Ace the AI Engineer Interviews

This course prepares candidates to confidently tackle AI engineer interviews by covering the most relevant and in-demand topics. You’ll explore neural network training (gradient descent, transfer learning, model compression, fine-tuning, synthetic data generation, and model alignment), language processing (tokenization, embeddings, and decoding/beam search), and transformer attention mechanisms (self-attention, cross-attention, and flash attention). You’ll gain a solid understanding of evaluation metrics like perplexity, BLEU, and ROUGE, and dive into modern AI challenges, including hallucinations, jailbreaks, and interpretability. You’ll also learn cutting-edge methods such as retrieval-augmented generation (RAG), few-shot learning, and chain-of-thought prompting, along with efficiency and scalability topics like Mixture of Experts, vector databases, and agentic AI behaviors.