Learning Objectives
Core Machine Learning and AI Knowledge
[25%] Covers foundational concepts in machine learning and AI, including understanding of neural networks, model architectures, and training methodologies essential for building generative AI systems.
Experimentation
[20%] Focuses on designing and conducting experiments to develop and refine AI models, emphasizing iterative testing, evaluation, and optimization techniques.
Multimodal Data
[15%] Addresses the integration and processing of diverse data types such as text, images, and audio, enabling the development of AI models that can interpret and generate across multiple modalities.
Software Development and Engineering
[15%] Involves applying software engineering principles to develop, deploy, and maintain AI applications, including proficiency in programming languages and development frameworks.
Data Analysis, Visualization, and Performance Optimization
[25%] Combines skills in analyzing and visualizing data to inform model development, along with techniques for optimizing performance to ensure efficient and effective AI solutions.
- The Multimodal Generative AI Training Course at Intellectual Point is meticulously curated to equip learners with cutting-edge skills necessary to work with advanced AI systems capable of processing and generating text, images, and audio simultaneously. This comprehensive course blends theoretical foundations with practical applications, facilitating a deep understanding of the complex algorithms that underlie multimodal AI technologies. Participants will gain hands-on experience in designing and implementing AI solutions that synthesize information across multiple data types. By the end of the course, learners will be poised to utilize generative AI models in various industries, enhancing creativity and operational efficiency.
- Throughout the training, you will explore the intricacies of neural networks, deep learning, and the integration of AI components to develop multi-capable AI agents. Engaging lectures and practical assignments will guide you through intricate topics such as cross-modal learning and transfer learning strategies. By the end, you'll be proficient in applying generative AI techniques to real-world scenarios, elevating your problem-solving capabilities. By the end of this course, participants will:
- 1) Develop AI models that seamlessly integrate data across multiple modalities.
- 2) Harness advanced neural network techniques to innovate generative AI systems.
- 3) Execute real-world projects using multimodal AI to solve complex challenges.
- 4) Spearhead AI solution designs that foster cross-disciplinary innovations.
- 5) Obtain the NVIDIA-Certified Associate: Generative AI Multimodal, enhancing career trajectory.
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-103: Multimodal Generative AI | 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 Associate: Generative AI Multimodal 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-103: Multimodal Generative AI | NVIDIA Certified Associate: Generative AI Multimodal | $125 |
Program Award
Upon successful completion of the course, the student will receive a Certificate of Completion for Multimodal Generative AI 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.
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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:
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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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