Women in Machine Learning: Deep Learning Workshop
Like so many areas in STEM the MLAI Industry is suffering from the Gender Gap. Paradoxically, there is a skills shortage in Australia for qualified people to be working in this area. We will run Deep Learning workshops exclusively for individuals who identify as female, building upon their current skill sets, making them a competitive candidate for a range of jobs in Machine Learning.
Despite the opportunities that MLAI can offer, there are also repercussions that need to be considered. Bias in data, privacy and how the technology will be used and important factors. Moreover the creations need to reflect the users who will benefit from it. With all this in mind it is crucial that more people who identify as females become involved in the industry.
We have developed the following program in a bid to do just that.
Python Office Hours
Dates: Various before 5th september
Location: VIrtual & Silverpond, Melbourne CDB
One of the few prerequisites for the Deep Learning Workshop is competency in the programming language python. This allows for the focus of the workshop to be on Deep Learning concepts and practical examples.
The Python “Open Hours” will be hosted at the Silverpond office, with the option able to engage remotely online. Efforts will be made to accommodate women with inflexible schedules or other considerations such as child care.
Deep Learning Workshop
Dates: 5th & 6th September
Location: Zendesk, Melbourne CDB
An intuitive understanding of the components of machine learning systems
Introduction to building neural networks in TensorFlow and TFLearn
Clear understanding of convolutions and representation learning
Experimenting with a model that learns representations of words
Practical real-world model development in TensorFlow
Dates: After 30th August
Location: Virtual and Melbourne CDB
To help you take your new skills to a new career, role or promotion we have
organised consultation with a careers professional.
Who Should Apply?
Women with a background in IT, data science or software engineering, who would otherwise be unable attend the program due to financial, caring, location or alike considerations
Bold Moves White Paper found that 56% of women in tech leave their jobs by mid career. Of those 51% leave the industry completely. We want to capture those women.