Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Will I earn university credit for completing the Specialization?

This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

Spezialisierung „Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs “

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Spezialisierung „Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs “

Launch career in NVIDIA Generative AI with LLMs.

Master AI, ML, and Deep Learning using NVIDIA tools.

Dozent: Whizlabs Instructor

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6-teilige Kursreihe

Befassen Sie sich eingehend mit einem Thema

aus 55 Bewertungen von Kursen in diesem Programm

Stufe Mittel

Empfohlene Erfahrung

16 Wochen zu vervollständigen

unter 3 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

6-teilige Kursreihe

Befassen Sie sich eingehend mit einem Thema

aus 55 Bewertungen von Kursen in diesem Programm

Stufe Mittel

Empfohlene Erfahrung

16 Wochen zu vervollständigen

unter 3 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Validating your expertise in generative AI, LLMs, and deep learning techniques.
Gaining industry recognition for your AI and machine learning skills.
Enhancing career opportunities in AI research, development, and cloud-based AI solutions.
Positioning yourself as a specialist in cutting-edge AI technologies.

Kompetenzen, die Sie erwerben

Kategorie: Convolutional Neural Networks
Kategorie: Data Ethics
Kategorie: Data Preprocessing
Kategorie: Deep Learning
Kategorie: Generative Model Architectures
Kategorie: Image Analysis
Kategorie: Large Language Modeling
Kategorie: LLM Application
Kategorie: Model Evaluation
Kategorie: Natural Language Processing
Kategorie: Plot (Graphics)
Kategorie: Prompt Engineering Tools
Kategorie: Recurrent Neural Networks (RNNs)
Kategorie: Responsible AI
Kategorie: Supervised Learning
Kategorie: Time Series Analysis and Forecasting
Kategorie: Transfer Learning
Kategorie: Unsupervised Learning

Werkzeuge, die Sie lernen werden

Kategorie: Generative AI
Kategorie: Prompt Engineering

Wichtige Details

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Erlernen Sie ein Thema oder ein Tool mit echten Projekten.
Entwickeln Sie ein fundiertes Verständnisse der Kernkonzepte.
Erwerben Sie ein Karrierezertifikat von Whizlabs.

Spezialisierung - 6 Kursreihen

NVIDIA-Certified Generative AI LLMs - Associate Specialization is intended for candidates working in AI, machine learning, and deep learning roles who want to enhance their expertise in generative AI and large language models (LLMs). This specialization will prepare learners to design, build, optimize, and deploy generative AI solutions using NVIDIA technologies. If you're seeking a role in AI development, research, or cloud-based AI solutions, this focused course will equip you with the necessary skills and knowledge to become NVIDIA Generative AI LLMs - Associate certified.

Understanding of generative AI and LLMs.
Fundamental machine learning and deep learning concepts.
Knowledge of natural language processing (NLP) and transformer-based models.
LLM deployment strategies and prompt engineering techniques.
Ethical considerations in AI development and deployment.

This specialization is divided into a set of 6 courses covering the domain requirements for appearing in the NVIDIA-Certified Generative AI LLMs - Associate certification. The course details are as follows:

Course 1: NVIDIA: Fundamentals of Machine Learning

Course 2: NVIDIA: Fundamentals of Deep Learning

Course 3: NVIDIA: NLP: From Foundations to Transformers

Course 4: NVIDIA: Large Language Models and Generative AI Deployment

Course 5: NVIDIA: Prompt Engineering and Data Analysis

Course 6: NVIDIA: LLM Experimentation, Deployment, and Ethical Considerations

Übungsprojekt

Learners will be provided with Lab Demonstrations based on the topics discussed in the courses that are part of this specialization. They will also have the opportunity to understand the demo labs. However, these demo hands-on labs are optional for learners to perform.

NVIDIA: Fundamentals of Machine Learning

KURS 1, 6 Stunden

Was Sie lernen werden

Understand the fundamentals of AI, ML, and Deep Learning, and their key differences.
Implement supervised learning techniques like classification and regression.
Apply clustering methods and time series analysis using ARIMA.
Leverage NVIDIA RAPIDS for GPU-accelerated ML workflows.

