Multimodal AI courses can help you learn how models process and combine different inputs such as text, images, audio, or video. You can build skills in feature representation, alignment techniques, evaluation methods, and designing workflows that use multiple data types. Many courses introduce tools like Python libraries, model APIs, and frameworks that support building and testing multimodal AI systems.
Skills you'll gain: Responsible AI, AI Workflows, AI Orchestration, Agentic systems, Generative AI Agents, Artificial Intelligence, Coordination, AI Security, Data Ethics, Governance, Systems Architecture, Software Architecture, Scalability, Regulatory Compliance, Communication Strategies, Communication
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Multimodal Prompts, LLM Application, Generative Model Architectures, OpenAI API, Application Development, Prompt Engineering, Web Applications, Flask (Web Framework), Web Development, Software Development
Intermediate · Course · 1 - 4 Weeks

Pearson
Skills you'll gain: Generative AI, Large Language Modeling, PyTorch (Machine Learning Library), Generative Model Architectures, Multimodal Prompts, Image Analysis, Model Evaluation, Autoencoders, Hugging Face, Computer Vision, Convolutional Neural Networks, Artificial Neural Networks, LLM Application, Natural Language Processing, Deep Learning, Embeddings, Tensorflow, Transfer Learning, Performance Tuning
Intermediate · Specialization · 1 - 4 Weeks

DeepLearning.AI
Skills you'll gain: Retrieval-Augmented Generation, Multimodal Prompts, Embeddings, Large Language Modeling, Generative AI, Vector Databases, Image Analysis, Applied Machine Learning
Intermediate · Project · Less Than 2 Hours

Skills you'll gain: Prompt Engineering, Multimodal Prompts, Generative AI, AI Workflows, AI Orchestration, Microsoft Azure, Computer Vision, Image Analysis, Solution Design, Application Programming Interface (API)
Intermediate · Course · 1 - 4 Weeks

Microsoft
Skills you'll gain: Generative AI, Generative Model Architectures, Prompt Engineering, Responsible AI, Generative Adversarial Networks (GANs), MLOps (Machine Learning Operations), AI Security, Multimodal Prompts, Data Ethics, AI Workflows, Microsoft Azure, ChatGPT, Azure DevOps Pipelines, AI Orchestration, Azure DevOps, Model Deployment, AI Enablement, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Python Programming
Intermediate · Professional Certificate · 3 - 6 Months

Skills you'll gain: Prompt Engineering, AI Orchestration, AI Workflows, Model Context Protocol, LangChain, Retrieval-Augmented Generation, Agentic Workflows, Tool Calling, LangGraph, LLM Application, Agentic systems, Multimodal Prompts, Generative AI, Generative AI Agents, Vector Databases, Generative Model Architectures, OpenAI API, Embeddings, Responsible AI, Software Development
Advanced · Professional Certificate · 3 - 6 Months

Vanderbilt University
Skills you'll gain: Prompt Engineering, ChatGPT, Prompt Patterns, Generative AI, Verification And Validation, Ideation, LLM Application, Productivity, OpenAI, AI Personalization, Responsible AI, AI Enablement, Creativity, Large Language Modeling, Artificial Intelligence, Risk Management Framework, Expense Management, Productivity Software, Travel Arrangements, Test Case
Beginner · Specialization · 1 - 3 Months

Vanderbilt University
Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI Agents, Agentic Workflows, Prompt Patterns, Generative AI, AI Orchestration, Workflow Management, AI Enablement, Agentic systems, LLM Application, Productivity, OpenAI, AI Personalization, Business Process Automation, AI Product Strategy, Large Language Modeling, Automation, Artificial Intelligence, Expense Management
Beginner · Specialization · 1 - 3 Months

Multiple educators
Skills you'll gain: Retrieval-Augmented Generation, AI Product Strategy, Independent Thinking, Productivity Software, Generative AI, AI Personalization, Artificial Intelligence and Machine Learning (AI/ML), Responsible AI, Business Communication, Emotional Intelligence, Productivity, Operational Efficiency, Administration, Business Operations, Planning, Project Planning, Business Planning, Project Management, Business Administration, Business
Beginner · Specialization · 1 - 3 Months

