Generative AI is changing how professionals work across industries. Content teams use it for research and content creation. Developers use it for coding assistance and application development. Analysts use it to interpret data and automate tasks. Business teams use it to improve decision-making and customer experiences.

But effective Gen AI adoption requires more than knowing how to use tools like ChatGPT. You need to understand how large language models work, write better prompts, evaluate AI outputs, build AI workflows, and apply these technologies to real business problems.

Great Learning offers Gen AI courses for different stages of your AI journey. Start with free courses to understand AI fundamentals and workplace applications. As you progress, certificate programs help you build skills in LLM applications, RAG, AI agents, automation, and enterprise AI implementation.

Gen AI Courses From Great Learning at a Glance

Course/Program	Type	Duration	Ideal For
Generative AI for Beginners	Free	3 hours	Professionals starting with Gen AI concepts
Generative AI Essentials and Applications	Free	2.25 hours	Learners building AI and ML foundations
Beginner’s Guide to Generative AI Tools	Free	8.25 hours	Professionals using AI tools at work
Python for Gen AI	Free	1.5 hours	Developers building AI applications
Working With Nano Banana Pro	Free	2.25 hours	Creators working with AI-generated images
Certificate in Generative AI, IIT Bombay	Paid	5 months	Professionals building LLM-based applications
Certificate Program in Applied Generative AI, Johns Hopkins University	Paid	16 weeks	Professionals applying Gen AI in business and technical workflows
No-Code Generative AI and Agentic AI, Johns Hopkins University	Paid	12 weeks	Professionals building AI workflows without coding
AI Agents and Generative AI for Business Applications, Texas McCombs	Paid	12 weeks	Professionals building business AI agents
AI-Native Professional	Paid	6 weeks	Professionals improving productivity with AI workflows

Gen AI Courses From Great Learning to Build Your Foundation (Free) 

If you are starting your AI journey, free Gen AI courses from Great Learning help you understand core concepts, explore popular AI tools, and build practical skills through beginner-friendly lessons. These courses cover topics such as large language models, prompt engineering, AI applications, Python for Gen AI, and AI-powered image creation, helping you build a strong foundation before moving into advanced AI programs. 

1. Generative AI for Beginners

This free Generative AI course is designed for learners who want to understand the basics of Generative AI. The course explains how AI evolved, how large language models work, how GPT-based systems generate content, and where businesses use Gen AI applications.

Delivery and Duration

• Level: Beginner
• Duration: 3 hours
• Format: Self-paced online course
• Credential: Certificate available

Course Overview and Highlights

• Fundamentals of Generative AI
• Evolution from traditional AI to Generative AI
• Large Language Models and GPT architecture
• How AI generates text responses
• Common business applications of Gen AI
• Limitations, hallucinations, and responsible AI practices

Course Outcome: How You Apply These Skills

After completing this course, you understand where Generative AI fits into professional workflows.

You can apply these skills to:

• If you're in marketing or content, you'll better understand when an AI-generated draft needs fact-checking or human review.
• If you're a manager, you'll be able to identify realistic business use cases instead of treating Generative AI as a solution for every problem.
• If you're moving into an AI-related role, the concepts covered here give you a useful base before moving into more technical training.

Why Choose This Course?

• Suitable if you are starting with AI without technical experience.
• Builds the foundation required for advanced Gen AI learning.
• Helps you understand AI capabilities before applying tools at work.

2. Generative AI with Machine Learning and LLMs

This free generative AI and machine learning course explains the relationship between artificial intelligence, machine learning, deep learning, and Generative AI. It introduces neural networks, transformers, large language models, GANs, and VAEs.

Delivery and Duration

• Level: Beginner
• Duration: 2.25 hours
• Format: Self-paced online course
• Credential: Certificate available

Course Overview and Highlights

• AI and machine learning fundamentals
• Supervised, unsupervised, and reinforcement learning
• Neural networks and deep learning
• CNNs and RNNs
• Transformer architecture
• Large Language Models
• GANs and VAEs
• Industry applications of Generative AI

Course Outcome: How You Apply These Skills

This course helps you understand the technology behind AI systems, not just how to use AI tools.

You can apply these skills to:

• If you're a data professional, the course helps connect traditional machine learning concepts with newer LLM applications.
• If you're working with technical stakeholders, you'll be better equipped to understand conversations around models, Transformers, and Generative AI.
• If you plan to move into AI engineering or data science, this can act as a concise foundation before longer programs.

Why Choose This Course?

• Helps you understand how modern AI systems work.
• Creates a technical foundation for advanced Gen AI courses.
• Useful for professionals involved in AI planning or adoption.

