the style of Physical Learning. The introduction of Robotic teachers will not eliminate human teachers, but will ease their job and/or reduce their number in the Education Facilities. The major job of teachers might shift to improvement of Robot's Intelligence and collection of data for neural module development. Education facilities such as classrooms, examination/assessment halls, laboratories and research facilities could become Massive Artificial Intelligence Powered Edusystems where students can access at their respective convenience. Automation saves time, labor and cost, while delivering utmost efficiency. Robotic Teachers will enhance Online Learning Technology by facilitating better computer-to-computer integration and interoperability. Robotic Teachers will also overcome the problems of the human body such as fatigue, irritation and mood swings.

ISLAMABAD: The federal government has allocated Rs 723 million for the promotion of Artificial Intelligence (AI) in the country to cope with the challenges of technological advancement. The Defence Division will spend Rs 300 million on the development of Information and Communication Technology (ICT) and AI-based precision agriculture system. Named Green AI, the system will utilize dual-use aerospace technologies. For the establishment of the Sino-Pak Centre for Artificial Intelligence under the Information Technology and Telecom Division, an estimated Rs 243 million has been allocated. The National Centre of Artificial Intelligence, Islamabad will work under the Higher Education Commission, for which Rs 170 million has been allocated.