What will you learn in AI Agents and Agentic AI in Python: Powered by Generative AI Specialization Course
Master foundational and advanced concepts in AI agent design using Python
Build AI agents from scratch using planning, memory, and reasoning modules
Use popular tools like LangChain, OpenAI APIs, and vector databases to enhance agents
Apply prompt engineering techniques to guide agent interactions and outputs
Design multi-agent systems that collaborate to complete complex tasks
Program Overview
Course 1: Foundations of AI Agents with Python
⏳ 1 week
Topics: Agent architecture, memory, environment interaction, decision-making
Hands-on: Create a simple AI agent using Python to perform goal-directed behavior
Course 2: Building AI Agents with LangChain and OpenAI
⏳ 1 week
Topics: LangChain integration, LLMs, vector stores, and tool calling
Hands-on: Build a LangChain-powered agent that retrieves and processes real-time data
Course 3: Designing Multi-Agent Systems
⏳ 1 week
Topics: Agent communication, delegation, autonomous task handling
Hands-on: Implement a Python-based multi-agent framework with coordinated workflows
Course 4: Evaluation, Safety & Deployment
⏳ 1 week
Topics: Testing agents, reliability checks, hallucination mitigation, ethical deployment
Hands-on: Deploy an agent to a web app or API and run evaluations using structured metrics
Get certificate
Job Outlook
Python developers with AI agent skills are in high demand for roles in automation, AI tooling, and applied AI
Emerging roles include AI Systems Developer, Agent Architect, and AI Automation Engineer
AI startups and enterprises alike are adopting agent frameworks for customer service, research, and productivity tools
Freelancers and consultants can offer custom agent solutions across sectors
Specification: AI Agents and Agentic AI in Python: Powered by Generative AI Specialization
|
FAQs
- Designed for beginners, no advanced AI experience required.
- Basic Python knowledge is recommended to follow coding exercises.
- Covers AI agent principles, LangChain, and LLM usage.
- Provides step-by-step guided projects to build confidence.
- Includes practical tools integration for real-world applications.
- Learn to design and deploy functional AI agents.
- Covers chatbots, coding assistants, and AI copilots.
- Integrates APIs and vector databases for real data usage.
- Emphasizes multi-agent collaboration and workflow orchestration.
- Teaches prompt engineering strategies for practical outcomes.
- Course exercises often use OpenAI APIs for agent creation.
- Access to vector databases or other external tools may incur costs.
- Core learning does not require paid tools, only optional for advanced projects.
- Alternatives or trial accounts may be used for hands-on practice.
- Focus remains on understanding AI agent architecture and workflows.
- Focused on high-demand AI agent development skills.
- Hands-on projects demonstrate applied knowledge for portfolios.
- Covers multi-agent systems, prompt engineering, and deployment.
- Prepares for roles in startups and enterprise AI teams.
- Teaches evaluation, safety, and reliability for professional projects.
- Teaches development of independent AI agents.
- Covers integration with external tools and APIs for custom solutions.
- Focus on building portfolio-ready projects for freelance opportunities.
- Explains safe and reliable agent implementation practices.
- Encourages experimentation with real-world AI agent applications.
