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How to learn AI

Explore practical steps for learning AI, from foundational principles to advanced concepts. Build AI skills that enhance productivity and attract attention from employers.

By: James M. Tobin, Edited by: Rebecca Munday, Reviewed by: Jeff Le

Published: September 17, 2025


Artificial intelligence (AI) is arguably the decade's most important technological development. In short order, AI has become integrated into industry, education, healthcare, and many other facets of everyday life.

Given the emerging landscape, mastering AI is a savvy move. Find out how to learn AI, whether you're a complete beginner or an experienced practitioner looking to reach the next level.

How to get started in AI

1. Read articles about AI

Experts have a lot to say about AI. Reading articles from AI researchers and thought leaders is a free, accessible way to gain insights and explore a diversity of perspectives on this transformative and fast-changing technology.

OpenAI's news portal, Google's DeepMind blog, Anthropic's Newsroom, and the Berkeley Artificial Intelligence Research blog are all excellent sources of AI news and information.

You can also explore AI articles in leading publications like TechTarget, Wired, and the Journal of Artificial Intelligence Research.

2. Take an online AI course or certificate

Structured, instructor-curated, self-paced learning pathways provide direction and deliver curated educational content targeting key concepts and specific skills. Your options include everything from standalone courses for beginners to advanced degree programs.

You can easily connect with a wealth of AI learning opportunities on edX: Explore courses, certificates, Executive Education programs, and AI-focused degrees.

3. Practice prompting AI using best practices

Effective prompts are the key to unlocking AI's full potential. Through practice and by applying a purpose-built prompting framework, you can dramatically improve the quality and relevance of your results.

Prompting frameworks include five main elements:

  • Setting the context or defining a role for AI to assume
  • Assigning a specific task within that context
  • Providing references for AI to use in task completion
  • Requesting a precise output format
  • Refining prompts through iteration to improve results

Experiment by starting with simple inputs, applying the framework, comparing output quality, and iterating to enhance your results.

4. Dive deeper into AI's capabilities with coding

Coding helps AI transform raw inputs into intelligent outputs. AI-specific coding applications include:

  • Using algorithms to guide machine learning models.
  • Cleaning and structuring data to improve output quality and accuracy.
  • Creating scripts to automate labor-intensive tasks.
  • Transforming raw AI into user-focused services and software applications.

To get started, you can learn Python: Computer scientists widely consider Python to be the most useful and versatile programming language for AI applications.

AI algorithms also rely on linear algebra, calculus, probability, and other branches of mathematics. Building strong math foundations can also help.

5. Consider furthering your education and starting a career in AI

If your initial efforts spark a stronger interest in AI, you may want to consider more in-depth learning options and in-field career paths. With global employers actively recruiting AI talent, a bachelor's degree or master's degree could be a strong addition to your résumé.

Also, consider emerging career paths in AI, such as prompt engineering, ethics, compliance, and research. You can pursue a degree in AI or start building skills with prompt engineering courses.

How long does it take to learn AI?

Depending on your background and career goals, it may take you anywhere from a few weeks to a few months to become proficient with AI applications.

If you start as a complete beginner, it will likely take multiple years to master AI-focused computer science completely, especially since new developments in AI are always emerging.

If your goal is to integrate AI skills, like prompt engineering, into your existing non-programmer role, refining those skills may take several months.

Established tech professionals and learners with a strong working knowledge of the math and programming languages that AI uses have an advantage. They may need less time to gain fluency in applied AI skills.

To launch your journey, consider these learning pathways and compare their respective timelines:

4-12 weeks
Courses
2-10 months
Certificates
6-8 weeks+
Executive Education
1-6 years*
Degree programs

*Bachelor's programs take 4-6 years; master's programs take 1-3 years

Learning timeline for people who want to use AI models

1
0-1 months: During your first month, learn about the different types of AI and engage with beginner-friendly AI tools. Explore the various ways professionals in your field use AI, and develop your knowledge of key concepts like natural language processing.
2
1-6 months: AI courses and certificate programs structure your learning, giving it direction and focus while providing support. They can help you build core skills as you learn more about topics like prompting frameworks, productivity applications, and business AI integrations.
3
6-12 months: With solid foundations in place, you can engage with the cross-deployment of multiple AI tools, consider the ethics of AI implementations, and use targeted methods for improving accuracy and reducing bias.
4
1+ years: At this stage, you can start developing AI-enhanced workflow systems and consider further education to advance your proficiency. You can also build a specialization in areas like AI-guided content creation, prompt engineering, and AI upskilling for employees. AI trends and capabilities change rapidly, so make sure you stay updated on the latest developments as you continue to learn.

Learn AI with edX

Now that you know how to learn AI, identify a learning pathway and take action. Consider these options, which are readily available through edX partner providers:

  1. Take AI courses in specific focus areas, or complete an AI certificate program.
  2. Consider AI Executive Education, targeting topics like mitigating AI risks or debunking myths about AI in business.
  3. Prepare for a career in AI by pursuing an undergraduate or graduate degree.

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