7 Generative AI Certifications for In-Demand Future Skills

Generative AI certifications can help you stand out from other job candidates in the dynamic field of generative artificial intelligence. As the field continues to evolve, organizations will keep investing in skilled staff who can develop and implement the technology.

Gen AI certifications validate your expertise and demonstrate your skills to employers as the demand for skilled tech professionals increases. I evaluated a wide range of certifications to see how they compared in terms of level, duration, and cost. Here are my picks for the top generative AI certifications.

Introduction to Generative AI: Best for learning basic generative AI concepts

Microsoft Azure AI Fundamentals (Generative AI): Best for familiarizing with Azure AI Studios 

Generative AI Overview for Project Managers: Best for understanding AI in project management

NVIDIA-Certified Associate Generative AI LLMs: Best for demonstrating expertise in generative AI and LLMs using NVIDIA solutions

IBM Generative AI for Data Scientists Specialization: Best for applying generative AI in data science projects

AWS Generative AI with Large Language Models: Best for real-world use case of generative AI and LLMs

IBM Generative AI for Software Developers Specialization: Best for integrating AI into development workflows

TABLE OF CONTENTS
ToggleBest generative AI certifications: Comparison chartTop seven AI certificationsTop seven AI certificationsNVIDIA-Certified Associate Generative AI LLMsFrequently asked questionsBottom line: Best generative AI certifications

Best generative AI certifications: Comparison chart

Here’s a summary of the experience level, certifying institutions, duration, cost, and prerequisites of the seven top generative AI courses to help you find the right fit for your skills and interests. Keep reading for more detailed information about each of our picks.

AI certificationCertifying bodyLevelDurationCostPrerequisitesIntroduction to Generative AIGoogle CloudBeginnerOne hour$59 per monthNo prerequisitesMicrosoft Azure AI Fundamentals: Generative AIMicrosoft LearnBeginnerThree hoursFreeFamiliarity with Azure and the Azure portalGenerative AI Overview for Project ManagersProject Management Institute (PMI)BeginnerOne hourFreeNo prerequisitesNVIDIA-Certified Associate Generative AI LLMsNVIDIAIntermediateOne hour$125 Basic understanding of generative AI and LLMsGenerative AI for Data Scientists SpecializationIBMIntermediateOne month at 10 hours a week$49 per monthPrior data science experienceGenerative AI with Large Language ModelsAWS and DeepLearning.AI Intermediate16 hours$49 per monthSome experience coding in PythonGenerative AI for Software Developers SpecializationIBMIntermediateOne month at 10 hours a week$49 per monthSome software engineering knowledge

Top seven AI certifications

Generative AI certification programs provide valuable skills for staying ahead in the dynamic field of AI, unlocking better job prospects with higher salaries.

Introductory generative AI courses cover the basics of machine learning, neural networks, and AI ethics. In contrast, specialized courses include lessons on natural language processing (NLP), image generation, and deep learning models. Advanced learners can also earn certificates that validate expertise in building and deploying generative AI models for applications in content creation, design, and automation.

Introduction to generative AI

Best for learning basic generative AI concepts | Beginner level

This introduction to generative AI course, offered by Google Cloud Training instructors on Coursera, provides an overview of the fundamental concepts of generative AI. The one-module course covers a range of topics, from the basics of generative AI to its applications. By the end of the course, you’ll be able to define generative AI, explain how it works, understand the different model types, and explore its various applications. 

Top seven AI certifications

Generative AI certification programs provide valuable skills for staying ahead in the dynamic field of AI, unlocking better job prospects with higher salaries.

Introductory generative AI courses cover the basics of machine learning, neural networks, and AI ethics. In contrast, specialized courses include lessons on natural language processing (NLP), image generation, and deep learning models. Advanced learners can also earn certificates that validate expertise in building and deploying generative AI models for applications in content creation, design, and automation.

Introduction to generative AI

Best for learning basic generative AI concepts | Beginner level

This introduction to generative AI course, offered by Google Cloud Training instructors on Coursera, provides an overview of the fundamental concepts of generative AI. The one-module course covers a range of topics, from the basics of generative AI to its applications. By the end of the course, you’ll be able to define generative AI, explain how it works, understand the different model types, and explore its various applications.

