Starweaver
GenAI Data and Analytics Academy Specialization

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Starweaver

GenAI Data and Analytics Academy Specialization

GenAI Data and Analytics Academy. Master GenAI, LLMs & Agents: From Data Pipelines to Model Deployment at Scale

Starweaver
Ritesh Vajariya

Instructors: Starweaver

Included with Coursera Plus

Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 4 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 4 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Design and implement comprehensive data pipelines for GenAI applications.

  • Develop and deploy autonomous AI agents and multi-agent systems.

  • Analyze prompt engineering and chain management for LLMs.

  • Build production-ready GenAI applications with monitoring and safety systems.

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Taught in English
Recently updated!

September 2025

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Specialization - 4 course series

What you'll learn

  • Master GenAI foundational concepts and LLM integration strategies for building scalable enterprise applications.

  • Construct advanced prompt engineering workflows with multi-step chains and context optimization.

  • Implement enterprise GenAI use cases with systematic design and ROI measurement frameworks.

  • Develop production-ready conversation systems with template engines and quality assurance protocols.

Skills you'll gain

Category: Prompt Engineering
Category: Generative AI
Category: Debugging
Category: Process Optimization
Category: ChatGPT
Category: Program Evaluation
Category: Systems Architecture
Category: Model Evaluation
Category: AI Workflows
Category: Application Programming Interface (API)
Category: Context Management
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Retrieval-Augmented Generation
Category: Performance Tuning
Category: Large Language Modeling
Category: Enterprise Application Management
Category: Development Environment
Category: Generative AI Agents

What you'll learn

  • Construct enterprise-grade data processing pipelines with quality validation and AI-ready formatting.

  • Implement sophisticated RAG architectures with vector search, embeddings, and context management.

  • Deploy advanced RAG optimization techniques including reranking, metadata filtering, and adaptive strategies.

  • Develop specialized customer support RAG systems with context-aware personalization and performance tracking.

Skills you'll gain

Category: Generative AI
Category: Data Processing
Category: Data Pipelines
Category: AI Personalization
Category: Embeddings
Category: Continuous Monitoring
Category: Talent Pipelining
Category: Retrieval-Augmented Generation
Category: Engineering
Category: AI Workflows
Category: Prompt Engineering
Category: Data Engineering
Category: Vector Databases
Category: Performance Tuning
Category: Data Architecture
Category: Database Systems
Category: System Monitoring
Category: Process Optimization
Category: Scalability

What you'll learn

  • Construct autonomous AI agents with CrewAI framework, tool integration, and decision-making capabilities.

  • Implement sophisticated multi-agent coordination systems with communication protocols and task delegation.

  • Deploy specialized customer support agents with knowledge base integration and escalation management.

  • Apply agent safety frameworks and testing protocols for reliable production deployment.

Skills you'll gain

Category: Generative AI Agents
Category: Generative AI
Category: LLM Application
Category: CrewAI
Category: Logical Reasoning
Category: Data Integration
Category: AI Workflows
Category: Generative Model Architectures
Category: Systems Architecture
Category: Prompt Patterns
Category: Responsible AI
Category: Context Management
Category: Collaboration
Category: AI Orchestration
Category: Tool Calling
Category: Agentic systems
Category: Application Deployment
Category: Job Evaluation
Category: Model Deployment

What you'll learn

  • Execute advanced fine-tuning workflows including LoRA optimization and domain-specific model customization.

  • Implement enterprise-scale deployment strategies with containerization, monitoring, and infrastructure automation.

  • Construct comprehensive production monitoring and maintenance protocols with automated alerting and performance tracking.

  • Apply advanced optimization techniques including caching, edge deployment, hybrid routing, and emerging technology adoption strategies.

Skills you'll gain

Category: Scalability
Category: MLOps (Machine Learning Operations)
Category: Generative AI
Category: Performance Tuning
Category: Cloud Infrastructure
Category: Kubernetes
Category: System Monitoring
Category: Model Deployment
Category: Process Optimization
Category: Continuous Deployment
Category: Job Evaluation
Category: Emerging Technologies
Category: Transfer Learning
Category: Large Language Modeling
Category: Containerization
Category: Prompt Engineering
Category: Model Evaluation
Category: Automation
Category: Docker (Software)
Category: Continuous Monitoring

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Instructors

Starweaver
Starweaver
490 Courses921,032 learners

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Starweaver

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