Essentially, you don’t need programming skills to create generative AI applications today. The emergence of no-code technologies allows any user to use AI models along with the data of the company as well as automatated systems with the help of easy-to-use interfaces.
If you have knowledge of Python, you can manage the logic, memory, APIs, and agency of your agent. Python is ideal for building complex agent architectures, RAG, advanced evaluation systems, and processes that need complicated integrations.
Below are five programs that use both approaches. The programs have different levels of programming knowledge required, technical complexity, examples of completed projects, and created AI systems.
Overview: 5 Generative AI and AI Agent Programs
| # | Program | Provider | Duration | Best suited for |
| 1 | Certificate in Agentic AI | Johns Hopkins University | 18 weeks18 weeks | Python, RAG, MCP, multi-agent systems
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| 2 | No-Code Generative AI and Agentic AI | Johns Hopkins University | 12 weeks | n8n, no-code agents, workflow automation |
| 3 | Certificate in Agentic AI Solutions for Managers | Georgetown University | 6 weeks | Business agents, workflow design, AI automation |
| 4 | Designing and Building AI Solutions | Cornell | 4 months | No-code AI prototyping, generative AI applications |
| 5 | Applied Agentic AI | University of San Francisco | 5 days | No-code agent development, tool calling, MCP, RAG |
1. Certificate Program in Agentic AI- Johns Hopkins University
The Certificate Program in Agentic AI from Johns Hopkins University is a comprehensive program that offers knowledge and skills in agent development using Python, RAG, integration of tools, and use of multi-agent systems. The course offers professionals a chance to learn agentic AI certification by offering practical experience in autonomous AI applications and dependable workflow.
Mode of delivery: Online course with 18 weeks overall, consisting of video learning material, teacher sessions, real-time consultation by industry mentors, and project execution.
Certificate: Students earning the certificate will also collect 13 CEUs.
Highlights: Learning Python programming, LLMs, RAG, vector databases, ReAct, MCP, LangChain, LangGraph, multi-agent coordination, evaluation, observability, security, and deployment.
Outcomes: Development of autonomous agents that are able to search for information, connect to external systems, complete selected tasks, and evaluate the performance of individuals.
Why should you choose this course:
Evaluation, security and observability elements help individuals learn how to build reliable workflows with AI.
2. No-Code Generative AI and Agentic AI Program- Johns Hopkins University
The No-Code Generative AI and Agentic AI program at Johns Hopkins University provides the knowledge needed to construct AI-based workflows without programming. It is aimed at participants looking to implement business solutions automation in a no-code setting.
The no-code generative AI program covers agent development, RAG, and the introduction of various automation tools through workflows.
Mode and Duration: 12-week online course with self-paced modules, interactive sessions, and mentorship programs. Students would be expected to spend 8-10 hours per week completing the work.
Certification and CEUs: Completion Certificate from Johns Hopkins University along with 9 CEUs.
Key content: includes topics such as n8n, ChatGPT, Claude, Gemini, NotebookLM, automated workflow systems, integration of AI Technologies, etc.
Results: Upon completion of the program, students would learn about automated workflow systems, AI tools integration, and agent development.
Why should you choose the course:
There is no need to have experience in programming before participating in the course. Projects and case studies illustrate how visual workflows can connect several AI tools and services.
3. Certificate in Agentic AI Solutions for Managers- Georgetown University
The Georgetown University Certificate in Agentic AI Solutions for Managers assists learners in understanding the development of AI agents for business applications. It permits learners to determine automation possibilities, create work processes based on AI agents, and implement autonomous AI systems in businesses.
This program is aimed at managers, specialists of different industries, and innovators who wish to gain insight into agent formation without going too deep into programming.
Format: Online 6-week course with weekly virtual lessons and assignments. The program consists of 32 hours of contact classes.
Certificate: Certificate from Georgetown University and 3.2 Continuing Education Units (CEUs).
Course highlights: Fundamentals of Agentic AI, large language models, vector databases, autonomous decision-making, workflow design, vendor-independent agent solutions, business automation.
Outcomes: Learners determine appropriate cases for business application of AI agents, create solutions and prototypes.
Why should you choose this course?
- Agent development is connected to business realities so that it can be applied by people who improve processes in organizations.
- A vendor-independent approach allows learning about agent architecture without depending on one solution.
4. Designing and Building AI Solutions- Cornell University
The program at Cornell University called Designing and Building AI Solutions is designed for people with no previous programming knowledge. The program includes traditional AI principles in relation to generative AI, business applications, and agent-based methods. Participants learn how to recognize the best AI ideas and build prototypes.
Course delivery and length: Delivery is online and takes around 4 months with practical tasks, sessions, and discussions with educators.
Credentials: Certificate of completion awarded by Cornell University and eCornell.
Course specifics: AI product development, data prepping methods, neural networks, agent-based approaches, responsible AI applications, and challenges with AI prototypes.
Results: Participants comprehend the AI application requirements and data preprocessing methods, and create AI solutions with these initiatives.
Why should you choose this course:
- People without programming knowledge can understand how to create AI solutions and agent-based applications.
- The course is focused on business requirements and data quality and can lead to successful developments in AI.
5. Applied Agentic AI- University of San Francisco
The Applied Agentic AI course from the University of San Francisco familiarizes students with how agents can be created without having to know programming. It uses Claude Desktop to show how agents plan actions and communicate with external tools.
Students will have the opportunity to learn theory together with instructor-led practical tasks, through which they will create an agent to solve the issue.
Format: Five days, either in-person or online learning, with 20 hours of learning activities.
Credentials: Certificate from the University of San Francisco and 2 CEUs.
Highlights: Fundamentals of LLMs, prompt engineering, agent planning, tool interaction, Claude Desktop basics, API use, MCP, RAG, assessment, human-in-the-loop strategies, and responsible AI.
Outcomes: Learners develop an AI agent, provide it with the necessary tools, analyze its working capabilities, and demonstrate the completed project during the final show.
Why should you choose this course?
- It provides immediate practice in agent creation without the need to learn to program in Python or other programming languages.
- The format gives the opportunity to create, test, and demonstrate the work of an agent in just five days.
To pick from various gen AI courses, determine if you need to automate work quickly or if you have full control of agent development. Programs with no coding are best for those who to create research assistants, transport documents, and automate business processes. Programs focusing on Python allow for being flexible with integrating tools, managing memory, reasoning and working with multi-agent systems.
Neither ovariantcan provide quality automation. Using AI agents means you need to feed them accurate information, have the necessary permissions to use involved tools, provide evaluations, and keep a human leader monitoring the process.
