This repository contains my journey to becoming an NLP Engineer, following a structured 12-week plan based on the book "Introduction to Large Language Models (LLMs)".
gantt
title NLP Engineer Portfolio Development Plan
dateFormat YYYY-MM-DD
axisFormat %m/%d
section Week 1: Foundations
Language Model Fundamentals :a1, 2025-04-14, 2d
NLP Pipeline Implementation :a2, after a1, 2d
Neural Network Basics :a3, after a2, 2d
Review & Documentation :a4, after a3, 1d
section Week 2: Word Embeddings
Word Embeddings Implementation :b1, 2025-04-21, 2d
Statistical LMs :b2, after b1, 2d
Evaluation Methods :b3, after b2, 2d
Integration & Documentation :b4, after b3, 1d
section Week 3: Neural LMs
CNNs for NLP :c1, 2025-04-28, 2d
RNNs & LSTMs :c2, after c1, 2d
Seq2Seq Models :c3, after c2, 2d
Testing & Documentation :c4, after c3, 1d
section Week 4: Transformers
Self-Attention :d1, 2025-05-05, 2d
Transformer Architecture :d2, after d1, 2d
Efficient Attention :d3, after d2, 2d
Project Packaging :d4, after d3, 1d
section Week 5: LLM Pretraining
Embedding Models :e1, 2025-05-12, 2d
Encoder Models :e2, after e1, 2d
Decoder Models :e3, after e2, 2d
Comparative Analysis :e4, after e3, 1d
section Week 6: Fine-Tuning
Task-Specific Fine-Tuning :f1, 2025-05-19, 2d
Instruction Tuning :f2, after f1, 2d
Alignment Methods :f3, after f2, 2d
Model Evaluation :f4, after f3, 1d
section Week 7: Prompting
Prompt Engineering :g1, 2025-05-26, 2d
In-Context Learning :g2, after g1, 2d
Chain/Tree of Thoughts :g3, after g2, 2d
Application Building :g4, after g3, 1d
section Week 8: Efficient LLMs
Knowledge Distillation :h1, 2025-06-02, 2d
Model Compression :h2, after h1, 2d
Parameter-Efficient Tuning :h3, after h2, 2d
Benchmarking :h4, after h3, 1d
section Week 9: Augmented LLMs
RAG Fundamentals :i1, 2025-06-09, 2d
RAG Evaluation :i2, after i1, 2d
Tool Calling & Agents :i3, after i2, 2d
Integration :i4, after i3, 1d
section Week 10: Multi LLMs
Multilingual Models :j1, 2025-06-16, 2d
Multimodal Integration :j2, after j1, 2d
Challenges & Solutions :j3, after j2, 2d
Demo Preparation :j4, after j3, 1d
section Week 11: Responsible AI
Bias Detection & Mitigation :k1, 2025-06-23, 2d
LLM Reasoning :k2, after k1, 2d
Long Context & Hallucination :k3, after k2, 2d
Ethical Framework :k4, after k3, 1d
section Week 12: Applications
Industry Applications :l1, 2025-06-30, 2d
Portfolio Integration :l2, after l1, 2d
Resume & LinkedIn Optimization :l3, after l2, 2d
Job Application Strategy :l4, after l3, 1d
Book Chapters: 1 & 2 (Introduction + NLP & Neural Networks Overview)
| Day | Learning Focus | Tasks | Status | Project Deliverable | Completion |
|---|---|---|---|---|---|
| 1-2 | Language Model Fundamentals | Study Ch. 1, research evolution of LLMs | ⬜ In Progress | GitHub repo structure, portfolio website skeleton | ⬜ 0% |
| 3-4 | NLP Pipeline | Study Ch. 2 (Part I), implement basic pipeline | ⬜ Not Started | NLP Pipeline demo | ⬜ 0% |
| 5-6 | Neural Network Basics | Study Ch. 2 (Part II), implement perceptron | ⬜ Not Started | Interactive neural network visualization tool | ⬜ 0% |
| 7 | Review & Documentation | Document learning, prepare blog post | ⬜ Not Started | Blog: "Evolution of Language Models" | ⬜ 0% |
Week 1 Progress: ⬜ 0% complete
Notes & Learnings:
- (Add your notes and learnings here)
Book Chapters: 3 & 4
| Day | Learning Focus | Tasks | Status | Project Deliverable | Completion |
|---|---|---|---|---|---|
| 1-2 | Word Embeddings | Study Ch. 3, implement Word2Vec | ⬜ Not Started | Word embedding visualization tool | ⬜ 0% |
| 3-4 | Statistical LMs | Study Ch. 4, implement n-gram models | ⬜ Not Started | N-gram text generator | ⬜ 0% |
