Applied AI Engineering – Complete Interview Preparation & Revision Handbook

What you will learn

• ✓Understand AI Engineer roles, responsibilities and technical interview expectations.
• ✓Revise AI, Machine Learning and Deep Learning fundamentals.
• ✓Understand supervised, unsupervised learning and model evaluation metrics.
• ✓Strengthen Python, SQL and data engineering fundamentals.
• ✓Understand neural networks, backpropagation and gradient descent.
• ✓Learn self-attention, multi-head attention and Transformer architecture.
• ✓Understand LLM prompting, tokenization, generation and API integration.
• ✓Learn embeddings, vector search and vector database fundamentals.
• ✓Understand RAG architecture, retrieval strategies and advanced techniques.
• ✓Explore AI agents, tool calling, memory and agentic workflows.
• ✓Learn AI evaluation, testing, debugging and regression testing.
• ✓Understand production AI security, deployment and reliability.
• ✓Prepare for AI system design and architecture interviews.
• ✓Practice coding patterns, SQL queries and problem-solving approaches.
• ✓Answer advanced technical questions with examples and trade-offs.
• ✓Analyze real-world AI engineering scenarios and troubleshooting cases.
• ✓Revise complete AI Engineering concepts using diagrams and cheat sheets.