By Quick answer: Which DeepLearning.AI courses are worth it in 2027?
- Non-technical — AI for Everyone, GenAI for Everyone.
- Foundations — ML Specialization.
- Depth — Deep Learning Specialization.
- LLMs — Generative AI with LLMs.
Key takeaways
- Andrew Ng's courses are known for clear teaching.
- Most can be audited free.
- Pair with projects or a cloud ML exam for job proof.
DeepLearning.AI, founded by Andrew Ng, makes some of the most popular AI courses online. They range from non-technical introductions to deep technical specializations. Here's which are worth your time.
Five DeepLearning.AI courses at a glance
Ranked for this reader. Costs and formats come from each issuer's own page, checked on 3 November 2026; prices change, so confirm before you book.
| # | Certification | Cost | Time | Prove it free |
|---|---|---|---|---|
| 1 | AI For EveryoneDeepLearning.AI / Coursera | Free to audit on Coursera1 | About 7 hours | Free test |
| 2 | Generative AI for EveryoneDeepLearning.AI / Coursera | Free to audit on Coursera2 | About 6 hours | Free test |
| 3 | Machine Learning SpecializationDeepLearning.AI & Stanford / Coursera | $49/mo Coursera plan3 | 2 months at 10 hours a week | Free test |
| 4 | Deep Learning SpecializationDeepLearning.AI / Coursera | Coursera plan4 | 3 months at 10 hours a week | Free test |
| 5 | Generative AI with Large Language ModelsDeepLearning.AI & AWS / Coursera | Coursera plan5 | 2 weeks at 10 hours a week | Free test |
Prove it free before you pay for an exam
Take the free test first. Pay for an exam only when you pass.
Every pick above has a matching free practice test on Science of Apps, one of the world's largest libraries of free certification tests (1,200+). Check your level before you pay for an exam, or add a verifiable credential to LinkedIn while you study. (Disclosure: we publish these tests; the certifications above earn us nothing.)
- AI Literacy CertificationPractise for AI For Everyone before you pay.Start free test →
- Generative AI Fundamentals CertificationPractise for Generative AI for Everyone before you pay.Start free test →
- Machine Learning Fundamentals CertificationPractise for Machine Learning Specialization before you pay.Start free test →
- Deep Learning CertificationPractise for Deep Learning Specialization before you pay.Start free test →
Each course, and who it's worth it for
- CourseraAI For EveryoneNon-technical learnersFree to audit on Coursera
- CourseraGenerative AI for EveryoneGenerative AI basicsFree to audit on Coursera
- CourseraMachine Learning SpecializationML foundations$49/mo Coursera plan
AI For Everyone
- Cost
- Free to audit on Coursera1
- Time
- About 7 hours
Non-technical AI literacy, about seven hours. Andrew Ng's non-technical course explains what AI can and can't do, how AI projects work and how to plan for AI in an organisation. It takes about seven hours, can be audited free on Coursera and is a strong first step for managers and non-specialists.
Best fornon-technical learners
Generative AI for Everyone
- Cost
- Free to audit on Coursera2
- Time
- About 6 hours
Generative AI basics, about six hours. Andrew Ng's short course explains how generative AI works, where it helps, where it fails and how to use it responsibly at work. It takes about six hours, can be audited free and suits non-technical professionals who use chat tools daily.
Best forgenerative AI basics
Machine Learning Specialization
- Cost
- $49/mo Coursera plan3
- Time
- 2 months at 10 hours a week
Supervised and unsupervised learning in Python, about two months at ten hours a week. Andrew Ng's specialization with Stanford teaches supervised and unsupervised learning, model evaluation and practical machine learning in Python. It takes about two months at ten hours a week and is widely regarded as the clearest structured start in ML.
Best forML foundations
Deep Learning Specialization
- Cost
- Coursera plan4
- Time
- 3 months at 10 hours a week
Neural networks and deep learning, about three months at ten hours a week. The Deep Learning Specialization covers neural networks, optimisation, CNNs and sequence models in depth. It takes about three months at ten hours a week, assumes machine learning basics and can be audited free on Coursera.
Best forneural networks
Generative AI with Large Language Models
- Cost
- Coursera plan5
- Time
- 2 weeks at 10 hours a week
LLMs with AWS, about two weeks at ten hours a week. DeepLearning.AI and AWS's course explains how large language models work, how to fine-tune and evaluate them and how to deploy them. It takes about two weeks at ten hours a week and suits developers and data scientists with Python.
Best forLLM skills
Which course for you?
| You are… | Take |
|---|---|
| Non-technical | AI for Everyone |
| Developer new to ML | ML Specialization |
| ML practitioner | Deep Learning, LLMs |
Table: Choosing a DeepLearning.AI course
How we ranked these picks
We assessed DeepLearning.AI courses by depth and fit to learner type. Times come from course pages, checked 3 November 2026.
Frequently asked questions
Are Andrew Ng's courses worth it?
Yes; they're widely respected for clear teaching.
Are DeepLearning.AI courses free?
Many can be audited free on Coursera; certificates need payment or aid.
Which should I take first?
AI for Everyone if non-technical; ML Specialization if technical.
Do employers recognise them?
They're well known; pair with projects for hiring.
Is there a free AI test?
Yes. Science of Apps offers free AI and ML tests.
Sources
- DeepLearning.AI — AI For Everyone, official page (checked 3 Nov 2026)
- DeepLearning.AI — Generative AI for Everyone, official page (checked 3 Nov 2026)
- DeepLearning.AI & Stanford — Machine Learning Specialization, official page (checked 3 Nov 2026)
- DeepLearning.AI — Deep Learning Specialization, official page (checked 3 Nov 2026)
- DeepLearning.AI & AWS — Generative AI with Large Language Models, official page (checked 3 Nov 2026)
- Checked November 4, 2026. Figures that change — fees, salaries, prices — are reviewed every six months; if something is out of date, tell us.
Where to go from here
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- Career guides by Science of Apps for 2027the Machine Learning Specialization review for 2027: is it worth it, who it's for and the best alternativesAndrew Ng's Machine Learning Specialization review for 2027: what it covers, about two months part-time, cost, who it suits and alternatives.
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