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AI Engineer Course Syllabus

7-Week Intensive Program

Week 0: Foundations & Setup

Duration: 5-7 hours
Focus: Environment setup and AI fundamentals

Learning Objectives

  • Set up IONOS VM with Ubuntu 22.04
  • Configure Python environment and Docker
  • Understand Hugging Face ecosystem
  • Deploy first AI model

Lessons

  1. Welcome & Course Overview - Course structure and expectations
  2. IONOS VM Setup - Cloud infrastructure basics
  3. Hugging Face 101 - Models, datasets, and spaces
  4. Python Environment - Virtual environments and dependency management
  5. Docker Fundamentals - Containerization for AI deployment

Project

Deploy DistilBERT sentiment analysis API on IONOS VM

Tech Stack

  • Ubuntu 22.04, Python 3.11, Docker, FastAPI

Week 1: LLM Playground

Duration: 8-10 hours
Focus: Transformer architecture and model interaction

Learning Objectives

  • Understand transformer architecture
  • Master tokenization techniques
  • Build interactive model interfaces
  • Implement parameter tuning

Lessons

  1. Transformers Overview - Attention, encoders, decoders
  2. Tokenization Deep Dive - BPE, WordPiece, SentencePiece
  3. Hugging Face Pipelines - Pre-built model interfaces
  4. Gradio UI Development - Interactive web applications
  5. Model Parameter Tuning - Temperature, top-p, top-k

Project

LLM Playground with model selection, parameter controls, and token visualization

Tech Stack

  • Hugging Face Transformers, Gradio, GPT-2, Falcon-7B

Week 2: Customer Support Chatbot

Duration: 10-12 hours
Focus: Fine-tuning and conversational AI

Learning Objectives

  • Implement parameter-efficient fine-tuning
  • Design conversation flows
  • Deploy production chatbots
  • Handle context and memory

Lessons

  1. Fine-tuning Fundamentals - Full vs parameter-efficient methods
  2. LoRA and PEFT - Low-rank adaptation techniques
  3. Conversation Design - Context handling and persona
  4. Dataset Preparation - FAQ and support ticket processing
  5. Production Deployment - Scaling and monitoring

Project

Customer support chatbot with role-based responses and FAQ integration

Tech Stack

  • Hugging Face PEFT, LoRA, Customer support datasets

Week 3: Ask-the-Web Agent

Duration: 12-15 hours
Focus: Agent frameworks and workflow automation

Learning Objectives

  • Build AI agents with tool access
  • Implement web search and summarization
  • Create automated workflows with n8n
  • Handle multi-step reasoning

Lessons

  1. Agent Architecture - Planner vs worker patterns
  2. LangChain Integration - Tool orchestration
  3. Web Search APIs - DuckDuckGo, Tavily integration
  4. n8n Fundamentals - Workflow automation basics
  5. Citation and Sources - Reliable information retrieval

Project

Perplexity-style research agent with automated report generation

Tech Stack

  • LangChain, n8n, Tavily API, Google Sheets integration

Week 4: Deep Research Agent

Duration: 12-15 hours
Focus: Advanced reasoning and long-context processing

Learning Objectives

  • Implement chain-of-thought reasoning
  • Handle long-context scenarios
  • Build tree-of-thoughts systems
  • Evaluate and reduce hallucinations

Lessons

  1. Advanced Reasoning - CoT, Self-Consistency, ToT
  2. Long Context Models - LongT5, MPT-7B-StoryWriter
  3. Multi-step Planning - Breaking down complex queries
  4. Evaluation Methods - Fact-checking and verification
  5. Structured Output - JSON, reports, citations

Project

Deep research agent with iterative query refinement and structured reporting

Tech Stack

  • Long-context models, Tree-of-Thoughts, structured output

Week 5: Image Generation & ElevenLabs

Duration: 12-15 hours
Focus: Multimodal AI and voice integration

Learning Objectives

  • Master diffusion models
  • Implement image fine-tuning
  • Integrate voice capabilities
  • Build multimodal applications

Lessons

  1. Diffusion Models - Stable Diffusion, SDXL architecture
  2. Image Fine-tuning - DreamBooth, LoRA for style
  3. ElevenLabs Integration - TTS and voice cloning
  4. Voice Workflows - STT → LLM → TTS pipelines
  5. Multimodal UX - Combining text, image, and voice

Project

Image generation service with voice-controlled interface

Tech Stack

  • Hugging Face Diffusers, Stable Diffusion, ElevenLabs API

Week 6: Capstone Project

Duration: 15-20 hours
Focus: Independent project development

Learning Objectives

  • Design and scope AI applications
  • Integrate multiple technologies
  • Deploy production-ready systems
  • Present technical work

Project Options

  • Multi-agent research assistant
  • Voice-enabled RAG system
  • Creative AI content pipeline
  • Business automation platform

Deliverables

  • Working application on IONOS
  • GitHub repository with documentation
  • Demo video and presentation
  • Technical writeup

Week 7: Advanced Topics (Optional)

Duration: 8-10 hours
Focus: Cutting-edge techniques and optimization

Learning Objectives

  • Implement multi-agent coordination
  • Optimize for production scale
  • Explore emerging techniques
  • Plan continued learning

Lessons

  1. Multi-agent Systems - Coordination and communication
  2. Production Optimization - Caching, quantization, batching
  3. Emerging Techniques - Latest research and tools
  4. Career Development - Building AI engineering skills

Project

Enhanced capstone with advanced features

Assessment & Certification

Project Portfolio (70%)

  • Week 0-5 projects (10% each)
  • Capstone project (20%)

Technical Writeups (20%)

  • Weekly reflection posts
  • Technology comparisons
  • Lessons learned documentation

Community Participation (10%)

  • Helping peers in Discord
  • Code reviews and feedback
  • Sharing insights and discoveries

Certification Requirements

  • Complete all weekly projects
  • Submit capstone project
  • Participate in final presentation
  • Maintain 80% overall score

Resources & Prerequisites

Prerequisites

  • Python programming (intermediate level)
  • Basic command line usage
  • Git version control
  • Understanding of APIs and web development

Required Accounts

  • Hugging Face Hub (free)
  • IONOS Cloud account
  • ElevenLabs account
  • n8n cloud account (optional)
  • Local development: 8GB RAM minimum
  • IONOS VM: 4-8 vCPU, 16-32GB RAM

Time Commitment

  • Self-paced: 8-15 hours per week
  • Live cohort: 10-12 hours per week + 2 hours live sessions

Course Delivery Options

Self-Paced Digital Course

  • Price: $199
  • Lifetime access to materials
  • Community Discord access
  • Email support

Live Cohort Program

  • Price: $699
  • 7 weeks of guided instruction
  • Weekly live Q&A sessions
  • 1:1 capstone review
  • Job placement assistance

Premium Package

  • Price: $999
  • Everything in live cohort
  • Extended mentorship (3 months)
  • Portfolio review and optimization
  • Industry connections and referrals

Ready to start your AI engineering journey? Begin with Week 0: Foundations