Learn data warehousing, OLTP vs OLAP, star schema, snowflake schema, ETL, and analytics design.
Scalability, distributed systems, caching, databases, microservices, and architecture patterns.
Master coding interview patterns, arrays, trees, graphs, DP, sliding window, and more.
Transformers, RAG, agents, fine-tuning, embeddings, vector databases, and production LLMs.
Text processing, embeddings, tokenization, sequence models, transformers, and NLP pipelines.
Neural networks, CNNs, RNNs, transformers, optimization, and deep learning frameworks.
Supervised learning, unsupervised learning, feature engineering, model evaluation, and deployment.
Linear algebra, probability, statistics, calculus, optimization, and ML mathematics.
Video-based Data Structures and Algorithms course with explanations and coding practice.