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Name: GENERATIVE AI & LLM ENGINEER
Rating: 5 (6734 reviews)

✅Best GENERATIVE AI & LLM ENGINEER Training Institute [Certified]

COURSE CURRICULUM

106+ Course Topics • Hands-on Labs • Real-Time Practice

MODULE 1: GENERATIVE AI & LLM FOUNDATIONS

01 Generative AI vs Traditional ML Topics

Generative AI concepts and use cases
LLM capabilities and limitations
Prompting and application patterns

02 LLM landscape Topics

Tokens and context windows
Model behavior and limitations
Practical use of LLMs in workflows

03 Transformer architecture Topics

Attention and sequence processing
Tokens, context and representations
Transformer-based language models

04 Tokens and tokenization Topics

Core concepts and terminology of tokens and tokenization
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

05 Attention mechanisms Topics

Core concepts and terminology of attention mechanisms
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

06 Next-token prediction Topics

Core concepts and terminology of next-token prediction
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

07 Context windows Topics

Core concepts and terminology of context windows
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

08 Temperature Topics

Core concepts and terminology of temperature
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

09 Top-k and top-p Topics

Core concepts and terminology of top-k and top-p
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

MODULE 2: PYTHON & AI DEVELOPMENT ENVIRONMENT

10 Python fundamentals for AI Topics

Python syntax and programming fundamentals
Data structures, functions and reusable code
Analytics-oriented programming workflow

11 NumPy Topics

Arrays and dimensions
Vectorized mathematical operations
Statistical calculations and reshaping

12 Pandas Topics

Series and DataFrames
Data selection, transformation and aggregation
Data preparation and analytical workflows

13 Jupyter Topics

Core concepts and terminology of jupyter
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

14 VS Code Topics

Core concepts and terminology of vs code
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

15 Google Colab Topics

Core concepts and terminology of google colab
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

16 Virtual environments Topics

Core concepts and terminology of virtual environments
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

17 AI development workflow Topics

Core concepts and terminology of ai development workflow
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

MODULE 3: LLM APIS & OPEN-SOURCE MODELS

18 OpenAI API Topics

REST principles and HTTP methods
Authentication, requests and responses
Errors, rate limits and integrations

19 Google Vertex AI Topics

Core concepts and terminology of google vertex ai
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

20 Anthropic Claude Topics

Core concepts and terminology of anthropic claude
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

21 Azure OpenAI Topics

Core concepts and terminology of azure openai
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

22 Hugging Face ecosystem Topics

Core concepts and terminology of hugging face ecosystem
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

23 Model selection Topics

Core concepts and terminology of model selection
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

24 Model cards and licensing Topics

Core concepts and terminology of model cards and licensing
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

25 Llama Topics

Core concepts and terminology of llama
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

26 Mistral Topics

Core concepts and terminology of mistral
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

27 Code models Topics

Core concepts and terminology of code models
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

28 Ollama Topics

Core concepts and terminology of ollama
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

29 Local model deployment Topics

Core concepts and terminology of local model deployment
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

30 Quantization Topics

Core concepts and terminology of quantization
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

MODULE 4: PROMPT ENGINEERING

31 Prompt structure Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

32 System prompts Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

33 User prompts Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

34 Role-based prompting Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

35 Zero-shot prompting Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

36 Few-shot prompting Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

37 Prompt templates Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

38 Complex reasoning prompts Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

39 Prompt injection Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

40 Prompt security Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

41 Prompt evaluation Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

42 Iterative optimization Topics

Core concepts and terminology of iterative optimization
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

MODULE 5: LANGCHAIN & APPLICATION DEVELOPMENT

43 LLMs Topics

Tokens and context windows
Model behavior and limitations
Practical use of LLMs in workflows

44 Chains Topics

Core concepts and terminology of chains
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

45 Agents Topics

Core concepts and terminology of agents
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

46 Memory Topics

Short-term and persistent context
State management
Memory selection and reliability

47 Prompt templates Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

48 Output parsing Topics

Core concepts and terminology of output parsing
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

49 Validation Topics

Core concepts and terminology of validation
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

50 Sequential chains Topics

Core concepts and terminology of sequential chains
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

51 Branching logic Topics

Core concepts and terminology of branching logic
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

52 Document loaders Topics

Core concepts and terminology of document loaders
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

53 Text splitters Topics

Core concepts and terminology of text splitters
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

54 Conversation memory Topics

Short-term and persistent context
State management
Memory selection and reliability

MODULE 6: RAG & VECTOR DATABASES

55 RAG architecture Topics

Document ingestion and chunking
Embeddings, retrieval and reranking
Grounded responses and knowledge assistants

56 Hallucination problem Topics

Core concepts and terminology of hallucination problem
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

57 Data ingestion Topics

Core concepts and terminology of data ingestion
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

58 Chunking Topics

Core concepts and terminology of chunking
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

59 Embeddings Topics

Core concepts and terminology of embeddings
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

60 Semantic search Topics

Core concepts and terminology of semantic search
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

61 Vector similarity Topics

Embeddings and semantic similarity
Indexing and retrieval
Vector database concepts and use cases

62 Pinecone Topics

Core concepts and terminology of pinecone
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

63 Weaviate Topics

Core concepts and terminology of weaviate
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

64 Qdrant Topics

Core concepts and terminology of qdrant
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

65 Chroma Topics

Core concepts and terminology of chroma
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

66 Metadata filtering Topics

Core concepts and terminology of metadata filtering
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

67 Hybrid search Topics

Core concepts and terminology of hybrid search
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

68 Retrieval and reranking Topics

Core concepts and terminology of retrieval and reranking
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

