10 ways to get started with AI

It's easy to feel left behind in the field of artificial intelligence . If you don't know how to integrate tools like ChatGPT into your business, don't understand the difference between Machine Learning (ML) and Natural Language Processing (NLP), or feel overwhelmed by all the latest AI news, you might think you're missing out. Luckily, that's not true. AI is just getting started. Business breakthroughs, groundbreaking advancements, and a whole new level of efficiency await professionals like you to discover today.

 

10 ways to build a business and career in the field of AI.

1. Read about AI trends and experiment with different tools.

 

According to Allie K. Miller, one of the most influential figures in the field of AI: 'Start by enriching your knowledge.' Listen to those who have experience in the field and put that understanding into action by actually experimenting with the tools. Make sure theory leads to practice.

"Start with AI tools like ChatGPT and Perplexity AI," Miller added. "Make learning AI a habit and stay informed. It will benefit you when you want to leverage the value of AI." It's never too late to start learning how to apply this technology to your work and career.

Time required: A few hours each week. Cost: 0 VND

2. Predicting job development

Predict the future of a specific role by evaluating your current position. 'Go to LinkedIn or Indeed and search for AI-specific versions of your current role,' Miller advises. 'If you're currently in sales, look at sales positions in the AI ​​field. Then, analyze the gap between the roles you find and your current skills, and work towards bridging that gap.'

The next version of your current role might require proficiency in several tools. 'A designer might need to know Adobe Firefly, or an account manager might need to know Salesforce's CRM-0.4% AI tools,' Miller adds, advising you to spend a few hours learning those tools, refer to YouTube for step-by-step tutorials, and update your resume once you're truly proficient. 'Understanding and using these tools proficiently will give you a significant advantage' with clients and employers.

Time required: 10 - 20 hours. Cost: Registration fees vary depending on the tool.

3. Find an AI mentor.

To move to the next level, find someone who has successfully transitioned from your current role to an AI-focused role (or roles). 'It could be a former colleague, a college classmate, or a stranger on social media,' Miller suggests. Ask for their advice on entering the AI ​​field.

 

Entrepreneurs can find AI versions of their current business models by searching online for tools in their field and looking for ideas on how their products/services could adapt. Either way, leverage the experience of others to shape your own model.

"Seek specific advice that is relevant to your role and act accordingly," Miller added.

Time required: Over 10 hours of searching, contacting, scheduling, and connecting. Cost: 0 VND. Resource: Another person.

4. Attend conferences or events related to AI.

There's a lot you don't know. Dig deeper by attending a conference and broaden your horizons with new and exciting technological concepts you may not have encountered before. Meet new people and understand their work. "Conferences can be a great advantage for networking, meeting recruiters, and learning about the direction of this technology," Miller explains.

Approach the opportunity with an open mind, take plenty of notes, and reconnect with everyone whose work catches your attention.

Time required: 3-5 days. Cost: Conference entrance fee and travel.

5. Take courses on AI.

Although AI is rapidly changing formal education, Miller believes that 'certificates can open many doors'. Don't just rely on self-learning; find courses that align with your career goals and 'formalize with certifications when necessary'.

If you're an aspiring Machine Learning engineer, 'try Python courses from Free Code Camp, ML crash courses from Google and Fast.ai, or ML courses from Andrew Ng,' Miller advises. If you're not an engineer, look for courses like ' What is Generative AI? ' on LinkedIn Learning, Andrew Ng's 'AI for Everyone,' or take Miller's in-depth 'AI for Business Leaders' course on Maven. There's also Heather Murray's AI course for non-tech people.

Time required: 2 weeks to 6 months. Cost: Course price.

6. Implement AI in your company.

Once you've mastered the fundamentals, you can build your portfolio and start innovating. 'Start applying AI meaningfully to your current role,' advises Miller. 'For example, a data analyst could suggest AI tools for data transformation, or learn a zero-programming platform to build machine learning predictive models. A customer support manager could guide their team in adopting customer service tools like Zendesk or creating a reminder repository for common support needs.' This is applying AI in practice. Use your ingenuity to find the tools, then track the impact (both qualitative and quantitative) on your team's performance.

 

If you run your own company, empower your team to increase productivity with AI and find solutions together. Prioritize solutions that deliver positive and meaningful results, such as freeing up time to work on new ideas that will help grow the entire business. 'Be proactive and create opportunities for real, hands-on project work,' Miller says, whether you're building within your own role or across the entire enterprise.

Time required: Several weeks to several months. Cost: Enterprise-grade AI tool subscription fee. Resource commitment: Consensus from the team and/or management.

7. Participate in a side project on Machine Learning (ML)

If you want to transition into artificial intelligence (AI) but aren't ready to take the leap from your current job, consider 'participating in an external AI collaboration project'. Miller suggests 'joining Slack or Discord groups, contributing to open-source communities via GitHub, or leveraging LinkedIn groups'.

Be proactive, but don't be reckless. 'Choose projects that align with your interests, such as a sports forecasting model if you're a basketball fan or a botany web application if you're a nature lover. I know hundreds of people building AI applications for friends or family,' she added. Showcase your skills and meet new people. You never know what you might create together.

Time required: Evenings and weekends for several months. Cost: Using an API or subscribing to a tool. Resources needed: An external team.

8. Start your own Machine Learning project.

"For those with self-motivation, initiating their own AI project can be incredibly rewarding and a great channel for showcasing creativity," Miller said, advising that you should take advantage of every spare moment, emphasizing the quality of time over the quantity. Learning from the basics is a great way to understand Machine Learning, from which you can build an AI-first business or integrate AI into your role with a solid foundation.

"This option is typically for engineers," Miller explained, "but non-technical people can look to platforms that don't require programming, such as Builder.ai, Bubble.io, or MindStudio, or collaborate with a development partner to bring the idea to life." Executability is key, but getting started is the hardest part.

 

Time required: Evenings and weekends for several months. Cost: API usage or tool subscription, manpower.

9. Working with an AI startup company

"Nothing compares to hands-on learning, and working at an AI startup is like riding a unicycle through the jungle. Unpredictable but incredibly exciting," Miller said. Collaborating with a startup is a great way to understand the complexities of working in an AI-based company.

"Make sure there are no conflicts of interest with your current role and conduct thorough due diligence to learn about the team and investors," Miller suggests, then roll up your sleeves and don't hesitate. She adds that this approach might initially involve a lower salary until you've proven your capabilities and built a strong portfolio.

Time required: Part-time or full-time work is possible.

10. Establish an AI company.

"This is the most challenging and ambitious path, and it demands dedication, risk-taking, and resilience," Miller explained. You need to be fully committed to have any hope of success. "90% of startups fail, so make sure your motivation isn't just financial rewards," she added.

Even if your AI company doesn't succeed, you'll learn a great deal and build valuable relationships. "The potential for impact and satisfaction alone is worth it," Miller said. If you think you're capable, find a core customer base and solve their problems in an AI-based way. Listen to their feedback and find the right fit between your product and the market.

Time required: Full-time or more. Cost: Varies greatly (tens to hundreds of millions of VND) depending on the product and team.