Generative AI - Skill Up Plus Package
1.350,00 EUR
- 600 hours
Learn Generative AI. Build intelligent systems. Master the next generation of AI. Stay ahead of the rapidly evolving AI landscape with a comprehensive Generative AI Skill Up Plus Package designed to take learners from GenAI fundamentals to advanced Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, multi-agent systems, AI development, and enterprise AI solutions.
About the package
This package combines 3 intensive bootcamps, 16 learning paths, and 160+ eLearning courses, giving you multiple ways to develop and apply in-demand skills
This extensive learning package brings together a broad collection of eLearning courses, learning paths, and intensive programs covering the technologies and skills shaping the next generation of AI. Learners can explore prompt engineering, LLMs, LangChain, LangGraph, AutoGen, CrewAI, Hugging Face, RAG, Model Context Protocol (MCP), AI agents, Microsoft Copilot, Azure AI, AWS Bedrock, Databricks, and Generative AI application development.
From creating effective prompts and working with LLMs to designing autonomous AI agents and deploying enterprise-grade GenAI solutions, learners can develop skills across the complete Generative AI ecosystem.
Whether you are a business professional looking to leverage GenAI, a developer building intelligent applications, or an AI professional advancing into Agentic AI, this package provides a flexible pathway to develop practical, future-ready capabilities.
Instead of only learning 3-5 courses, why not have everything you need under our AI Skill Up Plus course catalog? Learn more, save up more!
Key Features
Course and material in English
Beginner - Advanced level for aspiring professional
1 year learning platform access & class recordings
430+ hours eLearning content
200+ live class hours
Self-assign live class cohorts and courses
Dynamic and auto-update future courses
Practice projects, virtual labs and assessment included
Certification for each course completion
Exam voucher not included
Learning Outcomes
At the end of this Bootcamp, you will be able to:
Understand the foundations
of Generative AI and LLMs, including how modern generative models work and where they can be applied.
Apply advanced prompt engineering techniques
to improve the quality, consistency, and effectiveness of AI-generated outputs.
Understand Transformer architectures
and modern LLM technologies, including attention mechanisms and models such as BERT.
Build and work with LLM-powered applications
using technologies and frameworks such as LangChain and Hugging Face.
Design Retrieval-Augmented Generation (RAG) solutions
that connect generative AI models with enterprise and unstructured data.
Design and develop AI agents
and Agentic AI workflows, including autonomous systems capable of using tools, data, and external services.
Explore multi-agent architectures
and orchestration using frameworks such as LangGraph, AutoGen, and CrewAI.
Apply emerging AI technologies
such as Model Context Protocol (MCP) to connect AI agents with tools, data sources, and external systems.
Build, integrate, and deploy
enterprise Generative AI solutions using platforms such as Azure AI, AWS Bedrock, and Databricks.
Evaluate, optimize, and govern
Generative AI solutions, considering model performance, responsible AI, security, reliability, and real-world business requirements.
Featured Programs
Applied Agentic AI: Systems, Design & Impact Bootcamp
10 weeks Bootcamp
Applied Generative AI Specialization
12 Weeks Bootcamp
AI Accelerator Program: From Prompts to Agentic Workflows
Bootcamp
16 Learning paths
Learning Path
160+ eLearning
Topics
- Mastering Agentic AI using LangGraph, AutoGen, and CrewAI Frameworks
- Building AI Agents – From Fundamentals to Advanced Applications
- Foundations of Agentic AI and LLM-Powered Architectures
- Mastering AI Agents: Building Autonomous and Intelligent AI Systems
- Full-Stack AI Development: Building Intelligent Applications with LLMs and Agents
- Building AI Agents with LangGraph and OpenAI
- LLM Fine-Tuning and Customization
- LangChain for LLM Application Development
- Large Language Models & LangChain and Workflow Design
- Introduction to Large Language Models
- Prompt Engineering Masterclass – From Beginner to Advanced
- Prompt Engineering for Everyone with ChatGPT and GPT-4
- Building Generative AI Applications with RAG (Azure & AWS)
- Preprocessing Unstructured Data for LLMs and RAG Systems
- Azure AI Foundry + RAG
- Get Started with Databricks for Generative AI
- Building and Deploying Intelligent AI Solutions with Azure AI Studio
- Advanced AI Services, Integration, and Deployment with Azure AI Studio
- Azure AI Studio – Build Intelligent Apps, Agents, and Automations
- Generative AI on Azure
- AWS Advanced GenAI & Machine Learning
- Amazon Bedrock Core
- Bedrock GuardRails & Agents
- Deploy Intelligent AI Agents with Amazon Bedrock
- RAG & SageMaker on AWS
- Attention Mechanism and Transformers
- Transformer Models and BERT Model
- Natural Language Processing – Transformers with Hugging Face
- Using Hugging Face Transformers for Generative Tasks
- Gen AI Using Hugging Face
- Optimizing GenAI Models
- Benchmark and Evaluation of LLM Capabilities
- Model Context Protocol (MCP) for Agentic AI
- MCP for Leaders – Architecting Context-Driven AI
- Orchestrating Agent Teams with CrewAI
- Designing Multi-Agent Systems with AutoGen for Advanced Task Automation
- Mastering AI Agents for Databases
- Crafting AI Agents with Persistent Memory
- Advanced Automation – Connecting Microsoft Copilot to External Data
- Mastering Microsoft Copilot – Generative AI for 365 Productivity
And many more..
Progression:
Generative AI Fundamentals → Prompt Engineering → LLMs → RAG → AI Agents → Multi-Agent Systems → MCP → GenAI Development → Cloud AI → Enterprise Copilot → AI Governance
Who Should Enroll in this Program?
AI and Machine Learning Professionals looking to specialize in Generative AI and Agentic AI.
Software Developers and Engineers who want to build LLM-powered applications, AI agents, and intelligent workflows.
Data Scientists and Data Engineers interested in applying LLMs, RAG, and GenAI to enterprise data.
IT Professionals and Cloud Engineers working with Azure AI, AWS AI services, Databricks, and enterprise AI infrastructure.
Product Managers and Innovation Professionals exploring AI-powered products, services, and business opportunities.
AI Architects and Technical Leads seeking to design scalable GenAI, Agentic AI, and multi-agent solutions.
Prerequisites
There are no universal prerequisites for the Generative AI Professional Learning Package because it contains learning content ranging from beginner fundamentals to advanced technical topics. Learners can start with introductory courses and progressively move into more advanced areas such as LLM development, RAG, AI agents, multi-agent systems, and enterprise AI deployment.
For advanced technical courses, the following knowledge may be beneficial:
- Basic understanding of Artificial Intelligence and Machine Learning concepts.
- Familiarity with Python or another programming language for developer-focused courses.
- Basic understanding of APIs, cloud platforms, and software development for application-development topics.
- Familiarity with data, databases, or unstructured data for RAG and enterprise AI courses.
- Prior experience with LLMs or Generative AI tools can be helpful but is not required for the package as a whole.
Individual courses, bootcamps, and learning paths may have their own recommended prerequisites.
Explore and save up more with AVC Skill Up catalogs!
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