3. Generative AI Toolkit for Creators and Coders

This Free Beginner’s Guide to Generative AI Tools introduces widely used AI tools and shows how they support professional workflows. The course covers ChatGPT, GitHub Copilot, Claude, Gemini, prompt engineering, AI-assisted coding, and productivity applications.

Delivery and Duration

• Level: Beginner
• Duration: 8.25 hours
• Format: Self-paced online course
• Credential: Certificate available

Course Overview and Highlights

• ChatGPT fundamentals
• Prompt engineering techniques
• AI-assisted writing workflows
• GitHub Copilot for coding support
• Claude applications
• Gemini capabilities
• Workplace productivity use cases

Course Outcome: How You Apply These Skills

You learn how to integrate AI tools into everyday tasks.

You can apply these skills to:

• If you're a developer, you can use GitHub Copilot inside your coding environment for suggestions and repetitive code.
• If you're in operations or administration, ChatGPT or Claude can help with drafts, summaries, and recurring documentation.
• If you're in research or client services, you can compare responses from multiple tools before using important information.
• If you're building a technical product, the Claude API section gives you a starting point for creating AI-powered applications.

Why Choose This Course?

• Focuses on tools you can start using immediately.
• Helps professionals improve daily productivity.
• Covers multiple AI platforms instead of a single tool.

4. Python for Gen AI

This free Python for Generative AI course introduces Python programming concepts required to work with Generative AI applications. The course helps learners understand how Python connects with AI libraries, APIs, and application development.

Delivery and Duration

• Level: Beginner to intermediate
• Duration: 1.5 hours
• Format: Self-paced online course
• Credential: Certificate available

Course Overview and Highlights

• Python fundamentals
• Python programming concepts
• AI application development basics
• Working with AI-related workflows

Course Outcome: How You Apply These Skills

You build the programming confidence required for AI development.

You can apply these skills to:

• If you're a developer, you can start building small internal tools around language models.
• If you're a Python learner, you can use the projects to understand how APIs and AI services fit into web applications.
• If you're a technical product professional, the course gives you a better sense of what is involved in adding AI features to a product.

Why Choose This Course?

• Useful for learners moving from AI usage toward AI development.
• Builds programming skills needed for advanced Gen AI applications.
• Creates a foundation for working with AI libraries and APIs.

5. Working With Nano Banana Pro

This Free Nano Banana Course introduces you to Google’s Gemini 2.5 Flash Image model and its AI image generation capabilities. The course explains how Nano Banana and Nano Banana Pro work, their key features, practical applications, and how these tools fit into modern creative and professional workflows.

Delivery and Duration

• Level: Beginner
• Duration: 2.25 hours
• Format: Self-paced online course
• Credential: Certificate available

Course Overview and Highlights

• Introduction to Gemini 2.5 Flash Image and Nano Banana
• Evolution of AI image generation models
• Features and capabilities of Nano Banana and Nano Banana Pro
• AI image generation workflows
• Differences between Nano Banana and Nano Banana Pro
• Industry applications of AI-generated visuals
• Limitations and responsible use of AI image tools
• API and plugin-based integrations
• Practical use cases such as game concepts and app mockups

Course Outcome: How You Apply These Skills

This course helps you understand how AI image generation tools work and how they fit into creative, business, and product workflows.

You can apply these skills to:

• If you are a content creator or marketer, you can use AI-generated visuals for social media campaigns, marketing concepts, product promotions, and creative experiments.
• If you are a designer or UI/UX professional, you can create early design concepts, visual references, and mockups before developing final assets.
• If you work in product development, you can explore AI-powered visual features and understand how image generation models can support product ideas.
• If you are an educator or trainer, you can create illustrations, diagrams, and learning materials to explain concepts visually.
• If you are a developer, you can understand how AI image generation models connect with applications through APIs and plugins.

Why Choose This Course?

• Helps you understand the fundamentals of AI image generation.
• Introduces Google Gemini’s image generation capabilities and practical applications.
• Builds awareness of how AI visuals support creative and professional workflows.
• Creates a foundation for exploring advanced Generative AI and multimodal AI applications.

Gen AI Programs from Great Learning to Build Advanced AI Skills (Paid)

Free courses help you understand Gen AI concepts and experiment with AI tools. To build deeper expertise, you need programs that cover advanced topics such as large language models, retrieval-augmented generation (RAG), AI agents, automation, enterprise applications, and responsible AI practices.

