I’m a good example of someone who didn’t have cybersecurity experience coming into the field. But, my business skills include communication, relationship-building, project management, detail-orientation, and training. These skills made me a great fit for the security awareness and training role I applied for. As for the cybersecurity-related aspects, I learned those on the job. The rest, as they say, is history!
If you’re looking for a fulfilling, dynamic, and lucrative career where you’re learning all the time and using a diverse set of skills, look no further than cybersecurity. Here are some recommended steps to get started on your journey to learn cybersecurity skills and begin your career path.
Get your foundation: Learn about cybersecurity concepts and best practices. Use resources like Trailhead, the World Economic Forum, Fortinet, and the Global Cyber Alliance.
Develop your practical skills: Gain hands-on experience america phone number list through internships, projects, or a bug bounty program.
Network: If you don’t know anyone in the cybersecurity field, don’t worry. Salesforce’s Trailblazer Community has an entire group of people called Cybersecurity Trailblazers who can help along the way.Large companies are investing in enterprise LLMs, left and right. Why? These LLMs lay the foundation for AI tools that can chat with shoppers, detect fraud, diagnose medical issues, and much more.
Want to translate a product explainer in 10 languages in minutes, while staying true to your brand voice and tone? An enterprise large language model (LLM) can do that. Need to gauge the sentiment of your customer’s service interactions in real time? Tap an LLM. Want to analyze and summarize 500 pages of financial data in minutes? An LLM’s got you.
Clearly, LLMs hold enormous promise. In fact, the venture capital firm Andreesen Horowitz wrote that “pre-trained AI models represent the most important architectural change in software since the internet.”
What is a large language model?
Large language models (LLMs) are a type of AI that can generate human-like responses by processing natural-language inputs, or prompts. LLMs are trained on massive data sets, which gives them a deep understanding of a broad range of information. This allows LLMs to reason, make logical inferences, and draw conclusions.