Large Language Models (LLMs) and Reinforcement Learning (RL) Training Course

Large Language Models (LLMs) are sophisticated neural networks engineered to comprehend and produce human-like text derived from their input data. Reinforcement Learning (RL) constitutes a machine learning paradigm where an agent acquires decision-making capabilities by executing actions within an environment to maximise cumulative rewards.

This instructor-led, live training, available online or onsite, targets intermediate-level data scientists seeking a thorough grasp and practical expertise in both Large Language Models (LLMs) and Reinforcement Learning (RL).

Upon completion of this training, participants will be equipped to:

Grasp the components and operational mechanics of transformer models.
Optimise and fine-tune LLMs for specific tasks and applications.
Comprehend the foundational principles and methodologies of reinforcement learning.
Appreciate how reinforcement learning techniques can elevate LLM performance.

Course Format

Interactive lectures and discussions.
Extensive exercises and practice sessions.
Practical implementation within a live-lab environment.

Customisation Options

For bespoke training arrangements, please contact us to coordinate.

This course is available as onsite live training in South Africa or online live training.

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Course Outline

Introduction to Large Language Models (LLMs)

Overview of LLMs
Definition and significance
Applications in AI today

Transformer Architecture

Understanding transformers and their operation
Key components and features
Embedding and positional encoding
Multi-head attention
Feed-forward neural network
Normalization and residual connections
Transformer Models
- Self-attention mechanism
- Encoder-decoder architecture
- Positional embeddings
- BERT (Bidirectional Encoder Representations from Transformers)
- GPT (Generative Pretrained Transformer)
Performance Optimisation and Pitfalls
- Context length
- Mamba and state-space models
- Flash attention
- Sparse transformers
- Vision transformers
- The importance of quantisation
Enhancing Transformers
- Retrieval augmented text generation
- Mixture of models
- Tree of thoughts
Fine-Tuning
- Theory of low-rank adaptation
- Fine-Tuning with QLora
Scaling Laws and Optimisation in LLMs
- The importance of scaling laws for LLMs
- Data and model size scaling
- Computational scaling
- Parameter efficiency scaling
Optimisation
- The relationship between model size, data size, compute budget, and inference requirements
- Optimising performance and efficiency of LLMs
- Best practices and tools for training and fine-tuning LLMs
Training and Fine-Tuning LLMs
- Steps and challenges of training LLMs from scratch
- Data acquisition and maintenance
- Large-scale data, CPU, and memory requirements
- Optimisation challenges
- Landscape of open-source LLMs
Fundamentals of Reinforcement Learning (RL)
- Introduction to Reinforcement Learning
- Learning through positive reinforcement
- Definition and core concepts
- Markov Decision Process (MDP)
- Dynamic programming
- Monte Carlo methods
- Temporal Difference Learning
Deep Reinforcement Learning
- Deep Q-Networks (DQN)
- Proximal Policy Optimization (PPO)
- Elements of Reinforcement Learning
Integration of LLMs and Reinforcement Learning
- Combining LLMs with Reinforcement Learning
- How RL is used in LLMs
- Reinforcement Learning with Human Feedback (RLHF)
- Alternatives to RLHF
Case Studies and Applications
- Real-world applications
- Success stories and challenges
Advanced Topics
- Advanced techniques
- Advanced optimisation methods
- Cutting-edge research and developments
Summary and Next Steps

Requirements

Foundational understanding of Machine Learning

Audience

Data scientists
Software engineers

21 Hours

Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793

Large Language Models (LLMs) and Reinforcement Learning (RL) Training Course

Course Outline

Requirements

Upcoming Courses

Large Language Models (LLMs) and Reinforcement Learning (RL)

Large Language Models (LLMs) and Reinforcement Learning (RL)

Large Language Models (LLMs) and Reinforcement Learning (RL)

Large Language Models (LLMs) and Reinforcement Learning (RL)

Large Language Models (LLMs) and Reinforcement Learning (RL)

Related Categories

This site in other countries/regions

Europe

Asia Pacific

North America

South America

Africa / Middle East

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Large Language Models (LLMs) and Reinforcement Learning (RL) Training Course

Course Outline

Requirements

Upcoming Courses

Large Language Models (LLMs) and Reinforcement Learning (RL)

Large Language Models (LLMs) and Reinforcement Learning (RL)

Large Language Models (LLMs) and Reinforcement Learning (RL)

Large Language Models (LLMs) and Reinforcement Learning (RL)

Large Language Models (LLMs) and Reinforcement Learning (RL)

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Related Categories

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This site in other countries/regions

Europe

Asia Pacific

North America

South America

Africa / Middle East

Other sites