Program profile · official sources
Introduction to LLaMA
365 Data Science's 'Introduction to LLaMA' is an intermediate course instructed by Dr. Jaleed Khan, focusing on Meta's open-source LLaMA models. With a headline duration of two hours, the curriculum guides students through running lightweight LLaMA architectures in Google Colab, controlling text generation via decoding parameters, and applying prompt engineering strategies. Learners delve into evaluation, ethical AI challenges, and parameter-efficient fine-tuning using LoRA and QLoRA before deploying a real-time LLaMA-powered API. The course includes 34 lessons, 30 exercises, and practice exams, granting 4 CPE credits. Passing the final 30-minute exam with 60% or higher confers a verifiable certificate. Intermediate Python skills are required.
Facts checked 27 Sep 2026
- Price
- See pricing
Price observation recorded 27 Sep 2026 (not a current price): No total course price is stated. The platform-wide Self-Study plan displays a regular comparison price of $36/month, an observed $12.50/month billed annually offer, and an FAQ mentions a $29/month rate, as observed in United States captures dated 2026-09-27. ISO currency and a separately monthly-billed amount were not established; these subscription rates are not treated as a source-checked completion total. Certificates are included with the Self-study learning plan.
- Time
- 2 hours
- (provider headline; module and exam timings listed separately)
- Level
- Intermediate
- Credential
- Provider-issued certification
Verifiable credential with Credential ID and Credential Link; sharable on LinkedIn/resumes; downloadable upon passing. Certificates are included with the Self-study learning plan.
- Prerequisites
- Python (version 3.8 or later), Hugging Face Transformers library, and a code editor or IDE (e.g., VS Code or Jupyter Notebook) Intermediate Python skills are required. Familiarity with large language models (LLMs) or Hugging Face tools is helpful but not mandatory.
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
- Duration
- 2 hours (provider headline; module and exam timings listed separately)
- Level
- Intermediate
- Format
- 100% online, self-paced course
- Credential
- Provider-issued certification
- Prerequisites
- Python (version 3.8 or later), Hugging Face Transformers library, and a code editor or IDE (e.g., VS Code or Jupyter Notebook) Intermediate Python skills are required. Familiarity with large language models (LLMs) or Hugging Face tools is helpful but not mandatory.
Sources ↗
No accepted numeric price in this registry. 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 to LLaMA
- Deep Dive into LLaMA
- The Art of Prompting and Fine-Tuning
- Conclusion
- Course exam
Prerequisites: Python (version 3.8 or later), Hugging Face Transformers library, and a code editor or IDE (e.g., VS Code or Jupyter Notebook) Intermediate Python skills are required. Familiarity with large language models (LLMs) or Hugging Face tools is helpful but not mandatory.
What you actually do
What the credential is
- Credential type
- Provider-issued certification · 365datascience.com / introduction-to-llama
- Credential
- Course Certificate · 365datascience.com / certificates
- Issuer
- 365 Data Science · 365datascience.com / certificates
- Sharing
- Verifiable credential with Credential ID and Credential Link; sharable on LinkedIn/resumes; downloadable upon passing. Certificates are included with the Self-study learning plan. · 365datascience.com / certificates
- Exam requirement
- Pass the course exam; general certificate terms state 60% or above. Certificates are included with the Self-study learning plan. · 365datascience.com / certificates
- Credential expires
- provider does not state · 365datascience.com / introduction-to-llama
- Renewal
- provider does not state · 365datascience.com / introduction-to-llama
Who should skip it
- Check the course-specific preparation before enrolling: Python (version 3.8 or later), Hugging Face Transformers library, and a code editor or IDE (e.g., VS Code or Jupyter Notebook) Intermediate Python skills are required. Familiarity with large language models (LLMs) or Hugging Face tools is helpful but not mandatory. · Official source · 2026-09-27
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Related by topic or level.
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Change log
- : Initial recorded review of official program details. · Source
Cost details
Requires Python 3.8+, Hugging Face Transformers, Google Colab, and a code editor. Colab compute costs and total completion prices are not quantified by the provider.
Official source · 2026-09-27