The paid Gen AI programs from Great Learning, IIT Bombay, Johns Hopkins University, and Texas McCombs are designed for professionals who want to move from AI awareness to practical implementation. These programs include hands-on projects, industry use cases, and technical frameworks that help you apply Gen AI skills in real workplace scenarios.

6. Certificate in Generative AI, IIT Bombay

The Certificate in Generative AI by IIT Bombay is an advanced program designed to help professionals understand and build Generative AI applications. The program covers large language models, prompt engineering, retrieval-augmented generation, AI application development, and responsible AI practices. IIT Bombay faculty designed the curriculum, which focuses on practical applications of Generative AI across industries.

Delivery and Duration

• Duration: 5 months
• Format: Online with live IIT Bombay faculty sessions
• Learning approach: Live lectures, hands-on assignments, projects, and case studies
• Credential: Certificate of Completion from IIT Bombay

Course Overview and Highlights

• Generative AI fundamentals and applications
• Large Language Models and transformer architecture
• Prompt engineering techniques
• Retrieval Augmented Generation (RAG)
• Vector databases and embeddings
• Fine-tuning and model customization
• AI application development
• Responsible AI and evaluation methods

Course Outcome: How You Apply These Skills

This program helps you move from using AI tools to building AI-powered solutions.

You can apply these skills to:

• Software Development: Build AI applications that summarize documents, answer user queries, automate support tasks, or assist developers with coding workflows.
• Data Analytics: Create systems that extract insights from large volumes of documents, reports, and business data.
• Marketing: Build AI assistants that analyze customer feedback, generate content variations, and support campaign research.
• Product Management: Evaluate Gen AI features, define use cases, and work with engineering teams on AI product development.
• Business Operations: Develop knowledge assistants that help employees find information from internal documents.

Example:

If you manage a content team, you can use RAG concepts to build an internal AI assistant that searches your content guidelines, previous articles, and brand documents to answer questions about writing standards.

Why Choose This Course?

• Provides structured learning in Generative AI from fundamentals to applications.
• Covers practical concepts such as LLMs, RAG, and AI application development.
• Helps professionals understand how Generative AI systems are built and evaluated.
• Includes IIT Bombay faculty-led learning and applied projects.

7. Certificate Program in Applied Generative AI, Johns Hopkins University

The Applied Generative AI and Agentic AI from Johns Hopkins University focuses on applying Generative AI techniques to real-world business and technical problems. The program covers large language models, prompt engineering, RAG, AI agents, AI application development, and responsible AI. The curriculum helps professionals design, implement, and evaluate Generative AI solutions.

Delivery and Duration

• Duration: 16 weeks
• Format: Online with live sessions, mentorship, and projects
• Learning approach: Faculty sessions, hands-on assignments, and industry case studies
• Credential: Certificate from Johns Hopkins University

Course Overview and Highlights

• Generative AI and LLM foundations
• Prompt engineering
• Retrieval-Augmented Generation
• AI application architecture
• AI agents and automation workflows
• AI evaluation techniques
• Responsible AI practices
• Enterprise Gen AI implementation

Course Outcome: How You Apply These Skills

The program helps you design practical Gen AI solutions for business and technical workflows.

You can apply these skills to:

• Developers: Build LLM-powered applications, chatbots, document assistants, and automation systems.
• Data Professionals: Create AI workflows that analyze unstructured information and generate insights.
• Business Teams: Identify high-value AI use cases and improve operational processes.
• Consultants: Recommend AI solutions based on business requirements.
• Managers: Evaluate AI projects and communicate technical requirements with engineering teams.

Example:

If you work in customer support operations, you can design an AI assistant that retrieves information from product documentation, suggests responses, and helps support teams resolve queries faster.

Why Choose This Course?

• Focuses on practical Generative AI implementation.
• Covers the complete workflow from AI concepts to business applications.
• Helps professionals build skills for enterprise AI adoption.
• Includes hands-on learning with real-world applications.

8. No-Code Generative AI and Agentic AI Program, Johns Hopkins University

The No-Code Generative AI and Agentic AI Program from Johns Hopkins University is designed for professionals who want to build AI solutions without programming. The program focuses on Generative AI, AI agents, automation workflows, prompt engineering, and responsible AI adoption. It helps business professionals apply AI tools to solve workflow challenges without requiring software development experience.

Delivery and Duration

• Duration: 12 weeks
• Format: Online with instructor-led sessions and hands-on activities
• Learning approach: No-code tools, projects, and practical exercises
• Credential: Certificate from Johns Hopkins University

Course Overview and Highlights

• Generative AI fundamentals
• Prompt engineering
• AI assistants and automation
• AI agent concepts
• No-code AI workflows
• Business process automation
• Responsible AI practices

Course Outcome: How You Apply These Skills

This program helps you apply AI directly within your professional workflows.

