Teaching programming from scratch to a high level with a professional methodology. We begin with the algorithms to understand the basic of programming, then we do the asginement with C language, then we move forward with oriented object programing (JAVA), then we end with (python).

In this courses, we will discover the methodology of data science, we will learn how to work with supervised and unsupervised learning. and we will discover the type of the data (stractred, semi-stractred, and unstractred data). we will also discover the steps to handle the projects.

The "Machine Learning with Python and PyTorch: Practical Hands-on Training" course provides hands-on experience in using Python and PyTorch for deep learning. Participants will learn to build, train, and deploy neural networks, including CNNs, RNNs, and GANs. The course covers data preprocessing, optimization techniques, and model evaluation. Through coding exercises and projects, participants gain practical skills in implementing deep learning algorithms and deploying models for inference. By the end of the course, participants will be proficient in Python programming and PyTorch, ready to tackle diverse deep-learning tasks.

In today's rapidly evolving technological landscape, Large Language Models (LLMs) have emerged as a groundbreaking innovation, transforming the way we interact with machines and process vast amounts of textual information. This comprehensive course, "Mastering Large Language Models with Langchain: Building Chatbots and Document-based QA Systems," is designed to equip participants with the skills and knowledge to harness the power of LLMs for creating advanced chatbots and document-based question-answering (QA) systems.