Visit Intro to Gen AI at Coursera

Why I picked it 

I chose this course because it offers a concise and informative introduction to generative AI. This course is specifically designed for those without prior knowledge of the field. The instructors use clear explanations and avoid complex jargon, making it accessible to anyone interested in the topic. 

The course also introduces Google tools for developing your own generative AI applications. As part of Google’s Introduction to Generative AI Learning Path specialization, Introduction to Generative AI allows you to build subject-matter expertise in this field and develop job-relevant skills with hands-on projects throughout the program. 

Skills acquired

At the end of this course, you will gain an understanding of the following:  

Definition of generative AI 

Generative AI model types

How generative AI works

Various generative AI applications

Key course details

Whom it’s for

Beginners looking for an introductory course on Generative AI and its real-world applications

Career tracks

Data analyst, prompt engineer, and AI product manager

Course requirements

No prerequisites

Course fee, duration, and format

Free to audit

$59 per month Coursera Plus subscription for a shareable certificate

One hour to complete

Self-paced online learning via Coursera

Course content and assessments

Explains what generative AI is, how it’s used, and how it differs from traditional machine learning methods

Covers Google Tools to help you develop your generative AI apps

One assessment is required to pass

Part of the Introduction to Generative AI Learning Path Specialization

Microsoft Azure AI Fundamentals: Generative AI

Best for familiarizing with Azure AI studio | Beginner level

The Azure AI Fundamentals Generative AI course introduces generative AI technology, focusing on Microsoft Azure services and covering the fundamentals of generative AI.

This course also explains how large language models form the foundation of generative AI and details the capabilities of Azure AI Studios, the efficiency gains provided by generative AI applications like copilots, the importance of fine-tuning prompts and responses, and how Microsoft’s responsible AI principles drive ethical AI advancements in the field of generative AI.

Visit AI Fundamentals at Microsoft Learn

Why I picked it 

I chose this course because it covers fundamental concepts and practical applications of generative AI technology, focusing on Azure services. Its main objective is to help you learn how to use Azure AI Studio and understand the importance of responsible AI principles. 

This course will also teach you how to design a responsible generative AI solution, assess and minimize potential risks, and effectively manage its operation. As a Microsoft Learn course, it provides direct insights from industry experts and exclusive access to Microsoft resources, ensuring you learn best practices from the leaders in the field.

Skills acquired

By the end of the course, you’ll be able to understand the following: 

How LLMs form the foundation of generative AI

The capabilities of Azure AI Studio

How generative AI applications like copilots improve efficiency

How to fine-tune prompts and responses for better outcomes

Ethical considerations and responsible AI principles in developing and deploying generative AI solutions

Key course details

Whom it’s for

Beginner- to intermediate-level Microsoft developers who want to leverage the Azure OpenAI Service to build AI-powered solutions

Career tracks

AI engineers, developers, and solution architects

Course requirements

Familiarity with Azure and the Azure portal

Course fee, duration, and format

Free 

Four hours

Self-paced online learning via Microsoft Learn

Course content and assessments

There are four modules in this course: 

Introduction to generative AI

Plan and prepare to develop AI solutions on Azure

Implement a responsible generative AI solution in Azure AI Foundry

Get started with AI agent development on Azure

Generative AI Overview for Project Managers

Best for understanding AI in project management | Beginner level

The Generative AI Overview for Project Managers is an online course offered by the Project Management Institute (PMI) as part of its professional development course portfolio. It is designed to give project managers a comprehensive understanding of artificial intelligence and generative AI, as well as its various applications in project management.

By completing this course, project managers will also earn five PDUs (four for Ways of Working and one for Business Acumen). 

Enroll for Generative AI at PMI

Why I picked it 

As a microlearning course offered by PMI, a globally recognized authority in project management, project managers can trust the quality and credibility of its content. I picked this course because it helps project managers enhance their understanding and application of generative AI within the project management domain. 

This course offers a hands-on learning experience that project management professionals can apply to their next project. Its content has also been updated to reflect the latest on generative AI, including new resources, practical examples, recent thought leadership research, and access to PMI Infinity in the AI Tool Library. 

