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Women in professional roles want better generative AI training.
That’s the conclusion from a new study commissioned by Amazon Web Services (AWS), which found that 77 percent of women in professional roles in the U.S. want to learn how to integrate generative AI skills into their current workflows. However, 42 percent also state their employer isn’t offering adequate training in generative AI. (The data is based on a survey of 999 women by Morning Consult.)
In fact, there are multiple factors holding back women in professional roles from fully embracing AI. “The top barriers preventing women from developing generative AI capabilities include not knowing where to start or what skills to focus on (35 percent), uncertainty around how generative AI applies to their role (31 percent), lack of access to training resources (27 percent), and limited time due to busy schedules (26 percent),” reads the AWS summary of the findings. “To overcome these hurdles, women have identified employer-sponsored training (53 percent), affordable online courses (50 percent), flexible learning options (47 percent), and free or low-cost training programs (42 percent) as top motivators to generative AI skills development.”
Some 45 percent of respondents also said there isn’t a broader push by their organizations to integrate AI into their roles, which is a bit surprising when you consider the economy-wide interest in AI.
Launching Your AI/ML Path
A solid foundation in AI knowledge is essential—tailored to your goals, of course. If you aim to simply use existing AI tools effectively, concentrate on prompt engineering. However, for those who intend to develop and refine AI systems, acquiring these core skills is crucial:
- Programming Expertise: Develop proficiency in Python, the primary programming language for AI/ML.
- Mathematical Competence: Gain a strong understanding of linear algebra, calculus, and probability.
- Data Science Basics: Learn the techniques of data cleaning, exploration, and visualization.
Selecting Your Learning Approach
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Online Education: Leverage platforms like Coursera, edX, and Udemy, which provide diverse and affordable AI/ML courses with substantial support. Companies like Amazon also offer training and guidance for AI in the context of their respective platforms (such as AWS).
- Independent Study: Utilize complimentary resources such as YouTube tutorials, online documentation, and open-source projects.
Engaging in Hands-On Projects
Maintaining Currency and Building Connections
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Follow AI/ML News and Blogs: Keep abreast of the latest advancements and trends. Newsletters like AI Breakfast, Mindstream, and The Rundown AI are good resources.
- Join Online Forums: Connect with fellow learners, exchange knowledge, and seek assistance. Subreddits such as  r/AIAssisted and r/ChatGPT are good examples.
- Attend Industry Events: Network with professionals and broaden your understanding through conferences and meetups.
Even if your organization isn’t willing to help train you, online resources can help you quickly boost your AI skills. The world is changing rapidly, and you should make every effort to gain a knowledge foothold in AI.