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Rapid Application Development with Large Language Models (LLMs)
Recent advancements in both the techniques and accessibility of large language models (LLMs) have opened up unprecedented opportunities to help businesses streamline their operations, decrease...
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$500 USD
Duration
1 day
Course Code
NV-APPDEV-LLM
Available Formats
Classroom, Virtual
Overview
Recent advancements in both the techniques and accessibility of large language models (LLMs) have opened up unprecedented opportunities to help businesses streamline their operations, decrease expenses, and increase productivity at scale. Additionally, enterprises can use LLM-powered apps to provide innovative and improved services to clients or strengthen customer relationships. For example, enterprises could provide customer support via AI companions or use sentiment analysis apps to extract valuable customer insights. In this course you will gain a strong understanding and practical knowledge of LLM application development by exploring the open-sourced ecosystem including pretrained LLMs, enabling you to get started quickly in developing LLM-based applications.
Skills Gained
By participating in this workshop, you will:
- Find, pull in, and experiment with the HuggingFace model repository and Transformers API.
- Use encoder models for tasks like semantic analysis, embedding, question-answering, and zero-shot classification.
- Work with conditioned decoder-style models to take in and generate interesting data formats, styles, and modalities.
- Kickstart and guide generative AI solutions for safe, effective, and scalable natural data tasks.
- Explore the use of LangChain and LangGraph for orchestrating data pipelines and environment-enabled agents.
Prerequisites
- Introductory deep learning, with comfort with PyTorch and transfer learning preferred. Content covered by DLI’s Getting Started with Deep Learning or Fundamentals of Deep Learning courses, or similar experience is sufficient.
- Intermediate Python experience, including object-oriented programming and libraries. Content covered by Python Tutorial (w3schools.com) or similar experience is sufficient.
Course Details
Topics
The workshop covers large language models from beginning to end, starting with fundamentals of transformers, progression into foundational large language models, and finishing in model/agentic orchestration. Each of these sections is designed to equip participants with the knowledge and skills necessary to progress further in developing useful LLM-powered applications.
Course Introduction
- Overview of workshop topics and schedule.
- Introduction to HuggingFace and Transformers.
- Discuss how LLMs can enhance enterprise applications.
Transformers and LLMs
- Introduce and motivate the transformer-style architecture from deep learning first principles.
- Understand input-output processing with tokenizers, embeddings, and attention mechanisms.
Task-Specific Pipelines
- Profile encoder models for different NLP tasks where they are most useful.
- Investigate the use of lightweight models for natural language embedding, classification, subsetting, and zero-shot prediction.
Seq2Seq with Decoders
- Introduce GPT-style decoder models for sequence generation and autoregressive tasks.
- Apply encoder-decoder architectures for applications like machine translation and few-shot task completion.
Multimodal Architectures
- Integrate different data modalities (text, images, audio) into LLM workflows.
- Explore multimodal models like CLIP for cross-modal learning, visual language models for image question-answering, and diffusion models for text-guided image generation.
Scaling Text Generation
- Explore LLM inference challenges and deployment strategies, including optimized server deployments.
- Incorporate LLMs into interesting applications that can scale to larger repositories and user bases.
Orchestration and Agentics
- Introduce LangChain for LLM orchestration and agentic workflows.
- Investigate use of agentics and tool-calling for integrating natural language with standard applications and data.
Final Assessment
- Build an LLM-based application integrating text generation, multimodal learning, and agentic orchestration.
Review and Wrap-up
- Review key learnings and answer final questions.
- Earn a certificate upon successful completion.
- Complete the workshop survey.
Schedule
1 options available
-
Jul 28, 2025 - Jul 28, 2025 (1 day)
Virtual | 10:30 AM – 6:30 PM EDT Language English Select from 1 options below Virtual |10:30 AM – 6:30 PM EDT- Enroll
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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.
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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.
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We have training locations across the United States and Canada - View a complete list of classroom training locations.
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At Ascendient Learning, we offer training that is Instructor-Led, Online, Virtual, and Self-Paced.
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Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.
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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.
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We continuously work with our vendors to evaluate and refresh course material to reflect the latest training courses and best practices.
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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.
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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.
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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.
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Reviews
Great instructor, clear and concise course. Labs were easy to follow and worked perfectly.
great class and packed with material, would have lived to spread it more into many days but overall very informative.
The training was great . But i expected some of the Networking concepts would be covered in this certification .
this class was informative, made me think about certifying for the suse manager cert.
I like their training. A lot of material covered. The labs are very good. l learned a lot.
