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Comprehensive Generative AI Engineering for Data Scientists and ML Engineers

This Comprehensive Generative AI (GenAI) course is for Machine Learning and Data Science professionals who want to dive deep into the world of GenAI and Large Language Models (LLMs). This course...

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Duration 5 days
Course Code WA3517
Available Formats Classroom

Overview

This Comprehensive Generative AI (GenAI) course is for Machine Learning and Data Science professionals who want to dive deep into the world of GenAI and Large Language Models (LLMs). This course covers various topics, from the foundations of LLMs to advanced techniques like fine-tuning, domain adaptation, and evaluation. Participants gain hands-on experience with popular tools and frameworks, including Python, Hugging Face Transformers, and open-source LLMs.

Skills Gained

  • Understand the architecture, training techniques, and evaluation methods for Large Language Models (LLMs)
  • Fine-tune and adapt open-source LLMs for domain-specific tasks and applications
  • Develop and optimize prompts for improved LLM performance and output quality
  • Implement advanced techniques such as Retrieval Augmented Generation (RAG) and vector embeddings
  • Evaluate and compare LLM performance using appropriate metrics and benchmarks

Prerequisites

  • Practical experience (6+ months) minimum in Python - functions, loops, control flow
  • Data Science basics - NumPy, pandas, scikit-learn
  • Solid understanding of machine learning concepts and algorithms
  • Regression, Classification, Unsupervised learning (clustering, Neural Networks)
  • Strong foundations in probability, statistics, and linear algebra
  • Practical experience with at least one deep learning framework (e.g., TensorFlow or PyTorch) recommended
  • Familiarity with natural language processing (NLP) concepts and techniques, such as text preprocessing, word embeddings, and language models

Course Details

Outline

LLM Foundations for ML and Data Science

  • Overview of Generative AI and LLMs
  • LLM Architecture and Training Techniques
  • Deep dive into the transformer architecture and its components
  • Exploring pre-training, fine-tuning, and transfer learning techniques

Prompt Engineering for LLMs

  • Introduction to Prompt Engineering
  • Techniques for creating effective prompts
  • Best practices for prompt design and optimization
  • Developing prompts for various NLP tasks
  • Text classification, sentiment analysis, named entity recognition

LLM Evaluation and Comparison

  • Overview of metrics and benchmarks for evaluating LLM performance
  • Techniques for comparing LLMs and selecting the best model for a given task
  • Evaluating and comparing LLMs for a specific NLP task

Fine-Tuning and Domain Adaptation

  • Introduction to Open-Source LLMs
  • Advantages and limitations in ML and data science projects
  • Preparing domain-specific datasets for fine-tuning LLMs
  • Techniques for adapting LLMs to new domains and tasks using transfer learning
  • Fine-tuning and adapting an open-source LLM for a specific domain

Advanced Fine-Tuning and RAG Techniques

  • Advanced fine-tuning techniques for LLMs
  • Implementing Retrieval Augmented Generation (RAG)
  • Improving LLM output quality and relevance
  • Building a RAG-powered LLM application for a specific use case

Vector Embeddings and Semantic Search

  • Introduction to vector embeddings and their applications in NLP
  • Using vector embeddings for semantic search and recommendation systems
  • Generating vector embeddings from text data
  • Implementing a similarity search using libraries like Faiss or Annoy

LLM Optimization and Efficiency

  • Techniques for optimizing LLM performance
  • Quantization and pruning
  • Applying optimization techniques to reduce LLM model size and inference time
  • Strategies for efficient deployment and serving of LLMs in production

Ethical Considerations and Best Practices

  • Addressing biases and fairness issues in LLMs
  • Ensuring transparency and accountability in LLM-powered applications
  • Best practices for responsible AI development and deployment
  • Navigating privacy and security concerns when working with LLMs and sensitive data

Conclusion

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Schedule

Upcoming Course Dates

There are currently no scheduled dates for this course. If you are interested in this course, contact us with the form below.

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FAQ

Does the course schedule include a Lunchbreak?

Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does Ascendient Learning deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

What does vendor-authorized training mean?

As a vendor-authorized training partner, we offer a curriculum that our partners have vetted. We use the same course materials and facilitate the same labs as our vendor-delivered training. These courses are considered the gold standard and, as such, are priced accordingly.

Is the training too basic, or will you go deep into technology?

It depends on your requirements, your role in your company, and your depth of knowledge. The good news about many of our learning paths, you can start from the fundamentals to highly specialized training.

How up-to-date are your courses and support materials?

We continuously work with our vendors to evaluate and refresh course material to reflect the latest training courses and best practices.

Are your instructors seasoned trainers who have deep knowledge of the training topic?

Ascendient Learning instructors have an average of 27 years of practical IT experience and have also served as consultants for an average of 15 years. To stay current, instructors spend at least 25 percent of their time learning new, emerging technologies and courses.

Do you provide hands-on training and exercises in an actual lab environment?

Lab access is dependent on the vendor and the type of training you sign up for. However, many of our top vendors will provide lab access to students to test and practice. The course description will specify lab access.

Will you customize the training for our company’s specific needs and goals?

We will work with you to identify training needs and areas of growth.  We offer a variety of training methods, such as private group training, on-site of your choice, and virtually. We provide courses and certifications that are aligned with your business goals.

How do I get started with certification?

Getting started on a certification pathway depends on your goals and the vendor you choose to get certified in. Many vendors offer entry-level IT certification to advanced IT certification that can boost your career. To get access to certification vouchers and discounts, please contact info@ascendientlearning.com.

Will I get access to content after I complete a course?

You will get access to the PDF of course books and guides, but access to the recording and slides will depend on the vendor and type of training you receive.

How do I request a W9 for Ascendient Learning?

View our filing status and how to request a W9.

Reviews

Easy to work with. Learning material pdfs were able to be printed out in color which was very nice to write on.

Good training material and good instruction. More time needs to be provided for the lab work.

Courseware was effective but would like to have some PDF material on BPML and XPATH

very good and spcecific course and above all a very good instructor. In few days I have learned a lot.

Exit certified was great as it is very in depth and hands on learning which made it very easy to learn this type of work.