Google Cloud on Wednesday announced class is open for AI students.
The lesson plan comes amid a steep learning curve for most organizations: 62% admit they don’t have the expertise to take full advantage of AI.
“As the leader of learning for Google Cloud, the only thing that surprises me about that number is how low it is,” Erin Rifkin, managing director of Google Cloud Learning, said in a blog post Wednesday. “I meet with customers every day, and 100% of them flag some kind of AI skills gap.”
The new generative AI learning paths and courses are designed to equip technical professionals, according to Google. The company has divided the course into four buckets:
Build and modernize applications with generative AI. This teaches how to enhance projects and build end-to-end applications on Google Cloud through the power of generative AI. It includes “essential techniques and tools to integrate GenAI capabilities seamlessly” into the development workflow.
Integrate generative AI into your data workflow. Instructs how to use BigQuery Machine Learning for inference, how to work directly with Gemini models in BigQuery, and how to improve a data team’s efficiency via Gemini. The course features a new course on boosting productivity with Gemini in BigQuery to assist in the data-to-AI pipeline.
Deploy and manage generative AI models. This course teaches how to manage the entire lifecycle of GenAI models — from development and deployment to monitoring — including introductions to responsible AI for developers. The path also features a new course on security for AI models.
Generate smarter generative AI outputs. Instructs how to build applications that generate text and visual content using GenAI. Students will learn to develop an AI project on Google Cloud, use diffusion models for image generation, and build search applications with Vector Search and embeddings. It also teaches how to “dive deeper into multimodal prompts and Multimodal RAG with Gemini.”
The courses from Google come amid a significant gap in upskilling and reskilling AI knowledge as the technology is rushed into companies. Indeed, some states like California are pushing training for employees and educators.
About 70% of AI talent needs to update their skills, according to one estimate this year, and yet many technical professionals don’t have the training they need to move from theory to practice and integrate AI into their everyday work.
More than half of IT functions (51%) lack skills to deliver AI, according to a global study of chief information officers, Ken Wong, president, Solutions and Services Group, Lenovo Group, said in an interview.
What is more, new data from Cognizant and Oxford Economics’ New Work New World study shows most organizations (54%) are focused on upskilling employees for roles that critically need AI knowledge. Nearly half (44%) prefer to reassign employees within the organization, and 32% are investing in tools and training to help workers transition into new roles.
“AI upskilling can have a net positive impact on business efficiency if leaders approach it with an outcomes-driven lens, rather than falling victim to AI hype,” Wendy Johansson, co-founder and chief operating officer at MiSalud Health, said in an email. “Defining exactly how AI can enable existing roles in an organization is critical to developing and choosing an upskilling plan.”
Added Kjell Carlsson, head of AI strategy at Domino Data Lab, “As companies rapidly adopt AI, upskilling employees becomes critical. But it has to come from both the top and the bottom. Leadership needs to make it a priority, to make it part of team and individual goals, and to reward managers that actively support the skill development of their teams.”
