Course / Blockchain
Large Language Models
This course offers hands-on training in harnessing the capabilities of large language model, enabling learners to practically apply the principles and functionalities of cutting-edge language models.
Course Name
Large Language Models: Practical Applications
Course Duration
15 Hours
Course Engagement
Live Classes
Rewards
Certification
When do you want to start?
Started in IT thanks to Blockverse
Large Language Models training from BlockVerse Academy:-
Large Language Models (LLMs) such as GPT, Bard, and Llama are transforming the landscape of computer capabilities, redefining how machines comprehend human language. LLMs empower automated systems to generate creative prose, analyze customer sentiment, summarize vast document collections, aid programmers in code generation, and much more – the possibilities are limitless!
This practical course is your gateway to unlocking the potential of LLMs. Together, we will embark on a journey to build various applications that leverage LLMs, creating systems for X, Y, and Z.
Enroll in our LLM Practical Course and let’s explore the vast capabilities of Large Language Models.
You will learn this
This LLM Practical Course is tailored for individuals keen on mastering the practical applications of Large Language Models. Explore the following key aspects during the course:
Module 1 : Introduction
- Overview of LLMs
- They are neural networks that predict the next word
- High level description of of the transformer architecture
- Examples of what LLMs are good at
- Examples of what LLMs are not good at
- Overview of how to approach a new ML project
- Understand the problem
- Decide on a metric
- Decide on a baseline comparison model
- Find appropriate data
- Preprocess the data into the format you want
- Train the model
- Evaluate the model
- Analyze the results and find ways to improve the model
- Retrain the model, and repeat
Module 2 : Embeddings
- Explanation of what embeddings are
- Examples of applications where embeddings can be used
- Walk through of building an application using embeddings
- Description of problem
- Data collection and cleaning
- Extracting embeddings
- Using the extracted embeddings
- Evaluating the final model
- And comparing to a reasonable baseline
Module 3 : Fine Tuning
- Introduction to finetuning
- Pretrained models already exist, just train them a little bit more on your own data
- Examples of applications of fine-tuning
- Walk through of building an application using Fine Tuning
- Description of problem
- Data collection and cleaning
- Evaluating the model without fine tuning
- Fine tuning the model
- Evaluating the final model
- And comparing to performance before fine tuning
Module 4 : RAG
- Introduction to RAG
- Prompt design
- RAG uses a search engine to find relevant documents and then adds them to the prompt, this helps guide the LLM
- Examples of applications where RAG is useful
- Walkthrough of building an application using RAG
- Description of the problem
- Data collection and cleaning
- Evaluating the model without fine tuning
- Setting up a RAG/search engine
- Evaluating the model after adding RAG
Module 5 : Translate your unique idea into a project
Q&A Sessions
Key techniques for a Blockchain Full Stack Developer.
Understanding Large Language Models
Delve into the core concepts behind Large Language Models, including their architecture, training methodologies, and the science behind their ability to understand and generate human-like text.
Building Applications with LLMs
Learn hands-on techniques for building applications that harness the power of LLMs. Develop systems that can perform tasks like X, Y, and Z, showcasing the versatility of Large Language Models.
Practical Implementation of LLMs
Gain practical experience in implementing LLMs into real-world scenarios. Work on projects that require natural language understanding, sentiment analysis, and creative text generation.
Integration with Various Platforms
Explore how LLMs can be seamlessly integrated into different platforms and applications, ensuring compatibility and optimal performance.
Real-world Projects
Apply your acquired knowledge by working on real-world projects that showcase the practical applications of Large Language Models. Build systems that contribute to the A.I. Revolution.
Why we should go with this
Started in IT thanks to Blockverse
Be a Pioneer in A.I. Application Development
If you aspire to be at the forefront of A.I. application development, this practical course on Large Language Models is the ideal choice. Here’s why:
-
Contribute to the A.I. Revolution by mastering the applications of Large Language Models
-
Unlock diverse career opportunities in natural language processing, sentiment analysis, and creative content generation
-
Hands-on experience in building systems for various applications using cutting-edge A.I. technologies
-
Certificate of Proficiency to showcase your skills and expertise in Large Language Models