You can apply these skills to:

• Marketing Professionals: Create AI workflows for content planning, audience research, and campaign analysis.
• HR Professionals: Build AI-assisted workflows for employee queries, onboarding resources, and documentation.
• Operations Teams: Automate repetitive tasks such as reporting, information retrieval, and workflow approvals.
• Managers: Identify AI opportunities without needing programming expertise.
• Consultants: Build AI prototypes to demonstrate business solutions.

Example:

If you manage business operations, you can create a no-code AI workflow that collects information from multiple sources, summarizes updates, and prepares stakeholder reports.

Why Choose This Course?

• Designed for professionals without programming backgrounds.
• Focuses on practical AI adoption rather than coding-heavy development.
• Helps teams identify and implement AI automation opportunities.
• Useful for professionals leading AI transformation initiatives.

9. AI Agents and Generative AI for Business Applications, Texas McCombs

The Post Graduate Program in AI Agents and Generative AI from Texas McCombs focuses on building AI systems that can perform multi-step tasks using Generative AI and agent-based workflows. The program covers LLMs, RAG, AI agents, memory, tools, reasoning, automation, and business applications.

Delivery and Duration

• Duration: 13 weeks
• Format: Online with recorded content and live sessions
• Learning approach: Projects, case studies, and practical assignments
• Credential: Certificate from Texas McCombs

Course Overview and Highlights

• Generative AI and LLM fundamentals
• Prompt engineering
• Retrieval-Augmented Generation
• AI agent architecture
• Memory and tool integration
• Multi-agent systems
• AI workflow automation
• AI evaluation and deployment

Course Outcome: How You Apply These Skills

The program helps you build AI systems that complete complex business tasks.

You can apply these skills to:

• Software Teams: Build AI agents that automate coding assistance, documentation, testing, and support workflows.
• Analytics Teams: Create agents that analyze reports, retrieve business information, and generate insights.
• Sales Teams: Develop AI assistants that summarize customer interactions and support sales research.
• Operations Teams: Build workflow agents that automate repetitive processes and decision support.
• Leadership Teams: Evaluate how AI agents improve business processes.

Example:

If you manage a knowledge-heavy team, you can build an AI agent that searches internal documents, answers employee questions, and routes complex requests to the right teams.

Why Choose This Course?

• Focuses on business applications of AI agents.
• Covers advanced Gen AI concepts such as RAG, memory, tools, and orchestration.
• Helps professionals understand how autonomous AI systems work.
• Includes practical projects based on business scenarios.

10. AI-Native Professional

The AI-Native Professional program from Great Learning helps professionals integrate Generative AI into their daily work. The program focuses on AI productivity, automation workflows, prompt engineering, AI tools, and building AI-assisted work processes. It is designed for professionals who want to use AI more effectively in their current roles.

Delivery and Duration

• Duration: 6 weeks
• Format: Online
• Learning approach: Practical exercises and workplace-focused applications
• Credential: Program certificate

Course Overview and Highlights

• Generative AI fundamentals
• Prompt engineering
• AI productivity workflows
• AI-assisted research and content creation
• Automation techniques
• AI tools for professional work
• Building AI-powered workflows

Course Outcome: How You Apply These Skills

You learn how to integrate AI into everyday professional tasks.

You can apply these skills to:

• Content Teams: Speed up research, content planning, editing, and workflow documentation.
• Developers: Improve coding productivity, debugging, and documentation.
• Analysts: Automate summaries, reporting, and insight generation.
• Managers: Improve decision-making through AI-assisted research and analysis.
• Entrepreneurs: Use AI tools for market research, planning, and business operations.

Example:

If you manage projects, you can use AI workflows to summarize meetings, create action items, organize project updates, and prepare stakeholder reports.

Why Choose This Course?

• Focuses on practical AI adoption across professional roles.
• Helps you build repeatable AI workflows.
• Useful for professionals who want immediate workplace applications.
• Helps bridge the gap between AI tools and everyday productivity.

Conclusion

Gen AI skills are becoming valuable across technical, business, and creative roles. Free courses help you understand AI concepts and experiment with tools. Advanced certificate programs help you build deeper skills in LLMs, RAG, AI agents, automation, and enterprise AI implementation.

The right Gen AI course depends on your current role and career goals. If you are starting with AI, foundation courses help you build confidence. If you want to create AI applications, focus on programs covering LLMs, RAG, agents, and deployment. If you want to improve workplace productivity, choose programs focused on AI workflows and automation.