With the rapid development of artificial intelligence (AI) technology, learning AI-related skills has become a popular choice for job seekers and professionals. According to Coursera's latest "2025 Career Skills Report," the demand for AI courses has surged dramatically over the past year, with an annual growth rate of 866%. Analysis shows that enrollment has increased by 1100% for corporate employees, 500% for students, and 1600% for job seekers. This trend reflects the urgent demand for AI skills among employers.
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Why are AI skills so popular? The report indicates that about 75% of employers are using generative AI (GenAI), and 62% want their employees to have a certain level of understanding of it. Meanwhile, 22% of recruiters have updated job descriptions to align with AI-related skill requirements, and this percentage is expected to rise further by the end of the year. A survey by Amazon Web Services (AWS) shows that by 2028, 92% of companies plan to adopt AI-driven solutions. Notably, 73% of employers consider hiring talent with AI skills a priority, but nearly 75% of employers say they cannot find the talent they need.
According to Indeed, individuals with generative AI skills can see salary increases of up to 47%. In various fields, particularly in sales and marketing (43% salary increase), finance (42%), business operations (41%), legal compliance (37%), and human resources (35%), the salary growth is most significant. Therefore, professionals need to actively pursue these skills to enhance their career competitiveness.
Based on an analysis of 5 million learners by Coursera, here are the top 10 in-demand AI skills for 2025 and their definitions:
1. Generative AI - Using AI to generate content such as text and images.
2. Artificial Neural Networks - Building computer systems that mimic human brain learning.
3. Computer Vision - Teaching computers to "see" and understand images.
4. PyTorch (Machine Learning Library) - Using this tool to build powerful AI applications.
5. Machine Learning - Teaching computers to learn from data.
6. Applied Machine Learning - Using machine learning to solve real-world problems.
7. Deep Learning - Building advanced AI systems for complex tasks.
8. Supervised Learning - Training AI with labeled samples.
9. Reinforcement Learning - Training AI through trial and error.
10. Machine Learning Operations (MLOps) - Effectively managing and deploying machine learning systems.
There are various options for learning these AI skills. Some choose to attend boot camps or obtain degrees to network with other AI enthusiasts, while most prefer to learn through online courses and certifications, which are convenient and cost-effective. Platforms like IBM SkillsBuild (completely free), Coursera (some courses free, financial aid available for discounts), and Codecademy (offering relatively affordable courses through a subscription model) provide opportunities for learning.
Enhancing one's value in the workplace requires continually updating skill sets. Although not all AI skills are related to individual career goals, learning new skills is undoubtedly an important step in career development.
Key Points:
🌟 The demand for generative AI has surged in the past year, with a significant increase in employers' appetite for AI skills.
💰 Mastering AI skills can lead to salary increases of up to 47%, especially in fields like sales, finance, and business operations.
📚 Online learning platforms provide convenient access to mastering AI skills, catering to the learning needs of diverse groups.
