LifeJourney International has launched its Day of STEM initiative, aiming to show students what it actually means to have a career in science, technology, engineering, and mathematics (STEM), with the backing of some of the country's tech heavyweights. The program, Australia 2020, aims to push students towards a STEM-based career, but operates under the assumption that telling students to study STEM is not enough to incite interest. The online platform allows kids to explore what it is like to have a career in fields such as wireless technology, cybersecurity, drone delivery, financial services, and autonomous vehicles, with students mentored by Ian Hill, chief innovation officer at Westpac; Simone Bachmann, digital trust specialist, responsible for cyber innovation and culture at Australia Post; Gerard Tracey, wireless telecommunications expert at Telstra; Anastasia Cammaroto, CIO at BT Financial Group; Celeste Lowe, cyber risk director at Deloitte; Ita Farhat, chief of staff at AMP; Cara Walsh, digital experience expert from Queensland's RACQ; Martin Levins, consultant at Australian Council for Computers in Education; and others. The program is also backed by the likes of Australian Association of Mathematics Teachers, and the Australian Computer Society, as well as an education advisory board to ensure the content stays relevant to the Australian market. A Day in STEM is pushed out to teachers and run in the classroom, with 95,000 students already signed up to the program ahead of its September 5 launch.
Royal Melbourne Institute of Technology (RMIT) Online has announced another slew of tech-related university courses, accelerating its plan to tackle the impending skills shortage Australia is expected to face. The new courses come courtesy of a partnership with Silicon Valley-based global education startup Udacity, which works with the likes of Google, Facebook, Mercedes-Benz, and Nvidia to close talent gaps. This is the first time it has partnered with a university, however. According to RMIT Online, the courses will address skills shortages in emerging tech, robotics, engineering, and artificial intelligence fields through short courses that bring a "Silicon Valley mindset to Australia's workforce". RMIT Online CEO Helen Souness said Australia is facing a growing skills shortage across many design and technology fields and believes universities must lead the way.
My name is Kirill Eremenko and I am super-psyched that you are reading this! I teach courses in two distinct Business areas on Udemy: Data Science and Forex Trading. I want you to be confident that I can deliver the best training there is, so below is some of my background in both these fields. Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes.
Accurate house prediction is of great significance to various real estate stakeholders such as house owners, buyers, investors, and agents. We propose a location-centered prediction framework that differs from existing work in terms of data profiling and prediction model. Regarding data profiling, we define and capture a fine-grained location profile powered by a diverse range of location data sources, such as transportation profile (e.g., distance to nearest train station), education profile (e.g., school zones and ranking), suburb profile based on census data, facility profile (e.g., nearby hospitals, supermarkets). Regarding the choice of prediction model, we observe that a variety of approaches either consider the entire house data for modeling, or split the entire data and model each partition independently. However, such modeling ignores the relatedness between partitions, and for all prediction scenarios, there may not be sufficient training samples per partition for the latter approach. We address this problem by conducting a careful study of exploiting the Multi-Task Learning (MTL) model. Specifically, we map the strategies for splitting the entire house data to the ways the tasks are defined in MTL, and each partition obtained is aligned with a task. Furthermore, we select specific MTL-based methods with different regularization terms to capture and exploit the relatedness between tasks. Based on real-world house transaction data collected in Melbourne, Australia. We design extensive experimental evaluations, and the results indicate a significant superiority of MTL-based methods over state-of-the-art approaches. Meanwhile, we conduct an in-depth analysis on the impact of task definitions and method selections in MTL on the prediction performance, and demonstrate that the impact of task definitions on prediction performance far exceeds that of method selections.
GO1, a Queensland startup enabling organisations to create online training programs for their employees, has raised AU$4 million from a consortium of investors including Black Sheep Capital, Full Circle Venture Capital, Blue Sky Ventures, Amasia, and ex-Wotif.com More than AU$1 million was provided by the Queensland government's Business Development Fund, with existing investors Tank Stream Labs, Y Combinator, and Shark Tank's Steve Baxter also contributing to the startup's pre-Series A funding round. GO1 has previously raised $1 million from Baxter and Tank Stream Labs, in addition to receiving the standard $120,000 from Silicon Valley startup accelerator Y Combinator in exchange for 7 percent equity. The latest round values the three-year-old edtech startup at over AU$15 million. The investment will be used to grow GO1's global sales team by 30 staff over the next 12 months, as well as for ongoing product development.