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Local LLM Workshop - SWIB 2025
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Next Steps

Next Steps

Continuing Your LLM Journey

Now that you’ve completed the workshop, here are suggested paths for deepening your knowledge and skills.

Immediate Next Steps (This Week)

1. Practice with Your Own Data

Apply what you learned to your own use cases:

  • Identify a document collection you work with
  • Build a RAG system for those documents
  • Create custom prompts for your domain
  • Experiment with different models and parameters

2. Explore More Models

Try other models available through Ollama:

# Code generation
ollama pull codellama:7b

# Alternative LLM
ollama pull mistral:7b

# Specialized embedding
ollama pull mxbai-embed-large

3. Enhance Your Scripts

Improve the examples from the workshop:

  • Add error handling and logging
  • Create command-line interfaces
  • Build web interfaces with Flask or FastAPI
  • Implement caching for better performance

Short-Term Goals (This Month)

Learn Advanced RAG Techniques

Hybrid Search:

  • Combine semantic and keyword search
  • Implement BM25 + vector search
  • Re-ranking strategies

Query Optimization:

  • Query expansion
  • Query rewriting with LLMs
  • Multi-query retrieval

Advanced Chunking:

  • Semantic chunking
  • Recursive splitting
  • Context-aware chunking

Resources:

Experiment with Agent Systems

Build LLM agents that can:

  • Use tools and APIs
  • Plan multi-step tasks
  • Self-correct and iterate

Frameworks to explore:

  • LangChain
  • LlamaIndex
  • AutoGPT

Build a Project

Create something useful:

Ideas:

  • Personal knowledge base with RAG
  • Document summarization pipeline
  • Code documentation generator
  • Meeting notes analyzer
  • Research paper Q&A system
  • Local chatbot for your organization

Medium-Term Goals (Next 3 Months)

Dive Deeper into Embeddings

  • Study transformer architectures
  • Fine-tune embedding models for your domain
  • Experiment with different similarity metrics
  • Implement approximate nearest neighbor search

Explore Multimodal Models

  • Use Llama 3.2 Vision for image analysis
  • Build document processing pipelines (PDF → text + images)
  • Create visual Q&A systems

Optimize Performance

  • GPU acceleration with CUDA
  • Quantization techniques
  • Model compression
  • Batch processing optimization

Learn Evaluation Techniques

Measure and improve your systems:

  • Retrieval quality metrics (precision, recall)
  • RAG answer quality evaluation
  • A/B testing different approaches
  • Creating evaluation datasets

Long-Term Goals (Next 6-12 Months)

Advanced Topics

Fine-Tuning:

  • Understand LoRA and QLoRA
  • Fine-tune models for specific tasks
  • Create domain-specialized models

Multi-Agent Systems:

  • Build collaborative agent systems
  • Implement planning and reasoning
  • Create self-improving systems

Production Deployment:

  • Containerize your applications
  • Set up monitoring and logging
  • Implement rate limiting and caching
  • Scale to handle multiple users

Contribute to Open Source

  • Contribute to Ollama or related projects
  • Share your tools and scripts
  • Write tutorials and documentation
  • Help others in the community

Stay Current

The field evolves rapidly:

  • Follow key researchers and organizations
  • Read papers on arXiv
  • Attend conferences (NeurIPS, EMNLP, ACL)
  • Join online communities

Learning Resources

Free Courses

Beginner:

Intermediate:

Advanced:

Books

For Practitioners:

  • “Hands-On Large Language Models” by Jay Alammar & Maarten Grootendorst
  • “Build a Large Language Model (From Scratch)” by Sebastian Raschka
  • “Natural Language Processing with Transformers” by Lewis Tunstall et al.

For Researchers:

  • “Speech and Language Processing” by Jurafsky & Martin
  • “Deep Learning” by Goodfellow, Bengio & Courville

Communities

Newsletters & Blogs

Project Ideas by Skill Level

Beginner

  • Personal journal analyzer
  • Book recommendation system
  • Email categorizer
  • Study notes organizer

Intermediate

  • Technical documentation chatbot
  • Research paper summarizer with citations
  • Multi-language translation tool
  • Code review assistant

Advanced

  • Multi-modal search engine
  • Collaborative research assistant
  • Automated report generation system
  • Domain-specific knowledge graph builder

Staying Motivated

Set Clear Goals

Break your learning into achievable milestones:

  • Week 1: Build basic RAG system
  • Week 2: Add streaming responses
  • Week 3: Implement caching
  • Week 4: Create web interface

Join a Community

  • Find an accountability partner
  • Join study groups
  • Participate in hackathons
  • Share your progress online

Build in Public

  • Document your journey
  • Share your projects on GitHub
  • Write blog posts about what you learn
  • Help others starting out

Getting Help

When you get stuck:

  1. Search Documentation: Ollama docs, ChromaDB docs
  2. Check GitHub Issues: Often someone has faced the same problem
  3. Ask in Communities: Discord, Reddit, forums
  4. Experiment: Try different approaches
  5. Simplify: Break the problem into smaller parts
You’ve Got This! You now have a solid foundation in local LLMs. The key is consistent practice and building real projects. Start small, iterate, and keep learning!

Stay Connected

  • Workshop Website: Bookmark for future reference
  • Notebooks Repository: Star on GitHub for updates
  • Ollama Updates: Follow for new models and features

Questions about the workshop? Contact the instructor or check the FAQ.

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