Artificial Intelligence
LLM & Generative AI Engineering
Design, fine-tune and deploy large language models for production.
About this course
This course covers transformer architecture, prompt engineering, RAG pipelines, fine-tuning with LoRA/QLoRA, LangChain, vector databases, AI safety, and deploying LLMs on AWS/Azure/GCP.
Learning roadmap
1
Transformer architecture
Attention mechanism, tokenization, embeddings
2 weeks
2
Prompt engineering
Zero-shot, few-shot, chain-of-thought, RAG pipelines
2 weeks
3
Fine-tuning & RLHF
LoRA, QLoRA, PEFT, instruction tuning
3 weeks
4
LLM deployment
LangChain, vector DBs, API serving, cost optimization
2 weeks
5
AI safety & exam prep
Hallucination mitigation, guardrails, practice tests
3 weeks
Certification details
Generative AI Engineer Certificate
Issued by Various / Coursera / DeepLearning.AI ·
Valid for 2 years ·
Exam code: GenAI-001
60 questions · 90 min · Scenario-based · Cost: USD 200
Globally recognized
Market demand
Fastest growing role 2024
Industry ranking
Salary range (annual, USD equivalent)
Career growth path
AI Research Scientist
Expert
Interesting facts
GPT-4 was trained on over 1 trillion tokens of text data from the internet.
The generative AI market is expected to reach $1.3 trillion by 2032.
Prompt engineering has become one of the highest-paid skills in tech in 2024.
LLM engineers at top tech companies can earn $200K–$400K total compensation.
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