Career in AI | Which Career Option is the Best for Me?

Summary

In this video, the speaker explores various AI career paths, offering guidance to help viewers choose the right role based on their skills and interests. The decision tree begins by asking if you're skilled in coding, then branches into options like AI Engineer, Data Scientist, MLOps Engineer, or specialization in NLP/Computer Vision, depending on math and computer engineering skills. Non-technical roles such as AI Ethicist, Product Manager, and Sales Representative are also discussed for those without coding expertise. The video aims to help individuals navigate the rapidly expanding AI job market and find a rewarding career path.

Takeaways

• 😀 AI skills on your resume will significantly boost your career prospects in the AI-driven job market.
• 😀 Coding proficiency is a key factor in determining the right AI career path, but interest in coding can also open doors.
• 😀 MLOps Engineers focus on deploying and maintaining AI models and require strong coding skills but not heavy math knowledge.
• 😀 AI Engineers are responsible for building, deploying, and integrating AI models into existing technical systems. Strong coding and math skills are essential.
• 😀 Data Scientists excel in math and statistics, focusing on extracting insights from data and building models, with less emphasis on deployment.
• 😀 If you're strong in math and statistics but lack advanced computer engineering skills, a Data Scientist role may be a better fit than an AI Engineer role.
• 😀 NLP Engineers specialize in natural language processing and work on AI projects related to text, while Computer Vision Engineers focus on images and video.
• 😀 AI careers also offer specialized paths such as NLP and Computer Vision, which focus on specific domains within AI, such as language or visual data.
• 😀 Non-technical AI roles are also available for those who don't want to code. Key roles include AI Ethicist, AI Product Manager, and AI Sales Representative.
• 😀 AI Ethicists review AI projects for regulatory compliance, ethical concerns, and risks, ensuring AI is used responsibly and within legal boundaries.
• 😀 AI Product Managers serve as a bridge between technical teams (AI Engineers, Data Scientists) and business teams, requiring business acumen and technical understanding.
• 😀 AI Sales Representatives combine their sales expertise with AI knowledge to sell AI products, making it an ideal career for those who enjoy meeting people and solving business problems.

Q & A

Why is it beneficial to have AI listed on your resume?

Having AI on your resume will significantly benefit your career, as AI is booming across industries, and businesses are increasingly adopting AI technologies.

What is the first question you need to ask when deciding on an AI career role?

The first question you need to ask is whether you are good at coding, or if you have an interest in developing strong coding skills.

What role is recommended if you have strong coding skills but no interest in math and statistics?

If you have strong coding skills but do not have an interest in math and statistics, the recommended role is an MLOps engineer. This role focuses on coding but doesn't require heavy math and statistics.

What is the difference between an AI engineer and a data scientist in terms of skills?

AI engineers are responsible for building and deploying AI models, requiring strong computer engineering skills. Data scientists, on the other hand, focus on extracting insights from data and need stronger math and statistics skills but do not get involved in deployment as much.

What role should you pursue if you are skilled in math and statistics but lack strong computer engineering knowledge?

If you have strong math and statistics skills but lack strong computer engineering knowledge, the recommended role is a data scientist.

What are the two key specializations within AI engineering?

The two key specializations within AI engineering are NLP (Natural Language Processing) engineers, who focus on text-related AI projects, and computer vision engineers, who focus on image and video processing.

What are the three non-technical career options for individuals who are not interested in coding?

The three non-technical career options are AI ethicist, AI product manager, and AI sales representative.

What is the role of an AI ethicist?

An AI ethicist reviews AI projects to ensure compliance with laws and regulations, assesses the ethical risks of AI models, and ensures that AI technologies avoid biases and misuse.

What is the responsibility of an AI product manager?

An AI product manager acts as a bridge between the technical team (AI engineers, data scientists) and the business team, ensuring the successful integration of AI technology into products by understanding both business needs and technological capabilities.

Who is an AI sales representative best suited for?

An AI sales representative role is best suited for individuals with a sales background who are interested in learning about AI and using their sales skills to promote AI products to businesses.