As a Product Engineer and International Public Speaker, I help mission-driven startups build inclusive engineering platforms that scale. And I am a visibility strategist for Women in Engineering and Science!
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Upcoming events and resources to break into the tech pipeline!
On the 17th, learn from Camille Eddy and Shenea Leven about how they navigated their way into top tech companies (i.e. Google, Ebay, Nvidia) and how they are currently building their own startups. Join us on zoom!
For any engineer or manager that would like to present best use cases of AI to their teams or integrate ethical AI into their practice it can be helpful to learn of practical implications of the technology.
A lot of students and entry level job seekers struggle with gaining experience to get the job. I put together a list of projects you can start! Volunteer for a political group or design a project tech firm.
"When tackling culture bias in Artificial Intelligence (AI), it is important to understand how much we use AI in our everyday lives. There are quite a few applications, and while they all have different names, a few of them are becoming more familiar to the general public. There are fields such as machine learning, face recognition, computer vision, virtual and augmented reality. unc."
"Growing up, Camille Eddy wanted to be an astronaut. She went to space camp, loved Star Trek, and was even mentored by former NASA mission specialist Barbara Morgan. Part of being an astronaut, Eddy discovered, involved developing STEM skills. So she began programming at age 12, started her own web design business at age 17, and went to Boise State University in Idaho to major in mechanical engineering. While most college students rely on loans or parental support to pay for their university housing, Eddy used the profits from her web design business. "
"When tackling culture bias in Artificial Intelligence (AI), it is important to understand how much we use AI in our everyday lives. There are quite a few applications, and while they all have different names, a few of them are becoming more familiar to the general public. There are fields such as machine learning, face recognition, computer vision, virtual and augmented reality. unc."
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