Skills acquired

By the end of the course, you’ll gain a deep understanding of the following: 

Definitions of artificial intelligence (AI) and generative AI

Generative AI applications in project management

Generative AI project manager tools for maximizing efficiency

Best practices for project management in AI as a way of working

Key course details

Whom it’s for

Project managers who want to learn more about generative AI within the project management domain

Career tracks

Project manager, project coordinator, and agile facilitator

Course requirements

No prerequisites 

Course fee, duration, and format

Free 

One hour

Self-paced online learning via the Project Management Institute

Course content and assessments

There are five lessons in this micro-learning course: 

Introduction to GenAI

Enhancing PM with GenAI

Voice of the PM

ChatGPT Lab

AI Tool Library

NVIDIA-Certified Associate Generative AI LLMs

Best for demonstrating expertise in generative AI and LLMs using NVIDIA solutions | Intermediate level

The NVIDIA-Certified Associate Generative AI LLMs certification is a foundational credential for individuals involved in developing, integrating, and maintaining AI-driven applications using generative AI and large language models with NVIDIA solutions. This certification validates the fundamental concepts required for working with generative AI and LLMs, making it an efficient learning opportunity for AI DevOps engineers, data scientists, ML engineers, and more. 

The exam for this certification covers essential topics, including machine learning fundamentals, neural networks, prompt engineering, data analysis, experimentation, software development, Python libraries for LLMs, integration, and deployment.

Visit Generative AI LLMs at NVIDIA

Why I picked it 

Understanding how to train, fine-tune, and deploy LLMs is an essential skill for AI developers. This certification is designed to assess your knowledge and skills in generative AI and LLMs within the context of NVIDIA’s solutions and frameworks. 

As an official NVIDIA certification, it’s recognized within the industry and shows employers you have the necessary skills and knowledge to work with NVIDIA’s leading AI solutions. Ultimately, this certification provides you with an edge within a competitive field because it combines industry recognition, practical applications, and alignment with NVIDIA solutions.

Skills acquired

This certification will give you a range of foundational skills and knowledge in the following areas:

Fundamentals of ML and neural networks

Prompt engineering

Data analysis and visualization

Data preprocessing and feature engineering

Experiment design

Python libraries for LLMs

LLM integration and deployment

Key course details

Whom it’s for

Entry-level AI professionals, data scientists, and senior researchers who want to validate their skills in generative AI and LLMs using NVIDIA solutions 

Career tracks

AI developer, ML engineer, software engineer, and data scientist

Certification exam requirements

Basic understanding of generative AI and large language models

Exam fee, duration, and format

$125 

One hour (50–60 questions)

Online and proctored remotely

Exam content and assessments

Topics covered in the exam include the following: 

Fundamentals of machine learning and neural networks

Data analysis and visualization

Data preprocessing and feature engineering

Python libraries for LLMs

LLM integration and deployment

Upon passing the exam, participants will receive a digital badge from NVIDIA and an optional certificate that indicates the certification level and topic. The certification is valid for two years from its issuance, and recertification may be achieved by retaking the exam.

Generative AI for Data Scientists Specialization 

Best for applying generative AI in data science projects | Intermediate level

Taught by four experts from IBM, the Generative AI for Data Scientists Specialization course on Coursera is designed to help data professionals understand and implement generative AI in their data science projects. It is a three-course specialization that covers the basics of generative AI, prompt engineering concepts, tools, and techniques, and how to apply generative AI throughout the data science methodology.

The specialization includes hands-on projects and activities to reinforce learning and practical application of generative AI skills. Participants will learn how to use generative AI models for text, code, image, audio, and video generation, as well as data augmentation, feature engineering, and model development and refinement.

Get IBM Generative AI at Coursera

Why I picked it 

The specialization is specifically designed for data scientists, and it deep-dives into real-world data science problems where generative AI can be applied. It includes hands-on scenarios where you’ll learn to use generative AI models for querying and preparing data, enhancing data science workflows, augmenting datasets, and refining machine learning models.

The Generative AI for Data Scientists Specialization course also introduces powerful tools like GPT-3.5, ChatCSV, and Tomat.ai and demonstrates how to seamlessly integrate them into data science workflows.

