Develop and nurture the skills most in-demand by top employers
TORONTO, May 14, 2018 /CNW/ - As tech giants and other businesses increasingly rely on data and artificial intelligence (AI) to stay competitive, there is greater demand than ever for machine learning specialists with the requisite technical skills, as well as an in-depth, real-world understanding of the ethical, social, and business implications of their work. The York University School of Continuing Studiesi recently launched a part-time Certificate in Machine Learning to address this demand. The only dedicated program of its type in Canada—and created in collaboration with industry leaders in AI and machine learning—the certificate focuses on preparing students to become qualified candidates for the rewarding, desirable jobs on offer by top employers.
"Job growth in machine learning in Canada has already grown by 450%, and by 900% in the Greater Toronto Area1. Growth is expected to exceed another 56% over the next few years2. York University is eager to help employers meet an unprecedented need for trained data science professionals capable of developing and implementing machine learning solutions in response to complex business problems," says Tracey Taylor-O'Reilly, Assistant Vice-President, Continuing Studies. "We are thrilled to be helping to train the next generation of machine learning specialists in healthcare, finance, automotive and other leading fields."
1 Burning Glass
2 Quant Crunch Report
Designed for working professionals in software development, data science, business analysis, business intelligence, and related fields, the Certificate in Machine Learning offers students an accelerated path to completion, rich networking opportunities, and a unique cohort experience that allows them to build the cross-functional skills that top employers seek. Over eight months of study, completed online with occasional in-class sessions and completion of a project with selected companies, students will gain both the real-world skills needed to work in this competitive market and comprehensive insights into the viability of different machine learning data models. Graduates will also develop strong competencies in project management principles and the programming languages required to build and test machine learning algorithms in realistic scenarios.
"At StackAdapt, it took us nearly two years to hire the right people for our machine learning team," says Yang Han, Co-Founder & CTO of StackAdapt. "I'm excited to see York University tackle the skill gaps that the vast majority of machine learning specialists have, and enrich their students with the ideal strengths and experience needed to solve real world problems."
Registration for this program is open now, with the first session starting September 2018. Students should possess a minimum second-year undergraduate-level understanding of linear algebra, calculus, probability, and inferential statistics, and have experience with Python. The School of Continuing Studies at York University is proud to offer students industry-leading professional education, the most diverse educational experience in Toronto, and a world-class customer service support team.
For more information about the Certificate in Machine Learning, please visit our website or call +1 416 736 5616.
i York University School of Continuing Studies provides meaningful continuing education opportunities which combine guided instruction with practical application. Our programs are designed to develop the well-rounded professionals that employers value with both the deep discipline-based knowledge and the broad, cross-functional skills required to communicate and be effective within a multidisciplinary team. With a variety of options to suit your learning style and schedule, adding a recognized, respected credential such as a York University professional certificate has never been more convenient.
SOURCE York University
For further information: MEDIA CONTACT: Christine Brooks-Cappadocia, Director, Continuing Professional Education, Phone: 416.736.5449, Email: email@example.com