MODULE 7: FINE-TUNING & MODEL CUSTOMIZATION

69 When to fine-tune Topics

Core concepts and terminology of when to fine-tune
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

70 Prompting vs RAG vs fine-tuning Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

71 Full fine-tuning Topics

Customization vs prompting and RAG
PEFT, LoRA and QLoRA concepts
Training data and evaluation considerations

72 PEFT Topics

Core concepts and terminology of peft
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

73 LoRA Topics

Core concepts and terminology of lora
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

74 QLoRA Topics

Core concepts and terminology of qlora
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

75 Prefix tuning Topics

Core concepts and terminology of prefix tuning
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

76 Prompt tuning Topics

Prompt structure and context
Zero-shot, few-shot and role-based prompting
Prompt optimization and evaluation

77 Instruction tuning Topics

Core concepts and terminology of instruction tuning
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

78 Domain adaptation Topics

Core concepts and terminology of domain adaptation
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

MODULE 8: GENAI EVALUATION & GUARDRAILS

79 Task-specific evaluation Topics

Quality criteria and evaluation datasets
Hallucination and safety checks
Guardrails and output validation

80 Human evaluation Topics

Quality criteria and evaluation datasets
Hallucination and safety checks
Guardrails and output validation

81 BLEU Topics

Core concepts and terminology of bleu
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

82 ROUGE Topics

Core concepts and terminology of rouge
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

83 METEOR Topics

Core concepts and terminology of meteor
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

84 Semantic similarity Topics

Core concepts and terminology of semantic similarity
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

85 LLM-as-Judge Topics

Tokens and context windows
Model behavior and limitations
Practical use of LLMs in workflows

86 Cost-quality analysis Topics

Core concepts and terminology of cost-quality analysis
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

87 Safety controls Topics

Core concepts and terminology of safety controls
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

88 Output validation Topics

Core concepts and terminology of output validation
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

89 Guardrails Topics

Core concepts and terminology of guardrails
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

MODULE 9: DEPLOYMENT

90 FastAPI Topics

REST principles and HTTP methods
Authentication, requests and responses
Errors, rate limits and integrations

91 API development Topics

REST principles and HTTP methods
Authentication, requests and responses
Errors, rate limits and integrations

92 Docker Topics

Images, containers and Dockerfiles
Environment configuration
Containerizing AI applications

93 Cloud deployment Topics

Cloud service concepts
Deployment architecture and scalability
Operations, security and cost considerations

94 AWS / Azure / GCP concepts Topics

Core concepts and terminology of aws / azure / gcp concepts
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

95 Application monitoring Topics

Logs, metrics and traces
Application and infrastructure monitoring
Performance, reliability and alerting

96 Performance optimization Topics

Core concepts and terminology of performance optimization
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

97 Cost optimization Topics

Core concepts and terminology of cost optimization
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

98 Capstone Project Topics

Core concepts and terminology of capstone project
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

99 Build and deploy an end-to-end GenAI application. Topics

Core concepts and terminology of build and deploy an end-to-end genai application.
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

100 Project Options: Topics

Core concepts and terminology of project options:
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

101 RAG-based Knowledge Assistant Topics

Document ingestion and chunking
Embeddings, retrieval and reranking
Grounded responses and knowledge assistants

102 Fine-Tuned Customer Support Bot Topics

Core concepts and terminology of fine-tuned customer support bot
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

103 AI Content Generation Platform Topics

Core concepts and terminology of ai content generation platform
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

104 Domain-Specific Code Assistant Topics

Core concepts and terminology of domain-specific code assistant
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

105 Career Roles Topics

Core concepts and terminology of career roles
Practical implementation, analysis or workflow considerations
Business use cases, best practices and common challenges

106 GenAI Engineer | LLM Engineer | AI Application Engineer | Generative AI Developer Topics

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GENERATIVE AI & LLM ENGINEER

COURSE OVERVIEW

WHO SHOULD JOIN?

CAREER OUTCOMES

PRACTICE LIKE A REAL PROFESSIONAL

What You Will Learn to Do in Real-World Projects

Generative AI & LLM Foundations

Prompt Engineering

LLM APIs & Models

LangChain & LLM Frameworks

RAG & Vector Databases

Fine-Tuning & Model Optimization

GenAI Application Development

Deployment & Production AI

COURSE CURRICULUM

HANDS-ON LABS YOU WILL WORK ON

LLM Foundations

Prompt Engineering

LLM API Integration

LangChain Applications

DatabaseZap

Fine-Tuning & Optimization

AI Application Development

Deployment & Capstone Projects

WHAT'S INCLUDED IN THIS PROGRAM

90 Live Sessions

70% Hands-On Training

200++ hrs Lab Practices

24×7 Lab Access

Resume Building

Job Support

Real-World Projects

Internship Opportunities

Technical Mentorship

Career Guidance

GitHub Portfolio

Interview Preparation

Course Completion Certificate

MEET YOUR TRAINER

Surya Kumar

STUDENT SUCCESS STORIES

PLACEMENT ASSISTANCE

ResumePreparation

MockInterviews

TechnicalInterview Q&A

CompanyReferrals

PlacementSupport

UPCOMING BATCHES

LEARNING MODES

CLASSROOMTRAINING

LIVE ONLINETRAINING

SELF-PACEDLEARNING

FAQs

READY TO BECOME AN ORACLE DBA EXPERT?

Resume
Preparation

Mock
Interviews

Technical
Interview Q&A

Company
Referrals

Placement
Support

CLASSROOM
TRAINING

LIVE ONLINE
TRAINING

SELF-PACED
LEARNING