Should I study artificial intelligence (AI)?

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AI: Here, There, and Everywhere

You're hearing a lot about AI everywhere. AI is short for "artificial intelligence" or "augmented intelligence." AI is the use of machines to digest large amounts of data to recognize patterns, and make "human" like predictive decisions.

AI is already impacting how we live, work, and play. It’s not a matter of “if” AI is going to impact your life because it already is.

AI is a game changer and will impact your life today and in your future. Taking AI courses will bulletproof your future.

What Matters To You?

Getting a Job

Many industries are embedding AI into their products and services such as education, healthcare, financial services, manufacturing, entertainment, e-commerce, and more.

AI will unlock the doors to jobs, knowledge, wealth, and resources. To learn more about how and where AI is being used in different industries, check out the NVIDIA GTC 2024 Conference.

Making Your Work Life Easier

Leverage AI in with your job skills so you can be more creative and efficient. Why not let AI do the "grunt work?"

This will give you more time to focus on what matters the most to you.

Using AI for Good

AI is a double-edged sword. It can be used for good or bad! Understanding "responsible AI" and AI's limitations will help you make wise decisions when you use AI.

Start Planning Your AI Future Now!

• Get comfortable with AI conversations.

• Build your AI literacy to understand key AI terms, concepts, applications, and ethics.

• Check out this guide for beginners from Data Camp: What is AI Literacy?

6 AI Career Trends

Artificial Intelligence (AI) Engineer

• Use artificial intelligence (AI) and machine learning to create applications and systems, enhancing organizational efficiency by solving real-world problems.

• Through data-driven algorithm training, AI engineers contribute to cost reduction, productivity enhancement, profit maximization, and informed business decision-making.

Machine Learning (ML) Engineer

• Research, construct, and design AI systems for machine learning, while also maintaining and enhancing current AI technologies.

• Collaborate closely with data scientists, conducting experiments, statistical analysis, and developing robust machine learning systems to advance AI capabilities.

Robotics Engineer

• Specialists in creating robotic applications for sectors such as automotive, manufacturing, defense, and healthcare, responsible for designing new products and assembling prototypes.

• May supervise robot production on-site or assess their real-world performance, integrating mechanical and electrical engineering with computer science.

Software Engineer

• Develop diverse software solutions, ranging from computer games to network control systems, utilizing various programming languages, platforms, and architectures.

• Enhance digital systems by testing, refining, and maintaining software, a fulfilling role for those with analytical skills and a passion for problem-solving.

Data Scientist

• Identify critical questions for organizations and devise strategies to answer them using data analysis, often developing AI predictive models to anticipate patterns and outcomes.

• Utilizemachine learning techniques, data scientists work to refine data quality and enhance product offerings.

Quantum Computing Engineer

• Create quantum algorithms — complex instructions that allow quantum computers to perform calculations much faster than traditional computers.

• Algorithm testing and troubleshooting to improve accuracy and quality.

Resources

Find more information on AI job trends, salaries, and detailed learning path:

• 6 AI Jobs to Consider in 2024

• Top 10 Jobs to Opt for in 2024

• Top Quantum Computing Jobs & Careers in 2024

Bachelor’s and master’s degrees in AI are key for learning about the field, acquiring essential skills, and earning a valued credential. AI degree programs are increasingly available at both undergraduate and graduate levels.

A bachelor’s degree in AI may involve majoring in AI or related fields such as computer science, with a focus on AI courses.

Completing a bachelor’s degree in AI typically requires 4-5 years of full-time study. You may study in-person, hybrid, or remotely.

Possible AI Bachelor Degree Combinations

AI Major

• More universities are offering a bachelor of science in artificial intelligence combined with machine learning within computer science departments.

• Focuses on computer systems fundamentals, mathematics, algorithms, and programming languages.

AI Minor

• Universities may offer an AI minor, enhancing a broader bachelor’s degree, such as in computer science, with a specialized focus on artificial intelligence.

Other Majors

AI is a relatively new academic field, so students might explore broader majors that incorporate AI coursework:

• Computer science is widely available and may offer AI courses or tracks within its curriculum.