| 5-6 | Evaluation Methods | Implement perplexity and other metrics | ⬜ Not Started | Model comparison dashboard | ⬜ 0% |
| 7 | Integration & Documentation | Combine components, write documentation | ⬜ Not Started | GitHub README updates, blog post | ⬜ 0% |
Week 2 Progress: ⬜ 0% complete
Notes & Learnings:
- (Add your notes and learnings here)
Book Chapter: 5
| Day | Learning Focus | Tasks | Status | Project Deliverable | Completion |
|---|---|---|---|---|---|
| 1-2 | CNNs for NLP | Study Ch. 5.1, implement text CNN | ⬜ Not Started | Text classifier using CNN | ⬜ 0% |
| 3-4 | RNNs & LSTMs | Study Ch. 5.2, implement RNN/LSTM | ⬜ Not Started | Character-level text generator | ⬜ 0% |
| 5-6 | Seq2Seq Models | Study Ch. 5.3-5.4, implement attention | ⬜ Not Started | Simple machine translation system | ⬜ 0% |
| 7 | Testing & Documentation | Test models, document results | ⬜ Not Started | Technical blog post | ⬜ 0% |
Week 3 Progress: ⬜ 0% complete
Notes & Learnings:
- (Add your notes and learnings here)
Book Chapter: 6
| Day | Learning Focus | Tasks | Status | Project Deliverable | Completion |
|---|---|---|---|---|---|
| 1-2 | Self-Attention | Study Ch. 6.1-6.2, implement self-attention | ⬜ Not Started | Self-attention visualization tool | ⬜ 0% |
| 3-4 | Transformer Architecture | Study Ch. 6.3-6.4, implement components | ⬜ Not Started | Small-scale transformer | ⬜ 0% |
| 5-6 | Efficient Attention | Study Ch. 6.5-6.6, optimize transformer | ⬜ Not Started | Memory-efficient implementation | ⬜ 0% |
| 7 | Project Packaging | Package code, create demos | ⬜ Not Started | "Transformers from Scratch" repo | ⬜ 0% |
Week 4 Progress: ⬜ 0% complete
Notes & Learnings:
- (Add your notes and learnings here)
...
- Text preprocessing and normalization
- Word embeddings and text representations
- Statistical language modeling
- Neural language modeling
- Transformer architectures
- Fine-tuning pre-trained models
- Prompt engineering
- Retrieval-augmented generation
- Model optimization techniques
- LLM evaluation frameworks
- NLTK
- spaCy
- Hugging Face Transformers
- PyTorch
- TensorFlow/Keras
- FastAPI/Flask
- Docker
- Cloud deployment
- Portfolio website creation
- Technical blog posts (Target: 12)
- LinkedIn profile optimization
- GitHub profile enhancement
- ATS-optimized resume
- Mock interviews completed (Target: 6)
| Project | Description | Status | Demo Link | Repository |
|---|---|---|---|---|
| NLP Pipeline | Comprehensive text processing pipeline | ⬜ Not Started | - | - |
| Word Embedding Visualizer | Interactive tool to explore word relationships | ⬜ Not Started | - | - |
| Neural Text Generator | Character-level text generation with RNN/LSTM | ⬜ Not Started | - | - |
| Transformer Implementation | Transformer built from scratch | ⬜ Not Started | - | - |
| Custom Fine-Tuned Model | Domain-specific model fine-tuning | ⬜ Not Started | - | - |
| Prompt Engineering Studio | Interactive prompt design and testing | ⬜ Not Started | - | - |
| Model Optimization Framework | Tools for distillation and quantization | ⬜ Not Started | - | - |
| RAG-Enhanced Agent | Document QA system with retrieval | ⬜ Not Started | - | - |
| Multilingual Assistant | Text processing across multiple languages | ⬜ Not Started | - | - |
| Bias Detection Toolkit | Tools to measure and mitigate bias | ⬜ Not Started | - | - |
| Industry Application | Domain-specific NLP system | ⬜ Not Started | - | - |
| Title | Published Date | Status | Link |
|---|---|---|---|
| Evolution of Language Models | - | ⬜ Not Started | - |
| Understanding Word Embeddings | - | ⬜ Not Started | - |
| Neural Networks for Text | - | ⬜ Not Started | - |
| ... | ... | ... | ... |