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.

Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs Specialization

Launch career in NVIDIA Generative AI with LLMs. Master AI, ML, and Deep Learning using NVIDIA tools.

Instructor: Whizlabs Instructor

Included with Coursera Plus

Learn more

6 course series

Get in-depth knowledge of a subject

4.6

(19 reviews)

Intermediate level

Recommended experience

16 weeks to complete

at 3 hours a week

Flexible schedule

Learn at your own pace

6 course series

Get in-depth knowledge of a subject

4.6

(19 reviews)

Intermediate level

Recommended experience

16 weeks to complete

at 3 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

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.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English

30 practice exercises

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

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Advance your subject-matter expertise

Learn in-demand skills from university and industry experts
Master a subject or tool with hands-on projects
Develop a deep understanding of key concepts
Earn a career certificate from Whizlabs

Specialization - 6 course series

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

Applied Learning Project

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

Course 15 hours

What you'll learn

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.

Skills you'll gain

Supervised Learning, Unsupervised Learning, Regression Analysis, Machine Learning, Deep Learning, Feature Engineering, Data Processing, Artificial Intelligence, Predictive Modeling, Data Cleansing, Time Series Analysis and Forecasting, Classification And Regression Tree (CART), and Statistical Analysis

NVIDIA: Fundamentals of Deep Learning

Course 23 hours

What you'll learn

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.

Skills you'll gain

Deep Learning, Artificial Neural Networks, Data Processing, Image Analysis, Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Network Architecture, Supervised Learning, PyTorch (Machine Learning Library), Applied Machine Learning, Tensorflow, Machine Learning, and Linear Algebra

NVIDIA: Fundamentals of NLP and Transformers

Course 34 hours

What you'll learn

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.

Skills you'll gain

Natural Language Processing, Unstructured Data, Data Pipelines, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Methods, Text Mining, Artificial Neural Networks, and Data Processing

NVIDIA: Large Language Models and Generative AI Deployment

Course 44 hours

What you'll learn

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.

Skills you'll gain

Large Language Modeling, Generative AI, Application Deployment, Machine Learning Methods, PyTorch (Machine Learning Library), Tensorflow, Natural Language Processing, Prompt Engineering, MLOps (Machine Learning Operations), Data Cleansing, Continuous Monitoring, Machine Learning, and Deep Learning

NVIDIA: Prompt Engineering and Data Analysis

Course 53 hours

What you'll learn

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.

Skills you'll gain

Histogram, Prompt Engineering, Scatter Plots, Text Mining, Data Analysis, Data Visualization, Unstructured Data, Natural Language Processing, Data Visualization Software, and Large Language Modeling

NVIDIA: LLM Experimentation, Deployment, and Ethical AI

Course 64 hours

What you'll learn

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.

Skills you'll gain

Information Privacy, Version Control, Responsible AI, A/B Testing, Deep Learning, Artificial Intelligence, Machine Learning, Tensorflow, Scalability, PyTorch (Machine Learning Library), Large Language Modeling, Generative AI, MLOps (Machine Learning Operations), and Performance Tuning

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Whizlabs Instructor

Whizlabs

132 Courses88,471 learners

Offered by

Whizlabs

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Frequently asked questions

The specialization will be completed in 4 months

Basic understanding of generative AI and large language models, along with knowledge of Python, C, and AI frameworks like PyTorch and TensorFlow.

The courses can be taken in any order.

Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs Specialization

What you'll learn

Skills you'll gain

Tools you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

Advance your subject-matter expertise