• Data science often includes AI and machine learning.

• Robotics and engineering degrees often have AI and machine learning courses.

AI Master Degrees

• An AI master's degree allows for more in-depth learning with full-time programs lasting 1-3 years.

• Master of science programs might offer AI study options.

• Go beyond the basics to cover advanced topics like ethics, deep learning, with coursework in NLP (natural language processing) and machine learning for signal processing.

• Studies are more tailored to various industries.

To Degree or Not Degree?

Pros

• An accredited degree is widely recognized and can be used as credit toward your master's degree or professional continuing education credit.

• Your workplace may sponsor part of the program cost.

Cons

• It can be expensive and can lead to student loan debt.

• Programs have longer completion times.

• It can be less flexible when it comes to your schedule.

Alternatives to earning your degree in AI

MOOC

Massive online open courses (MOOC) offer flexible and self-paced learning to gain a basic understanding or delve into specialized advanced topics.

Coursera's AI for Everyone or IBM’s Introduction to AI are worth exploring.

Professional Certificates

Professional certificates are a series of MOOCs over months to earn a verified credential for your resume and LinkedIn.

Examples of Coursera's AI professional certificates are IBM Applied AI or Google Data Analytics Professional Certificate. 

Bootcamps

A part/full-time bootcamp is a short and fast-paced specialized training course. It focuses on hands-on job ready skills and may last for 3-6 months.

Explore some at EDx AI bootcamps

To Bootcamp or Not?

Pros

• Shorter time commitment.

• No bachelor/master's degree prerequisites.

Cons

• Information overload in a short time period.

• No scheduling flexibility, as courses are on a fixed schedule.

Self-directed Learning

Learners take the initiative for their own learning process by identifying their learning goals, educational resources, learning strategies, and evaluating their learning outcomes.

Check these online self-directed course links:

• Linkedin Learning AI Courses

• Google AI Essentials Course

• Oxford AI Program

• Microsoft AI for Beginners

Self-directed Learning or Not?

Pros

• Highly customizable with flexible learning content and scheduling.

• Builds initiative and self-discipline.

Cons

• Lack of structure may not work well for some learners.

• Limited instructor guidance.

Resources

• Explore the GenAI Learning Hub and filter courses by topic area, course difficulty, price, and student reviews.

Ask Yourself 6 Questions

1. What AI topic and course difficulty level meet your current needs? Beginner, intermediate, or advanced?

2. What are the course prerequisites — and can these courses be used as credit in a future specialization or advanced degree program?

3. What are the course reviews from other students?

4. What is the course length and your budget?

5. What course delivery method suits you and your lifestyle best? In-person, hybrid, or remote?

6. Do you want a broad AI overview, a deep dive into a full degree program, or a course on a specific AI topic?

Take Baby Steps

• Follow AI thought leaders on social media like Let's Learn AI Together with Alex Wang.

• Watch this YouTube video from PechaKucha, Seattle: Community Powered Conversations on the Future of AI

• Play with GPT Models such as CoPilot, ChatGPT, Gemini, and Perplexity, or test drive other generative AI-based tools from this AI directory link.

• Test the Khan Academy's AI driven co-learning pilot: a Chatbot called Khan Amigo

• Learn more about the Perils of AI.

AI Essentials

• Establish basic AI literacy. Pick a beginner-level AI fundamentals course.

• Sharpen your prompt engineering skills. Taking a prompt engineering course can make using your generative AI tools a breeze. Prompt engineering is a fancy way of saying "How do we build a better prompt or question to get better answers?" 

• Build your AI terminology. learning AI terms is like learning another language. Learn basic terms to help you pick your courses and to increase your AI literacy. Visit the Coursera AI - A to Z Glossary.

Do some self-reflection about how AI can help you in your current role or new trending AI roles in your company.

For example:

• Do you want to write, research, email, or code better? Check out the GenAI Hub for Top AI Applications to enhance your creativity, productivity, and lifestyle.

• At your workplace, what kind of AI or data roles are posted that grab your interest?

If you're ready to study AI, leverage these learning tips for success: