Program profile · official sources
Intro to Federated Learning
DeepLearning.AI and Flower Labs introduce federated model training with Flower and PyTorch. The listed lessons cover the training process, tuning, data privacy and bandwidth. The page places this introductory course within a two-part series; the later federated LLM fine-tuning topics described in the overview are not treated as additional lessons in this course. Python, machine learning and LLM familiarity are stated for the intended audience. Free beta access and Pro accomplishments have separate boundaries.
Facts checked 15 Oct 2026
- Price
- Free
- (As shown in the United States on 15 October 2026, the visible page offers course access free for a limited time during the platform beta. The end date is not stated. Pro accomplishments are separate; no free credential, perpetual free access or Pro membership price is inferred.)
- Provider link
See price and enroll at DeepLearning.AI (official site) ↗
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- Time
- 1h18m listed course duration; individual activity estimates are rounded
- Level
- Beginner
- Credential
- Accomplishment with Pro
- Prerequisites
- A basic background in Python and machine learning and an understanding of LLMs are stated for the audience.
- Format
- Online course with video lessons and listed learning activities
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
Sources ↗
This program is free. It is not plotted on the logarithmic price scale. See the sourced pricing details below.
See the full registry price landscape. Prices retain their stated payment scope; they are not comparable completion costs.
What’s covered
- Introduction
- Why Federated Learning
- Federated Training Process
- Tuning
- Data Privacy
- Bandwidth
- Conclusion
- Quiz
Prerequisites: A basic background in Python and machine learning and an understanding of LLMs are stated for the audience.
What you actually do
- Introduction : 4m; Video; provider outline item, not a separately named module · Source
- Why Federated Learning : 18m; Video with Code Example; provider outline item, not a separately named module · Source
- Federated Training Process : 15m; Video with Code Example; provider outline item, not a separately named module · Source
- Tuning : 10m; Video with Code Example; provider outline item, not a separately named module · Source
- Data Privacy : 9m; Video with Code Example; provider outline item, not a separately named module · Source
- Bandwidth : 9m; Video with Code Example; provider outline item, not a separately named module · Source
- Conclusion : 1m; Video; provider outline item, not a separately named module · Source
- Quiz : 10m; Graded; provider outline item, not a separately named module · Source
What the credential is
- Credential type
- Accomplishment with Pro · www.deeplearning.ai / intro-to-federated-learning
- Credential
- Accomplishment with Pro · www.deeplearning.ai / intro-to-federated-learning
- Exam requirement
- A graded quiz is listed; its passing threshold and any separate final examination are not stated. · www.deeplearning.ai / intro-to-federated-learning
- Credential scope
- As checked on 15 October 2026, the course page identifies an accomplishment with Pro, not an explicitly named academic or professional certification. The capture does not establish an independent credential issuer, full completion thresholds, expiry, renewal or academic-credit eligibility. · www.deeplearning.ai / intro-to-federated-learning
Source differences retained
As checked on 15 October 2026, the official page gives differing information on the points below. Each reading is kept as found; none is reconciled.
- Duration: Visible course duration is 1h18m; same-course embedded metadata has generic courseWorkload PT1H. The visible duration is retained as text; no single numeric completion estimate is used. · Source
- Language: As checked on 15 October 2026, the same-course structured metadata states inLanguage="en" and availableLanguage=["en","jp","kr"]. English is retained; the additional literal codes do not establish whether they describe teaching audio, subtitles or another language option. No additional delivery language is verified. · Source
Who should skip it
- The page conditions the accomplishment on Pro membership; a free-access label does not establish that this recognition or all graded activities are free. · Official source · 2026-10-15
- The overview describes a two-part series. This introductory page lists only the seven introductory video lessons plus a quiz; part-two federated LLM fine-tuning is not recorded as an additional module here. · Official source · 2026-10-15
Alternatives in the registry
Related by topic or level.
- AWS Certified AI Practitioner (AIF-C01) : USD 100 (One initial exam attempt; check applicable regional pricing and taxes. Optional preparation and retakes are not included.) (price checked 4 September 2026); 90 minutes (exam only; not preparation time) (duration checked 4 September 2026).
- AI Fundamentals : DataCamp Premium : USD 35/month for course content, billed monthly at the regular price (price checked 8 September 2026); Approximately 9 hours (duration checked 8 September 2026).
- Introduction to Generative AI : Check official price; 45 minutes (duration checked 6 September 2026).
Change log
- : Initial source review from the dated US capture. · Source
See price and enroll at DeepLearning.AI (official site) ↗
Official site. No commission.