Top Artificial Intelligence Courses to Build Your Skills in 2025

• By Jennysis
• 10-09-2025
• Artificial Intelligence

Artificial Intelligence is transforming healthcare, finance, manufacturing, and entertainment. In 2025, demand for AI talent is at its highest, with companies actively hiring people who can build, deploy, and manage AI systems.

This guide presents seven leading AI certificate programs for beginners entering the field, working professionals upskilling for new roles, and experts seeking specialized training. Use it to find the program that fits your goals, experience, budget, and time commitment.

Factors to Consider Before Choosing an AI Course

• Career Goal: Decide if you want to become an ML engineer, data scientist, or AI product manager. Each path needs different depth and tools.
• Experience Level: Be honest about your knowledge in math, Python, and ML basics so you pick an entry point that matches your current level.
• Learning Style: Choose between structured cohorts with mentorship or flexible, self-paced learning.
• Budget: Free and low-cost options exist, while paid programs often add live support, projects, and career services.

1) PG Program in Artificial Intelligence & Machine Learning

Duration/Mode: 12 Months, Online.

Offered by: McCombs School of Business at The University of Texas at Austin.

Overview: The McCombs School of Business at The University of Texas at Austin’ Post Graduate Program in AI & ML: Business Applications is a 7-month online program with live mentorship. You’ll learn Python, machine learning, deep learning, NLP, computer vision, and generative AI while building hands-on projects; graduates earn a UT Austin certificate. The curriculum lists 200+ learning hours, 7 projects, and 20+ tools.

What Sets It Apart?

• University partner: The McCombs School of Business at The University of Texas at Austin
• Online format with a clearly stated 12-month duration on the card.

Course Link: artificial intelligence courses

2) The University of Texas at Austin (McCombs) – Post Graduate Program in AI & ML

Duration/Mode: Typically 7–12 months, online with mentorship and projects

Offered by: UT Austin, McCombs School of Business, in collaboration with Great Learning

Overview: A business-plus-technical curriculum that covers core ML, NLP, computer vision, and Generative AI with hands-on projects and career support, culminating in a McCombs certificate.

What Sets It Apart?

• University-backed credential from McCombs with project-based learning.
• Mentorship and career guidance designed for working professionals.

Ideal For: Professionals who want a recognized university certificate and a structured, project-heavy experience.

Course Link: Artificial intelligence course

3) Johns Hopkins University – Certificate in Applied Generative AI

Duration/Mode: 16 weeks, online

Offered by: Johns Hopkins University (Lifelong Learning / ExecEd)

Overview: A practitioner path into Generative AI that covers LLMs, prompt engineering, ethical and responsible AI, and domain use cases through hands-on labs and deployable project work.

What Sets It Apart?

• Research-driven faculty with emphasis on responsible AI practice.
• Applied projects across RAG, AI agents, and LLM workflows.

Ideal For: Professionals who want a rigorous, applied GenAI credential from a top university.

Course Link: Johns Hopkins – Applied Generative AI.

4) DeepLearning.AI – Generative AI with Large Language Models

Duration/Mode: About 3 weeks, online, created with AWS

Offered by: DeepLearning.AI (in partnership with AWS)

Overview: A focused, hands-on introduction to building with LLMs, including how transformers work, practical fine-tuning strategies, and deployment for real applications.

What Sets It Apart?

• Clear coverage of core LLM concepts with practical labs.
• Fast path to shipping small GenAI features or prototypes.

Ideal For: Engineers and analysts who want a quick, practical route into LLMs.

Course Link: DeepLearning.AI – Generative AI with LLMs.

5) Google Cloud – Generative AI Leader Certification

Duration/Mode: Self-paced prep; 90-minute proctored exam; exam fee $99 USD

Offered by: Google Cloud

Overview: A leadership-level certification that validates your ability to guide GenAI strategy, evaluate solution options, and drive responsible adoption using Google Cloud’s GenAI stack.

What Sets It Apart?

• Business-centric validation for managers and PMs.
• Official launch details and blueprint from Google Cloud.

Ideal For: Product leaders, consultants, and executives who must steer GenAI initiatives.

Course Link: Google Cloud – Generative AI Leader.

6) AI & ML PG Certificate Program (Great Learning)

Duration/Mode: 12 Months of learning content with live mentored learning and a 4-week capstone project.

Offered by: Great Learning — curriculum designed by The McCombs School of Business at The University of Texas at Austin faculty, and industry practitioners.

Overview: A comprehensive program covering AI, machine learning, and generative AI to help you start or transition into AI/ML roles. It includes Python & Gen AI prep work, as well as a Python Bootcamp for Non-Programmers, to bring beginners up to speed before the main coursework.

What Sets It Apart?

• Dual certificates from Texas McCombs and Great Lakes (as showcased on the page).
• Extensive GenAI coverage and live mentored learning.
• 27+ languages & tools highlighted in the curriculum.

Ideal For: Beginners and working professionals transitioning to AI/ML, including non-programmers who benefit from the built-in Python bootcamp.

Course Link: ai course

7) IBM – AI Engineering Professional Certificate (Coursera)

Duration/Mode: Multi-course professional certificate series, online and self-paced

Offered by: IBM on Coursera (with IBM Skills Network)

Overview: A job-oriented sequence covering ML algorithms, deep learning with TensorFlow/PyTorch, MLOps basics, and applied projects to build a public portfolio.

What Sets It Apart?

• Hands-on labs and projects across classic ML and deep learning.
• Clear pathway for engineers moving toward AI roles.

Ideal For: Developers and data professionals who want an applied, project-centric path to AI engineering.

Course Link: IBM – AI Engineering Professional Certificate.

Conclusion

Choose the course that aligns with your goal, baseline skills, and weekly bandwidth, then commit to consistent practice. Start small, ship projects, and document outcomes that you can show on your resume and LinkedIn. With the right program and steady effort, you can turn 2025 into a year of real, measurable progress in AI.