Skills acquired

At the end of the course, you’ll gain a deep understanding of the following: 

Real-world generative AI use cases

Popular AI models and tools for text, code, image, audio, and video

Appropriate generative AI tools for data science 

Generative AI prompt engineering concepts and examples

Prompt techniques to generate and augment datasets for developing and refining ML models

Key course details

Whom it’s for

Data scientists and aspiring data science professionals who want to apply generative AI into their projects

Career tracks

Data scientist, data analyst, AI consultant, and product analyst

Course requirements

Prior data science experience

Course fee, duration, and format

$49 per month Coursera subscription

One month at 10 hours a week

Online via Coursera

Course content and assessments

This three-course series specialization includes the following: 

Generative AI: Introduction and Applications

Generative AI: Prompt Engineering Basics

Generative AI: Elevate Your Data Science Career

To pass the three-course specialization, learners must complete three modules for each course, which include readings, assignments, and discussion prompts.

Generative AI with Large Language Models

Best for real-world use case of generative AI and LLMs | Intermediate level

Generative AI with Large Language Models is a joint offering of AWS and DeepLearning.ai, two cloud computing and AI leaders. Through this collaboration, learners can benefit from the expertise and resources of AWS and DeepLearning.ai in the domain of generative AI with LLM, helping them gain foundational knowledge, practical skills, and a functional understanding of how LLMs work and how they can be deployed effectively in real-world scenarios.

Visit Generative AI at Coursera

Why I picked it 

I chose this certification because it offers a hands-on, practical approach to working with the latest AI technologies in real-world scenarios. Unlike courses that focus solely on the technical aspects of LLM, it tackles the entire generative AI life cycle — from data gathering to performance evaluation and deployment. You’ll also learn from industry practitioners about the challenges and opportunities that generative AI creates for businesses.

Skills acquired

At the end of the three-module course, you’ll gain the following: 

Foundational knowledge and understanding of how generative AI works

Awareness of the latest research on generative AI and how companies use this technology

Instructions for expert AWS AI practitioners who build and deploy AI in business use cases

Key course details

Whom it’s for

AI developers and engineers who want to learn real-life applications of generative AI and LLMs

Career tracks

LLM model developer, ML engineer, AI product manager, and LLM solutions architect

Course requirements

Experience with coding in Python

Course fee, duration, and format

$49 per month Coursera subscription

Approximately 16 hours

Online via Coursera

Course content and assessments

There are three modules in this course: 

Generative AI use cases, project life cycle, and model pre-training

Fine-tuning and evaluating large language models

Reinforcement learning and LLM-powered applications

Generative AI for Software Developers Specialization

Best for integrating AI into development workflows | Intermediate level

Whether you’re a seasoned developer or a beginner, this specialization will help you enhance your programming capabilities by incorporating generative AI techniques into your projects. 

Throughout this specialization’s three self-paced course series, you will learn the basics of generative AI, including its applications, models, and tools for generating text, code, images, audio, and video. You will also learn about prompt engineering, exploring approaches and tools such as Prompt Lab, Spellbook, and Dust to enhance your generative AI skills.

Enroll for AI for Software Developers at Coursera

Why I picked it 

This course provides hands-on experience with tools like IBM watsonx and open-source libraries to help you integrate generative AI into development workflow tasks. You will also benefit from the knowledge and expertise of IBM and learn the latest advancements and best practices in the field. This specialization format breaks down the learning into manageable modules, offering a structured and comprehensive approach to mastering generative AI. 

Skills acquired

At the end of the three-module course, you’ll learn the following: 

Real-world generative AI use cases and popular generative AI models

Tools and techniques to generate snippets, scripts, test cases, and applications using generative AI models 

Generative AI prompt engineering concepts and examples

How to develop innovative software engineering solutions using AI-powered tools and LLMs  

Key course details

Whom it’s for

AI developers and engineers who want to learn real-life applications of generative AI and LLMs

Career tracks

LLM application  developer, full-stack developer, prompt engineer, and solutions developer

Course requirements

Knowledge in software engineering 

Course fee, duration, and format

$49 per month Coursera subscription

One month at 10 hours a week

Online via Coursera

Course content and assessments

This three-course series includes the following: 

Generative AI: Introduction and Applications

Generative AI: Prompt Engineering Basics

Generative AI: Elevate Your Software Development Career

Real-world applications of generative AI certifications

Generative AI certifications aren’t just about theoretical knowledge; they equip professionals with the skills to tackle diverse real-world challenges across industries. Here are some of their notable applications.

Content creation and marketing

Generative AI certifications empower marketers and creatives to produce high-quality content for various platforms. They help them understand how to use AI tools effectively, including prompt engineering, content generation, and data analysis.