Edureka
Skills you'll gain: Prompt Patterns, Generative AI Agents, AI Orchestration, AI Workflows, Business Process Automation, Make.com, Large Language Modeling, Automation, ChatGPT, Generative Model Architectures, Microsoft Power Automate/Flow, LLM Application, LangChain, Agentic Workflows, Responsible AI, Workflow Management, OpenAI, Process Optimization, Application Programming Interface (API), Decision Support Systems
Beginner · Specialization · 1 - 3 Months

University of Colorado Boulder
Skills you'll gain: Vision Transformer (ViT), Recurrent Neural Networks (RNNs), Multimodal Prompts, Artificial Intelligence and Machine Learning (AI/ML), Embeddings, Digital Signal Processing, Transfer Learning
Build toward a degree
Advanced · Course · 1 - 4 Weeks
Multimodal AI refers to artificial intelligence systems that can process and understand multiple forms of data, such as text, images, audio, and video. This capability is crucial because it allows for more comprehensive and nuanced interactions with technology, enabling applications that can interpret and respond to complex inputs in a human-like manner. For instance, a multimodal AI can analyze a video while simultaneously understanding the spoken dialogue and the text displayed on the screen, leading to more effective communication and decision-making.‎
Careers in multimodal AI are diverse and growing rapidly. Potential job roles include AI Engineer, Data Scientist, Machine Learning Engineer, and AI Product Manager. These positions often involve developing and implementing AI models that can handle various data types, creating applications that enhance user experiences, and optimizing AI systems for better performance. As industries increasingly adopt multimodal AI technologies, professionals with these skills are in high demand, making this a promising field for career growth.‎
To excel in multimodal AI(https://www.coursera.org/courses?query=multimodal ai), you should focus on acquiring a blend of technical and analytical skills. Key areas include programming languages such as Python and R, familiarity with machine learning frameworks like TensorFlow or PyTorch, and a solid understanding of data processing techniques. Additionally, knowledge of natural language processing (NLP), computer vision, and audio processing will be beneficial. Soft skills such as problem-solving, critical thinking, and effective communication are also essential, as they enable you to collaborate effectively in multidisciplinary teams.‎
There are several excellent online courses available for those interested in multimodal AI. For instance, the course Build Multimodal Generative AI Applications provides hands-on experience in creating applications that utilize multiple data types. Another option is Multimodal Generative AI: Vision, Speech, and Assistants, which covers the integration of various modalities in AI systems. These courses are designed to equip you with the necessary skills and knowledge to thrive in this evolving field.‎
Yes. You can start learning multimodal AI on Coursera for free in two ways:
If you want to keep learning, earn a certificate in multimodal AI, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎
To learn multimodal AI effectively, start by identifying your current skill level and the specific areas you want to focus on. Enroll in introductory courses that cover the basics of AI and machine learning, then gradually progress to more specialized courses in multimodal AI. Engage with practical projects to apply what you learn, and consider joining online communities or forums to connect with other learners and professionals. Consistent practice and collaboration will enhance your understanding and keep you motivated.‎
Typical topics covered in multimodal AI(https://www.coursera.org/courses?query=multimodal ai) courses include data representation, model training for different modalities, integration techniques for combining data types, and evaluation methods for multimodal systems. Courses may also explore real-world applications, such as chatbots that understand text and voice, image recognition systems that analyze visual content, and AI assistants that can process and respond to multiple inputs simultaneously. Understanding these topics will provide a solid foundation for working in the multimodal AI space.‎
For training and upskilling employees in multimodal AI, courses like IBM AI Engineering Professional Certificate and Generative AI for Software Development Skill Certificate are excellent choices. These programs are designed to provide practical skills and knowledge that can be directly applied in the workplace, helping teams to leverage multimodal AI technologies effectively and stay competitive in their respective fields.‎