Learning Objectives
Fundamentals of Machine Learning and Neural Networks
[20%] Understand core concepts of machine learning and neural networks, including supervised and unsupervised learning, model evaluation, and neural network architectures.
Prompt Engineering and Alignment
[20%] Apply prompt engineering techniques to optimize LLM outputs and ensure model alignment with desired outcomes.
Data Analysis, Preprocessing, and Feature Engineering
[20%] Perform data analysis, preprocessing, and feature engineering to prepare datasets for training and evaluation of LLMs.
Experimentation and Experiment Design
[20%] Design and conduct experiments to evaluate LLM performance, including setting up controlled tests and interpreting results.
Software Development and LLM Integration
[20%] Develop software solutions that integrate LLMs using Python libraries, and deploy these models effectively within applications.
- Intellectual Point’s Generative AI and Large Language Models (LLMs) Training Course presents cutting-edge education in artificial intelligence, focusing on generating human-like text and automating content creation processes. This course provides comprehensive knowledge of LLM architectures, including OpenAI's GPT models, and equips participants with the hands-on skills necessary to design, implement, and optimize AI-driven solutions. It balances theoretical understanding with practical exercises tailored for real-world applications, ensuring participants can leverage these powerful tools efficiently.
- Within this training, you will dive into the core principles of AI and machine learning, unpack the mechanics behind LLMs, and explore their implementation for various use cases. By the end, you will apply your learning to develop AI applications, fine-tune models for specific tasks, and understand the ethical considerations in AI deployment. By the end of this course, participants will:
- 1) Master the architecture and operation of generative models like GPT.
- 2) Develop the ability to program and fine-tune AI models for specific applications.
- 3) Gain proficiency in using leading AI platforms and tools to implement AI solutions.
- 4) Understand and apply ethical AI practices to ensure responsible AI deployment.
- 5) Achieve the NVIDIA Certified Generative AI and LLMs certification, validating your expertise.
Module by Module Learning Outline
Tuition & Hours
Tuition is charged by course. The cost of the certification exam is not included in the tuition and is a separate cost based on the current rates as set by the vendor.
| Course | Total Hours | Tuition |
|---|---|---|
| AIML-102: Generative AI and LLMs | 72 | $4,499.00 |
Books & Supplies
There are no additional charges for books or supplies.
Indirect Costs
Should a student wish to obtain the NVIDIA Certified Professional: Generative AI LLMs certification exam, the cost is an additional fee not covered in tuition. While encouraged, the exam is not a required expense to be paid at the time of enrollment. To obtain a voucher for the certification exam, you will need to purchase it separately.
| Course | Exam | Exam Fee |
|---|---|---|
| AIML-102: Generative AI and LLMs | NVIDIA Certified Professional: Generative AI LLMs | $125 |
Program Award
Upon successful completion of the course, the student will receive a Certificate of Completion for Generative AI and LLMs Training.
* Exam fees are quoted based on time of publication. Voucher prices may change based on vendor rates and are updated accordingly. Please contact Intellectual Point to verify exam fee charges.
Class Registration
Date |
Price |
Location |
|
|---|---|---|---|
| January: 5, 2026 - January 30, 2026 - 6 PM - 10 PM (EST) Schedule: Mon - Fri |
$4,499.00 | In-Person & Virtual | Register |
Download Course PDF
AI in the Data Center an entry-level certification that validates foundational concepts of adopting artificial intelligence computing by NVIDIA in a data center environment.
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AI in the Data Center Course at Intellectual Point Includes:
-
Live instructor-led training in modern classrooms
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Thorough review of all NIVIDIA Certified Associate – AI in the Data Center topics by industry experts
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Hands-on labs on real NVIDIA’s GPU technologies
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24 x 7 access to the real labs in classrooms and remotely
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100% latest material & and realistic practice questions
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Confidence building hands-on training
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Authorized Pearson VUE testing at the same location to help you complete your exam*
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Study material, notes, videos, and practice questions included in the course price
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