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
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:
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.
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.
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.
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).
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:
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.
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.
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.
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:
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.
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.
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.
