1. AI vs ML vs DL vs NLP vs Generative AI
2. Generative AI principles
3. Role of ML in Generative AI
4. Different ML techniques (Supervised, Unsupervised, Semi-supervised, Reinforcement Learning)
5. Applications in various domains
6. Ethical considerations

1. Basic NLP tasks
2. NLP essentials
3. Different text classification approaches
4. Frequency based: TF-IDF, BoW, N-gram
5. Distribution Models: CBOW, Skipgram (Traditional approaches), Word2Vec, GloVe
6. Ensemble and traditional Machine learning Models: Naive Bayes, SVM, Logistic Regression, Decision
   Trees
7. Deep learning techniques: CNNs, RNNs, LSTMs, GRU, Transformers

1. VAE’s and applications
2. Autoencoders
3. GAN’s and its applications
4. Different types of GAN’s and applications
5. Language Models and Transformer models
6. Different types of Language models
7. Applications of Language models
8. Transformers and its architecture
9. BERT, RoBERTa, GPT variations
10. Applications of transformer models and Hugging face

1. Different principles of Prompt Engineering
2. What is Prompt Engineering
3. Types of Different Prompt Engineering techniques
4. Crafting effective prompts to LLMs
5. Priming Prompt
6. Prompt Decomposition

1. Generative AI lifecycle
2. What is RLHF
3. LLM pre-training and scaling
4. Different fine-tuning techniques

1. Use cases of word embeddings
2. Word embeddings
3. Word Embeddings: Word2Vec, GloVe, FastText
4. Contextual Embeddings: ELMo, BERT, GPT
5. Sentence Embeddings: Doc2Vec, Infersent, Universal Sentence Encoder
6. Subword Embeddings: BPE (Byte Pair Encoding), Sentence Piece
7. Use case of Embeddings

1. Use of chunking the document
2. Chunking
3. Traditional effective chunking techniques
4. Problems and limitations with traditional chunking techniques
5. Overcoming limitations of Traditional chunking
6. Advanced chunking techniques:
7. Character splitting
8. Recursive character splitting
9. Document based chunking
10. Semantic Chunking
11. Agentic Chunking

1. Main components of RAG
2. What is RAG
3. High-level architecture of RAG
4. Building RAG using external data sources
5. Advanced RAG

1. What is Langchain
2. Core concepts of Langchain
3. Components of Langchain
4. How to use Langchain agents

1. LlamaIndex
2. Vector Databases
3. Why prefer Vector databases over traditional databases
4. Different types of Vector databases: Open-source and Close Source
5. Open-source: Chroma DB, Weaviate, Faiss, Qdrant
6. Close-Source Vector Databases: Pinecone, ArangoDB, Cloud-Based Solutions

1. Repurposing-Feature Extraction
2. Supervised Finetuning
3. Advanced techniques in Supervised finetuning: PEFT, LoRA, QLoRA

1. Amazon bedrock, Azure OpenAI, GCP

Text based LLMs:

• 1. Automatic Evaluation: BLUE score, ROUGE Score, METEOR, BERT Score
  2. Human Evaluation: Coherence, Factuality, Originality, Engagement
  3. Image based LLMs:
  4. Automatic Evaluation: Pixel-level metrics, FID (Frechet Inception Distance), IS (Inception Score),
     Perceptual Quality Metrics, Diversity Metrics
  5. Human Evaluation: Photorealism, Style, Creativity, Cohesiveness
  6. Audio generation LLMs:
  7. Automatic Evaluation: FAD (Frechet Audio Distance), IS (Inception Score), Perceptual Audio Quality
     Metrics – PAQM, PAQM – SNR (Signal-to-Noise Ratio), PAQM – PESQ (Perceptual Evaluation of Speech
     Quality)
  8. Human Evaluation: Perceptual Quality – PQ, PQ – Naturalness, PQ-Fidelity, PQ – Musicality, Task specific
     evaluation
  9. Video Generation LLMs:
  10. Automatic Evaluation: Fréchet Video Distance (FVD), Inception Score (IS), Perceptual Quality Metrics,
  11. Motion-Based Metrics – Optical Flow Error, Content-Specific Metrics
  12. Human Evaluation: Visual Quality, Temporal Coherence, Content Fidelit

1. Scalability and Performance Optimization
2. Model Deployment and Management
3. Security and Privacy
4. Monitoring and Logging
5. Cost Optimization
6. Model Interpretability and Explainability
7. Continuous Integration and Deployment (CI/CD)
8. Collaboration and Workflow Management
9. Regulatory Compliance
10. Disaster Recovery and Failover

1. ChatGPT, Gemini, Copilot, Claude, Perplexity etc.,