Learning Resources & Tools
That Push The Boundaries of AI
Industry-leading courses and practical resources for students and professionals pioneering the future of AI.
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Most Popular Courses
How To Build A Large Language Model
Acquire the engineering skills to construct, train, and optimize sophisticated large language models.
Approx. 80 hours
Programming and Deep Learning
Advanced Transformer Architecture
Master the theory, mathematics, and implementation of advanced Transformer architectures for modern LLMs.
Approx. 30 hours
Deep Learning & Python Proficiency
LangChain for Production-Ready LLM Applications
Develop and operationalize complex, scalable LLM applications using advanced LangChain features and best practices.
Approx. 32 hours
Python & Basic LangChain
Python Programming Fundamentals
Acquire the core Python skills needed to write clear, functional code and begin your programming path.
Approx. 20 hours
No prior programming experience.
Practical Quantization for Large Language Models
Implement LLM quantization techniques (PTQ, QAT, GPTQ, GGUF) to reduce model size and improve inference speed.
Approx. 15 hours
LLM Fundamentals & Python
Python for LLM Workflows: Tooling and Best Practices
Build and manage LLM applications using Python, LangChain, LlamaIndex, and essential development practices.
Approx. 18 hours
Intermediate Python skills
Getting Started with PyTorch
Build and train fundamental deep learning models using PyTorch's core features like tensors, autograd, and neural network modules.
Approx. 18 hours
Basic Python & ML knowledge
Time Series Analysis and Forecasting
Analyze time-dependent data and build statistical forecasting models like ARIMA and SARIMA.
Approx. 15 hours
Basic Python and Pandas
RLHF: Reinforcement Learning from Human Feedback
Apply Reinforcement Learning from Human Feedback (RLHF) principles and techniques to align large language models.
Approx. 24 hours
Advanced ML & DL knowledge
Advanced Reinforcement Learning Techniques
Implement and apply advanced reinforcement learning algorithms to solve complex sequential decision-making challenges.
Approx. 70 hours
Python, ML & RL Fundamentals
Mastering Gradient Boosting Algorithms
Effectively implement, tune, and interpret advanced gradient boosting models for sophisticated machine learning applications.
Approx. 28 hours
Python & ML Fundamentals
Advanced PyTorch
Build, optimize, and deploy complex deep learning models using PyTorch's advanced capabilities.
Approx. 36 hours
Intermediate PyTorch & DL concepts
Trusted by Machine Learning Students and Professionals
Courses, references, and tools are utilized and cited by top universities and industry-leading tech companies worldwide.
MASTERCLASS
HOW TO BUILD A
LARGE LANGUAGE MODEL
30 Chapters, 700+ Pages of In-Depth Content
Guide to understanding and building state-of-the-art language models
Prerequisites: Strong foundations in programming and deep learning
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