100DaysOfAIEngineer

Day 61 - 100 Days of AI Engineer

📁 Push your Day 61 code to this directory!

This directory is where you’ll store all your code, notebooks, and project files for Day 61.

Structure your day directory:

day61/
├── README.md          (this file - your daily log)
├── code/              (your Python scripts)
├── notebooks/         (Jupyter notebooks)
├── data/              (any data files)
├── outputs/           (results, models, plots)
└── notes.md           (additional notes)

When you complete Day 61:

1. ✅ Complete all tasks below
2. 💻 Push your code to this directory
3. 📝 Update this README with your learnings
4. 🔗 Commit and push to GitHub
5. 💬 Post in CODERCOPS Discord

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Day 61: Large Language Models - Fundamentals

Phase 5: LLMs & RAG Systems

Date: _______

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🎯 Learning Objectives

By the end of today, you will:

• Understand Large Language Models - Fundamentals fundamentals
• Implement Large Language Models - Fundamentals concepts hands-on
• Apply knowledge to practical problems
• Build working code examples

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📚 Prerequisites

Before starting, ensure you understand:

• Days 1-60 completed
• Previous concepts solid

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⏱️ Time Breakdown (6-8 hours total)

• Theory & Reading: 120-150 min
• Hands-on Practice: 225-300 min
• Mini Project/Exercises: 75-120 min
• Review & Documentation: 40-75 min

Adjust based on your pace and prior knowledge

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📖 Learning Resources

📝 Must-Read Articles

• LangChain RAG Tutorial - Official guide
• RAG Complete Guide - SingleStore
• Master RAG with LangChain - Step-by-step

🎥 Video Tutorials

• LangChain Tutorial - Complete guide
• RAG Explained - Sam Witteveen

💪 Practice Resources

• LangChain Examples - Code samples
• RAG Projects - GitHub
• Pinecone Examples - Vector DB

🎮 Interactive Platforms

• LangChain Hub - Prompt templates
• OpenAI Playground - Test prompts
• Google Colab - RAG development

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🔑 Key Concepts

• Large Language Models - Fundamentals - Core principles
• Large Language Models - Fundamentals - Best practices
• Large Language Models - Fundamentals - Common applications
• Large Language Models - Fundamentals - Implementation details

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✅ Today’s Tasks

1. 📚 Conceptual Understanding

• Read through learning resources
• Watch at least one video tutorial
• Take notes on key concepts
• Understand why this topic matters

2. 💻 Hands-On Practice

• Set up your environment
• Complete coding exercises
• Experiment with examples
• Debug and troubleshoot issues

3. 🚀 Mini Project

Build: Large Language Models - Fundamentals - Practical Implementation

Build a practical project applying Large Language Models - Fundamentals concepts learned today.

Requirements:

• Implement core functionality
• Test with real data
• Document your code
• Create examples/demos

4. 📝 Documentation

• Comment your code clearly
• Update this README with your learnings
• Note any challenges you faced
• Write down questions for the community

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⚠️ Common Pitfalls to Avoid

• Skipping fundamentals and jumping ahead
• Not testing code with different inputs
• Copy-pasting without understanding
• Ignoring error messages

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✅ Success Criteria

You’ve successfully completed Day 61 if:

• Can explain Large Language Models - Fundamentals concepts clearly
• Successfully completed all exercises
• Code works correctly with test cases
• Can modify code for new requirements

See QUALITY_STANDARDS.md for detailed completion criteria.

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🛠️ Tools & Setup

• Python 3.8+
• LangChain
• OpenAI API
• Vector DB
• transformers

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💬 Discord Check-In (REQUIRED)

Post in CODERCOPS Discord #100daysofaiengineer:

https://discord.gg/9eFXYntYa8

Daily Post Template:

Day 61/100 ✅

🎯 Topic: Large Language Models - Fundamentals

- [ ] What I learned:
- [Key learning 1]
- [Key learning 2]
- [Key learning 3]

💻 Code: [Your GitHub link to this directory]

🤔 Challenge: [What was hardest]

#100DaysOfAIEngineer #CODERCOPS @codercops

Why post daily:

• 📊 Build your public learning streak
• 🤝 Get support when stuck
• 💪 Stay accountable to the community
• 🎯 Network with other AI engineers

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📱 Social Media Post

Share on LinkedIn/Twitter (3x/week minimum):

🚀 Day 61/100 of my AI Engineering journey!

Today's focus: Large Language Models - Fundamentals

Key takeaway: [Your biggest insight]

Built: [Your mini project]

The progress is real! 💪

#100DaysOfAIEngineer #CODERCOPS #MachineLearning #AI
@codercops

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🔗 Helpful Links

• 📘 Main Curriculum
• 📊 All Daily Checklists
• 🎯 Quality Standards
• 🤝 CODERCOPS Community

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✅ End of Day Checklist

Before you finish Day 61:

• All learning objectives achieved
• Code written and tested
• Mini project completed
• Code pushed to GitHub
• Discord check-in posted
• Notes and reflections documented
• Tomorrow’s topic previewed

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📝 Notes & Reflections

What I learned today:

[Write your key takeaways]

Challenges I faced:

[What was difficult?]

How I overcame them:

[Your solutions]

Questions for the community:

[What are you still unsure about?]

Tomorrow’s prep:

[What will you study for Day 62?]

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🎉 Day 61 Complete! Keep the momentum going!

Next: Day 62

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**CODERCOPS Community

#100DaysOfAIEngineer

@codercops**

Remember: Learning in public, building real projects, staying consistent.