Kompetenzen, die Sie erwerben

Kategorie: Unsupervised Learning

Kategorie: Supervised Learning

Kategorie: Deep Learning

Kategorie: Model Evaluation

Kategorie: Machine Learning Algorithms

Kategorie: Machine Learning

Kategorie: Artificial Intelligence

Kategorie: Time Series Analysis and Forecasting

Kategorie: Model Optimization

Kategorie: Classification Algorithms

Kategorie: Generative AI

Kategorie: Model Training

Kategorie: Regression Analysis

Kategorie: Artificial Intelligence and Machine Learning (AI/ML)

Kategorie: Feature Engineering

Kategorie: Data Preprocessing

NVIDIA: Fundamentals of Deep Learning

KURS 2, 4 Stunden

Was Sie lernen werden

Understand deep learning fundamentals, including neuron data processing and model training.
Implement multi-class classification and CNNs for image recognition tasks.
Apply transfer learning with pre-trained models to improve deep learning performance.

Kompetenzen, die Sie erwerben

Kategorie: Transfer Learning

Kategorie: Deep Learning

Kategorie: Model Optimization

Kategorie: Linear Algebra

Kategorie: Convolutional Neural Networks

Kategorie: Artificial Neural Networks

Kategorie: Tensorflow

Kategorie: Artificial Intelligence and Machine Learning (AI/ML)

Kategorie: Generative AI

Kategorie: Computer Vision

Kategorie: PyTorch (Machine Learning Library)

Kategorie: Model Training

Kategorie: Image Analysis

Kategorie: Machine Learning Methods

Kategorie: Applied Machine Learning

Kategorie: Machine Learning

Kategorie: Classification Algorithms

Kategorie: Data Processing

NVIDIA: Fundamentals of NLP and Transformers

KURS 3, 4 Stunden

Was Sie lernen werden

Understand NLP fundamentals, key tasks, and real-world applications.
Implement NLP techniques, including tokenization, word embeddings, and sequence models.
Explore transformer architecture, self-attention mechanisms, and encoder-decoder models.

Kompetenzen, die Sie erwerben

Kategorie: Unstructured Data

Kategorie: Embeddings

Kategorie: Generative Model Architectures

Kategorie: Data Pipelines

Kategorie: Artificial Neural Networks

Kategorie: Machine Learning Methods

Kategorie: Model Evaluation

Kategorie: Data Preprocessing

Kategorie: Natural Language Processing

Kategorie: Recurrent Neural Networks (RNNs)

Kategorie: Machine Learning

Kategorie: Token Optimization

Kategorie: Generative AI

Kategorie: Large Language Modeling

NVIDIA: Large Language Models and Generative AI Deployment

KURS 4, 4 Stunden

Was Sie lernen werden

Understand the foundational concepts of LLMs, including NLP and training data.
Explore model optimization techniques like loss functions, alignment, and PEFT.
Implement deployment strategies for LLMs and monitor performance using ONNX.

Kompetenzen, die Sie erwerben

Kategorie: Data Quality

Kategorie: Model Evaluation

Kategorie: Model Training

Kategorie: Large Language Modeling

Kategorie: Model Deployment

Kategorie: Fine-tuning

Kategorie: Natural Language Processing

Kategorie: LLM Application

Kategorie: Model Optimization

Kategorie: Deep Learning

Kategorie: Generative Model Architectures

Kategorie: Prompt Engineering

Kategorie: Generative AI

Kategorie: Data Cleansing

Kategorie: Machine Learning

Kategorie: MLOps (Machine Learning Operations)

NVIDIA: Prompt Engineering and Data Analysis

KURS 5, 3 Stunden

Was Sie lernen werden

Understand prompt engineering and its role in LLM optimization.
Apply P-tuning and RAG architecture for improved model performance.
Utilize data analysis and visualization techniques for effective NLP tasks.

Kompetenzen, die Sie erwerben

Kategorie: Prompt Engineering

Kategorie: Retrieval-Augmented Generation

Kategorie: Data Visualization Software

Kategorie: Text Mining

Kategorie: Prompt Engineering Tools

Kategorie: Data Analysis

Kategorie: Data Processing

Kategorie: Model Optimization

Kategorie: Unstructured Data

Kategorie: Fine-tuning

Kategorie: Plot (Graphics)

Kategorie: Large Language Modeling

NVIDIA: LLM Experimentation, Deployment, and Ethical AI

KURS 6, 5 Stunden

Was Sie lernen werden

Experiment with LLMs using hyperparameter tuning and A/B testing.
Apply version control and optimize AI workflows with NVIDIA tools like BioNeMo, Triton, and TensorRT.
Understand ethical AI principles, data privacy, and methods to minimize bias and enhance AI trustworthiness.