Content creators and marketing teams can develop ad campaigns, generate engaging website copy, and brainstorm blog post ideas using generative AI solutions. Beyond content ideation and generation, AI tools increase productivity and efficiency, so having the skills to automate repetitive tasks and simplify workflows will help marketers focus on strategic initiatives.

Product design and prototyping

Mastering generative AI empowers product designers to accelerate innovation through rapid prototype creation. Using the right AI tools, designers can automatically generate design variations and concepts, freeing valuable time for creative exploration and ideation. With targeted prompts, generative AI models can produce UI/UX mockups, technical documentation, and user stories precisely aligned with the design objectives.

Data generation and training 

Generative AI creates synthetic but realistic training data for AI models, enhancing output quality and reducing the need for extensive real-world datasets. It makes for reliable predictive analytics tools by automatically analyzing historical data and forecasting trends. Mastering the right generative AI tool for data generation and AI model training gives data professionals a significant competitive advantage.

Enterprise implementation

Within organizations, certified experts lead the implementation and deployment of generative AI technologies to automate manual tasks, personalize user experiences, and drive innovation. Certified AI professionals can lead the adoption of generative AI solutions for different business use cases, including knowledge management, workflow automation, and scalable solutions.

Frequently asked questions

Does generative AI require coding?

It’s not always necessary. Building a generative AI model from scratch often requires coding to customize it for specific needs, but when dealing with pre-built models, extensive coding is not required, as these models have user-friendly interfaces and require little to no programming. Additionally, there are no-code solutions that come with drag-and-drop interfaces and natural language prompts that let you construct generative AI apps without writing a single line of code.

Is a generative AI certification course worth the investment?

If you are interested in building a career in AI, yes. Certifications make you stand out to potential employers and demonstrate your commitment to continuous learning and development. Or if you are interested in learning more about generative AI and its applications in various industries, a certification course may be worth the investment. It can help you gain valuable skills and knowledge to apply to your current job or transition into a new career. 

How can I choose the right generative AI certification?

The best generative AI certification course for you will depend on your knowledge and experience with generative AI and your specific goals and interests. If you are new to generative AI, look for beginner-friendly courses that provide a solid foundation in the basics. If you are more experienced, consider more advanced courses that dive deeper into certifications for prompt engineering, model fine-tuning, deployment, and more.

Ensure the course covers the topics and skills you are interested in learning. As much as possible, only take courses from a reputable institution or organization in the field. A certification from a recognized entity can boost your credibility and increase your chances of getting hired. Also take into account your schedule and preferred learning style. Look for courses that offer flexible timing, online options, and self-paced learning and that are within your budget.

Can I become an AI expert without a degree?

Having a degree in computer science, engineering, or a related field provides a strong foundation when breaking into the AI field, but it’s not needed. You can become an AI expert without a traditional degree by taking certifications, building your portfolio, and seeking mentorship within the AI community. 

Platforms like Coursera, edX, and Udacity offer numerous affordable AI courses and certifications that can help you expand your knowledge and hone your skills. You can also build your portfolio through hands-on projects or contribute to open-source AI projects to learn from AI experts. Additionally, you can seek mentorship from professionals who can provide guidance, support, and connections within the AI community.

What companies should I work for post-certification?

After completing a generative AI certification, you may be interested in working for these top companies that are leaders in AI and technology.

Google is known for its innovative use of AI and machine learning in various products and services, such as Google Photos, Google Search, Google Assistant, and Gemini. Working at Google will allow you to work on projects that will help develop your generative AI skills.

NVIDIA is a leading technology company specializing in graphics processing units (GPUs) and AI computing. It is heavily involved in research and development in AI, including generative AI for applications such as image generation and style transfer. Working at NVIDIA means being involved in advanced AI projects at a company that employs the world’s leading experts in artificial intelligence.

OpenAI is an organization focused on artificial intelligence research and development. It is known for its work in creating advanced AI models, including generative models such as GPT-4, Dall-E, and more.

Bottom line: Best generative AI certifications

Generative AI certifications are gaining popularity, as the technology is transforming the tech landscape, driving creativity and innovation. The best programs offer a comprehensive curriculum, hands-on experience, and industry-recognized credentials tailored to your career goals. My recommendations highlight top programs that meet these standards, helping you choose the right path to boost your skills and expand your career opportunities.

Know more about the innovation giants shaping the future of AI by exploring our list of the top generative AI companies. 
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