8 Generative AI Certifications (2024) for Future-Ready Skills

Generative AI certifications can help you distinguish yourself from other job candidates in the dynamic field of generative artificial intelligence. As the field continues to rapidly evolve, disrupting nearly every industry, organizations will continue to invest not just in AI but in skilled staff who know how to develop and implement the technology.

Generative AI certifications can 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 on level, duration, and cost. Here are my picks for the top generative AI certifications in 2024:

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

Generative AI for Business Leaders: Best for Developing AI Implementation Policies

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

Best Generative AI Certifications: Comparison Chart

The chart below summarizes the experience level, certifying institutions, duration, cost, and prerequisites of the eight top generative AI courses to help you find the right one for your skills and interests, or keep reading for more detailed information about each of our picks.

AI Certification
Certifying Body
Level
Duration
Cost
Prerequisites

Introduction to Generative AI
Google Cloud
Beginner
One hour
$59 per month
No prerequisites

Microsoft Azure AI Fundamentals: Generative AI
Microsoft Learn
Beginner
Three hours
Free
Familiarity with Azure and the Azure portal

Generative AI Overview for Project Managers
Project Management Institute (PMI)
Beginner
One hour
Free
No prerequisites

Generative AI for Business Leaders
edX
Intermediate
One month
Free to audit
No prerequisites

NVIDIA-Certified Associate Generative AI LLMs
NVIDIA
Intermediate
One hour
$135 
Basic understanding of generative AI and LLMs

Generative AI for Data Scientists Specialization
IBM
Intermediate
One month at 10 hours a week
$49 per month
Prior data science experience

Generative AI with Large Language Models
AWS and DeepLearning.AI 
Intermediate
16 hours
$49 per month
Some experience coding in Python

Generative AI for Software Developers Specialization
IBM
Intermediate
One month at 10 hours a week
$49 per month
Some software engineering knowledge

TABLE OF CONTENTS
ToggleBest Generative AI Certifications: Comparison ChartTop 8 AI Certifications for 2024Introduction to Generative AIMicrosoft Azure AI Fundamentals: Generative AIGenerative AI Overview for Project ManagersGenerative AI for Business LeadersNVIDIA-Certified Associate Generative AI LLMsGenerative AI for Data Scientists SpecializationGenerative AI with Large Language ModelsGenerative AI for Software Developers SpecializationFrequently Asked Questions (FAQs)

Top 8 AI Certifications for 2024

Generative AI certification programs provide valuable skills for staying ahead in the dynamic field of AI, along with access to better job prospects and higher salaries. Introductory generative AI courses cover the basics of machine learning, neural networks, and AI ethics, while specialized courses include lessons on natural language processing (NLP), image generation, and deep learning models. Advanced learners can also earn certificates that validate expertise 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 is designed to span 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 different generative AI model types, and explore various applications of generative AI.

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 with no prior knowledge of the field, teaching you the basics of generative AI, how it works, and its applications. The instructors use clear explanations and avoid complex technical jargon, making it accessible to anyone interested in the topic.

The course also lets you familiarize yourself with Google tools you can use to develop your own generative AI applications. Additionally, Introduction to Generative AI is a part of the Introduction to Generative AI Learning Path specialization, allowing 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:

Basic knowledge of generative AI

Generative AI model types

How generative AI works

Various generative AI applications

Key Course Details

Who It’s For

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

Course Requirements

No prerequisites

Course Fee, Duration, and Format

Free to audit

$59 per month Coursera Plus subscription for shareable certificate

One hour to complete

Self-paced online learning via Coursera

Course Content and Assessments

Course module 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 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 covers the fundamentals of generative AI. It 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. The course can help you learn how to leverage Azure AI Studio and grasp the importance of responsible AI principles in the field, equipping you with hands-on exercises on how Azure AI Studio works and when to use it.

It also enables you to understand how to plan a responsible generative AI solution, how to measure and mitigate potential harm, and how to operate a responsible generative AI solution. Additionally, as a Microsoft Learn course, you’ll be learning best practices directly from industry experts and have access to Microsoft resources.

Skills Acquired

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

Knowledge of how LLMs form the foundation of generative AI

Familiarity with Azure AI Studio and its capabilities

Understand how generative AI applications like copilots improve efficiency

Ability to fine-tune prompts and responses for better outcomes

Awareness of ethical considerations and responsible AI principles in developing and deploying generative AI solutions

Key Course Details

Who It’s For

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

Course Requirements

Familiarity with Azure and the Azure portal

Course Fee, Duration, and Format

Free

Three hours

Self-paced online learning via Microsoft Learn

Course Content and Assessments

There are three modules in this course:

Fundamentals of Generative AI

Introduction to Azure AI Studio

Responsible Generative AI

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 offerings. It is designed to give project managers a comprehensive understanding of how generative AI can be applied in project management. Through this course, project managers will learn the definitions of artificial intelligence and generative AI and explore the various applications of generative AI in project management. You’ll also earn five PDUs for taking the course (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 organization in project management, project managers can trust the quality and credibility of the content. I picked this course because it caters to project managers, allowing them to enhance their understanding and application of generative AI within the project management domain.

This course offers a hands-on learning experience for project professionals, which they can apply right away to their project management approaches. 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 to the AI Tool Library.

