Explorepython

Master the fundamentals of LangChain to build LLM-powered applications. This beginner-friendly course guides you through prompt templates, chains, agents, conversational memory, and document loaders using Python and OpenAI.

Master the binary search algorithm to solve lookup problems in logarithmic time. Learn to implement iterative and recursive approaches, analyze time complexity, and apply this fundamental search technique to excel in technical coding interviews.

Master the sliding window algorithm to solve complex subarray and substring problems efficiently. Learn to transition from brute-force O(N^2) to optimal O(N) time complexity, preparing you to ace competitive programming and top-tier technical interviews with confidence.

Master the inner workings of Large Language Models by coding a complete GPT-style architecture from scratch. Learn tokenization, multi-head attention, pretraining, and supervised fine-tuning using PyTorch and Python. Build, train, and align your own deep learning models.

Accelerate your software engineering career by mastering computer science foundations, design patterns, testing, and DevOps with Docker. Then, leap into the future of software development by building stateful, multi-agent AI systems using LangGraph, Python, and LangChain.

Master Python programming from scratch. Go from fundamental syntax to building real-world projects in automation, machine learning with scikit-learn, and web development with Django.

Master the inner workings of LLMs by building a GPT-2-style transformer from scratch. Learn neural network fundamentals, GPU optimization, attention mechanisms, pre-training pipelines, instruction tuning, and policy optimization using PyTorch.

Master the LangChain Python framework to build intelligent, autonomous AI agents. Learn to implement conversations, streaming, RAG with vector stores, dynamic prompts, and custom middleware for production-ready applications.

Master the fundamentals of AI agents, LangChain, vector databases, and RAG. Learn to build stateful multi-agent workflows with LangGraph and integrate external tools using the Model Context Protocol (MCP) through hands-on labs.

Master the fundamentals of AI, Machine Learning, Deep Learning, and NLP. Build practical skills with hands-on algorithms, neural networks, and real-world applications.

Master Python for AI development, build reliable AI agents from first principles, implement high-performance hybrid search RAG pipelines, and establish systematic LLM evaluations for production-grade systems.

Learn to build and automate custom Claude Skills using the DBS framework. Connect Slack, Gmail, and Google Calendar, leverage RAG concepts like indexing and vector stores, and generate presentations automatically with Gamma.