STEM


How to Prepare the Next Generation for Jobs in the AI Economy

#artificialintelligence

People who create this type of technology must be able to build teams, work in teams, and integrate solutions created by other teams. The number of students taking Advanced Placement exams in computer science is growing dramatically, but the 58,000 students taking the AP Computer Science A (APCS-A) test last year still pales in comparison to the 308,000 who took the AP Calculus AB test. Few U.S. high schools now go beyond the core training necessary to prepare for the APCS-A exam, though we have a few stunning success stories -- Stuyvesant High School in New York City, Thomas Jefferson High School for Science and Technology in Alexandria, Virginia, and TAG (The School for the Talented and Gifted) in Dallas, among others. As with science and math, we need governmental standards driving K-12 computer science education, along with textbooks, courses and ultimately a highly trained national cadre of computer science teachers that are tied to those standards.


7 Steps to Mastering Machine Learning With Python

@machinelearnbot

Since we will be using scientific computing and machine learning packages at some point, I suggest that you install Anaconda. This actually is a reflection of the field of machine learning, since much of what data scientists do involves using machine learning algorithms to varying degrees. Gaining an intimate understanding of machine learning algorithms is beyond the scope of this article, and generally requires substantial amounts of time investment in a more academic setting, or via intense self-study at the very least. For example, when you come across an exercise implementing a regression model below, read the appropriate regression section of Ng's notes and/or view Mitchell's regression videos at that time.


Online program wins engineering education award

MIT News

The team was chosen for its design and development of a new four-course online professional certification program called Architecture and Systems Engineering: Models and Methods to Manage Complex Systems. Nine faculty members from MIT and more than 25 industry experts from Boeing, NASA, IBM, Apple, General Electric, General Motors, and other companies developed content for the courses. To earn a certificate, students must complete four courses: Architecture of Complex Systems; Models in Engineering; Model-Based Systems Engineering: Documentation and Analysis; and Quantitative Methods in Systems Engineering. ASEE, the award sponsor, created the Excellence in Engineering Education Collaboration Awards to demonstrate best practices in collaboration that enhance engineering education.


The politics of math: Is algebra necessary to obtain a college degree?

Los Angeles Times

To transfer to California State University, community college students generally must show evidence of completing an approved, quantitative reasoning course with "an explicit intermediate algebra prerequisite." In 2009, the California Community Colleges system raised its elementary algebra minimum and also began requiring demonstrated math competency at the level "typically known as Intermediate Algebra ... or another mathematics course at the same level, with the same rigor." Some schools, like Pierce College and College of the Canyons, have experimented with programs such as the Carnegie Foundation's Statway and those developed by the California Acceleration Project -- courses in statistics and data analysis designed for majors not in math or science as a way to reach college-level quantitative reasoning without getting stuck in non-credit remedial courses or completing a traditional intermediate algebra course. Cal State administrators have been open to exploring alternative pathways for some majors: As a pilot, the system has accepted some transfers who completed the Statway program, and a few campuses are currently piloting the statistics approach for their own remedial math students.


Program Allows Kids To Build And Fly Drones, While Helping Them Grow In STEM Fields

International Business Times

A new program called Project Icarus is teaching kids how to build drones, while at the same time helping them grow in STEM fields, which focus in science, technology, engineering and mathematics. Seven-year-old Ava builds her drone at a Project Icarus workshop. Dani Dias' seven-year-old daughter Ava participated in a Project Icarus workshop. The drone program helped Ava grow, her mother said.


Machine passes EM gaokao /EM math test - China - Chinadaily.com.cn

#artificialintelligence

A smart machine made by a company in Chengdu, Sichuan province, took the math test of the national college entrance examination, or gaokao, on Wednesday. AI-MATHS is an artificial intelligence program developed in 2014, based on cutting-edge big data technology, artificial intelligence and natural language recognition from Tsinghua University. Before Wednesday's test, the developer had the machine answer 12,000 math questions to improve its logical reasoning and computer algorithms. In February, AI-MATHS took a math test with Grade 3 students at Chengdu Shishi Tianfu High School and scored 93, slightly higher than the passing grade of 90.


How to Prepare the Next Generation for Jobs in the AI Economy

#artificialintelligence

People who create this type of technology must be able to build teams, work in teams, and integrate solutions created by other teams. The number of students taking Advanced Placement exams in computer science is growing dramatically, but the 58,000 students taking the AP Computer Science A (APCS-A) test last year still pales in comparison to the 308,000 who took the AP Calculus AB test. Few U.S. high schools now go beyond the core training necessary to prepare for the APCS-A exam, though we have a few stunning success stories -- Stuyvesant High School in New York City, Thomas Jefferson High School for Science and Technology in Alexandria, Virginia, and TAG (The School for the Talented and Gifted) in Dallas, among others. As with science and math, we need governmental standards driving K-12 computer science education, along with textbooks, courses and ultimately a highly trained national cadre of computer science teachers that are tied to those standards.


What Does It Mean to Prepare Students for a Future With Artificial Intelligence? (EdSurge News)

#artificialintelligence

The plan was the beginning of a national effort to prepare Americans for a future with AI--a future some computer scientist believe our nation is ill-equipped to handle. Using research and concepts from several AI experts including Mark Stehlik of Carnegie Mellon and Rand Hindi of Snips, EdSurge put together the following three-step list educators can use to start implementing AI education in schools. Dr. Rand Hindi, CEO of Snips (a machine learning device company), is part of a research group working with the French government to prepare their country for AI. For Stehlik, the onus is on technology companies and higher education institutions to prepare K-12 teachers for AI instruction by providing them with curriculums, capacity and continuing education opportunities.


Thoughts on the EU's draft report on robotics

Robohub

I was asked to write a short op-ed on the European Parliament Law Committee's recommendations on civil law rules for robotics. In the end, the piece didn't get published, so I am posting it here: It is a great shame that most reports of the European Parliament's Committee for Legal Affairs' vote on its Draft Report on Civil Law Rules on Robotics headlined on'personhood' for robots because the report has much else to commend it. Within the report's draft Code of Conduct is a call for robotics funding proposals to include a risk assessment. This too is a very good idea and guidance already exists in British Standard BS 8611, published in April 2016.


List of Free Must-Read Books for Machine Learning

#artificialintelligence

In this article, we have listed some of the best free machine learning books that you should consider going through (no order in particular). Based on the Stanford Computer Science course CS246 and CS35A, this book is aimed for Computer Science undergraduates, demanding no pre-requisites. This book holds the prologue to statistical learning methods along with a number of R labs included. This Deep Learning textbook is designed for those in the early stages of Machine Learning and Deep learning in particular.