Skills Acquired

By the end of the course, you’ll gain the following skills:

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

Who It’s For

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

Course Requirements

No prerequisites

Course Fee, Duration, and Format

Free

One hour

Self-paced online learning via Project Management Institute

Course Content and Assessments

There are six lessons in this micro-learning course:

Introduction to GenAI

Enhancing PM with GenAI

Voice of the PM

ChatGPT Lab

AI Tool Library

Knowledge Check

Generative AI for Business Leaders

Best for Developing AI Implementation Policies | Intermediate Level

edX’s Generative AI for Business Leaders course is designed to provide business leaders with a comprehensive understanding of generative artificial intelligence and how it can impact various industries. Dr. Brian Charles, a recognized leader in AI and the Internet of Things (IoT), is the lead instructor for this course. The course covers the basics of generative AI and its potential impacts on businesses. It also offers guidance on implementing AI strategies, enabling learners to develop internal policies or tools to guide decision-making within their organization.

Enroll for AI for Business Leaders at edX

Why I Picked It

This course goes beyond the technical aspects of generative AI and emphasizes its strategic application and impact on business operations. Choosing this course allows business leaders, startup founders, and managers to gain a foundational understanding of generative artificial intelligence and insights into the potential impacts of this technology on industries.

It’s also in a concise and accessible format, allowing busy professionals to have crucial knowledge of generative AI and equip themselves to draft well-informed policies. While you can’t earn a shareable certificate upon completing this course, it’s free to audit after you sign up.

Skills Acquired

At the end of this course, you’ll be able to:

Describe generative artificial intelligence

Identify potential impacts of generative AI on businesses or corporate functions

Develop internal policies to guide strategic decision-making around generative AI within your organization

Key Course Details

Who It’s For

Business leaders who need guidance in implementing AI strategies within an organization

Course Requirements

No prerequisites

Course Fee, Duration, and Format

Free to audit

One month

Online via edX

Course Content and Assessments

This course covers the following topics:

Introduction to Generative AI

Impact of Generative AI on Industries

Strategic Planning in the Age of AI

Learners need to earn a weighted grade of 60 percent to pass the course. This course is for auditing only, so learners will lose access to this course and their progress after a month.

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 (NCA 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 suitable for professionals such as AI DevOps engineers, data scientists, machine learning engineers, software engineers, and more. The exam 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 specifically 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 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

Who 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

Certification Exam Requirements

Basic understanding of generative AI and large language models

Exam Fee, Duration, and Format

$135

One hour (50 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 the issuance date, 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 offered 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. You will also familiarize yourself with tools like GPT 3.5, ChatCSV, and tomat.ai and learn how to integrate them into your data science workflows.

Skills Acquired

At the end of the course, you’ll gain the following knowledge and skills:

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

Who It’s For

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

Certification Exam 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 need to accomplish three modules for each course, including readings, assignments, and discussion prompts.

Generative AI with Large Language Models

Best for Real-World Use Case of Generative AI and LLMs | Intermediate Level

This course is a product of combined efforts between AWS and DeepLearning.ai, two prominent organizations in the fields of cloud computing and artificial intelligence. Through this collaboration, learners can benefit from the expertise and resources of AWS and DeepLearning.ai in the domain of generative AI with large language models. In this course, learners will have the opportunity to dive into the latest research on generative AI, particularly focusing on LLMs. You will gain foundational knowledge, practical skills, and a functional understanding of how LLMs work and how they can be deployed effectively in real-world applications.

Visit Generative AI at Coursera

Why I Picked It

Understanding how to train, fine-tune, and deploy LLMs is a crucial skill for AI developers. This course will provide you with the knowledge and tools needed to deploy generative AI models in various applications. Unlike some courses that focus solely on the technical aspects of LLM, this course tackles the entire generative AI lifecycle.

This means that you will understand how to build LLMs, from data gathering and model selection to performance evaluation and deployment. You’ll also learn from industry researchers and practitioners to deepen your understanding of various 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

Who It’s For

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

Course Requirements

Some experience 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 lifecycle, 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 already a seasoned developer or just starting, 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 delve into 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

Understanding how to train, fine-tune, and deploy LLMs is a crucial skill for AI developers. This course will provide you with the knowledge and tools needed to deploy generative AI models in various applications. You will also benefit from the knowledge and expertise of IBM, a leader in AI research and development, offering you the latest advancements and best practices in the field. Additionally, 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

Who It’s For

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

Course Requirements

Some software engineering knowledge

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

Frequently Asked Questions (FAQs)

Does Generative AI Require Coding?
Coding is often associated with generative AI, but it’s not always necessary. Building a generative AI model from scratch typically requires coding, as it allows you to tailor it to your specific needs. However, you don’t need extensive coding when you’re dealing with pre-built models, which 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, the answer is yes, an AI certification is well worth the time and money involved. 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 current 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 complex concepts and techniques.
Ensure the course covers the topics and skills you are interested in learning. Also, consider taking a course from a reputable institution or organization that is well-known in AI. A certification from a recognized entity can boost your credibility and help you stand out to potential employers. 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 can provide a strong foundation when breaking into the AI field, but it’s not always necessary. 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 provide you with the necessary 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 you with 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 top companies that are leaders in AI and technology.
Google: 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 can allow you to work on advanced AI projects and develop your skills on the cutting edge of generative AI.NVIDIA: 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 can allow you to be included in advanced projects at a company that employs the world’s leading AI experts.OpenAI: 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 certification is a hot topic because generative AI itself is revolutionizing tech, as it gives you leverage to achieve uniqueness and creativity in AI. With many certification options available, the best generative AI certification offers a comprehensive curriculum, hands-on experience, and industry-recognized credentials that fit your needs. My recommendations outline the top generative AI certification programs that meet these criteria so you can choose the best one for your career goals. Whichever program you choose, investing in a generative AI certification will undoubtedly enhance your skills and open up new opportunities for you.

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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