AI AGENTS MASTERY 7-in-1
Build Real-World Production AI Agents
Master One System Stack.
Build Any AI Agent.
Deploy in Any Industry.
20 End-to-End Python Projects
7 Hands-On Modules
+ Advanced Production Module
⭐⭐⭐⭐⭐(5/5)
Rated by 3,200+ in 130+ countries
Claude Code · LangGraph · MCP ·
Google ADK · PydanticAI · CrewAI · OpenAI
AI Agents Mastery 7-in-1 is one of the Most Complete, Project-based Training Programs for Building Real-world Production AI Agents. With 7 Hands-on modules, one Advanced Production Engineering Stack, and 20 end-to-end projects across 16 industries, you learn to Build, Adapt, and Deploy AI Agents across any Industry.
Created by Dr. Maryam Miradi, a real-world AI expert with a PhD in AI and 20+ years of experience building AI systems. Trusted by AI professionals across 130+ countries.
100% Hands-on · Self-Paced · Full Code Included
3,200+ already enrolled.
Lifetime Access · Free Future Modules
🎧 English Captions Included
︾
What AI Professionals Say About AI Agents Mastery 7-in-1
✱ Trusted by AI Engineers, Architects, Data Scientists, Researchers, Leaders & Students in 130+ countries.
Exceptional Quality · Well-Chosen Projects · Outstanding Mentor
Tran Chanh Truc
AI Data Scientist | Vietnam
⭐⭐⭐⭐⭐
The AI Agents Mastery 7-in-1 course by Dr. Maryam Miradi clearly reflects an Exceptional Level of Dedication and care in both its Design and Delivery.
Practical · Enterprise-Focused · Applicable
Narendra Pydi
Enterprise Gen AI Architect | USA
⭐⭐⭐⭐⭐
I really enjoyed the AI Agents Mastery program 7-in-1. As an AI & Enterprise Architect, I found it practical and especially valuable for real-world enterprise use cases.
Extraordinary Expertise · Holistic · Comprehensive
Joachim M. Vis
AI Consultant | Germany
⭐⭐⭐⭐⭐
AI Agents Mastery 7-in-1 is Mind-blowing!! I got to know Maryam's extraordinary expertise in the field of AI Agent technology.
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Building AI Agents Gets Easier Once You See the System.
LangGraph, CrewAI, PydanticAI, Google ADK and other AI Agent frameworks may look different, but underneath they solve many of the same core problems:
Models · Tools · State · Memory · Orchestration · Workflows
Once you understand these patterns, moving between frameworks becomes much easier.
Compound Learning Makes You Unbeatable.
Apply the same System Stack across projects and industries. Each build strengthens the last.
You get faster at recognizing patterns, adapting architectures, and deploying AI Agents across new industries.
Tools come and go.
Systems stay.
Projects Compound.
︾
That is why AI Agents Mastery is built on 3 Pillars:
7 Frameworks & Tools + One Production Engineering Stack + 20 Projects
THE FRAMEWORKS & TOOLS
✓ Module ①: LangGraph
✓ Module ②: CrewAI
✓ Module ③: OpenAI Swarm
✓ Module ④: PydanticAI
✓ Module ⑤: Model Context Protocol (MCP)
✓ Module ⑥: Google ADK
✓ Module ⑦: Claude Code
THE STACK
⊕ Advanced Production AI Agent Engineering
12-Layer Production Stack · Loop Engineering · Graph Engineering · Harness Engineering · Forward Deployed Engineering · Advanced RAG · Multimodal · Evals · Observability · Continual Learning
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THE PROJECTS
⊕ 20 End-to-End AI Agent Systems across 16 industries:
Healthcare & Medical Emergency, Legal, Cybersecurity, Supply Chain, Renewable Energy, Road Infrastructure, Aviation, Incident Operations, Finance, Insurance, Smart Cities, Environmental Monitoring, Tax, Accounting, LinkedIn Marketing, Retail, and more.
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⊕ All Future Modules and Updates are Free.
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What You’ll Be Able to Build:
Complete, End-to-End Production AI Agent Systems.
Foundations to Production Engineering.
12-Layer Production AI Agent Stack
Master how Production AI Agents
handle context, verify results,
recover from failure & improve
Knowledge Engineering. Model Engineering. Context Engineering. Semantic Engineering.
Agent Engineering. Loop Engineering. Evaluation Engineering. Harness Engineering.
Infrastructure Engineering. Continual Learning.
20 End-to-End Projects
Industries: Healthcare, Medical Emergency, Legal, Cybersecurity, Supply Chain, Renewable Energy, Smart Cities, Finance, Insurance, Aviation, Road Infrastructure,
Incident Operations, Tax, Accounting, LinkedIn Marketing, Retail
Production-grade systems. Real data. Real constraints.
Top AI Agent Frameworks
LangGraph, CrewAI, OpenAI Swarm, PydanticAI & Google ADK
Flow engineering. Execution graphs. Role isolation. Agent coordination. Structured handoffs. AI Agents Pattern Design
Claude Code as Building Accelerator
Build AI agents faster with Claude Code, Skills, Plugins, MCP, and Sub-agents.
CLAUDE.md. Skills. Meta Skills. Plugins. Hooks. MCP. Sub-agents. Worktrees. Evals.
Production AI Agents
Roadmap
Build Production AI Agents from Scratch in 2026 (10-Steps)
Reasoning. Hallucination defense. Evals. Fine-tuning. Deployment. Monitoring.
Graph
Engineering
Build Production AI Agents
that reason over
real world graphs
OpenStreetMap. OSMnx. NetworkX.
LangGraph. Pathfinding. Asset decisions.
Forward Deployed
Engineering
Build Meta Agents that turn
company context into
Production AI Agents
FDE Meta Agents. MCP + Skills. AgentSpec. Human Gates. Evals. Observability.
Loop
Engineering |
Harness
Engineering
Build the engineering layers
behind Production AI Agents
Execution. Loops. Orchestration. GraphRAG. Evals. Permissions. Observability. Human Gates.
Continual Learning
Build Self-Improving Production AI Agents that learn from outcomes and improve safely over time
Episodic Memory. Evals. Learning Signals. Expertise Memory. Context Gating. Isolation Forest.
Multimodal AI Agents
Voice, Vision, Text, Video, Tabular data
Object detection. Image classification. Face recognition. OCR. Text-to-speech. Tabular context.
AI Agent Design Patterns
9 Patterns: Tool-Use, ReAct, Structured Output, Memory-Augmented, Reflection, Plan & Execute, Router, Parallel Research, Orchestrator-Worker
Unique combination of LlmAgent, SequentialAgent, ParallelAgent, LoopAgent & CustomAgent
Advanced AI Agent Design Patterns
6 patterns: Self-Consistency CoT, ReWOO, Reflexion, AdaPlanner, HITL, LLMCompiler
Consensus voting. Parallel planning. Reflection loops. Adaptive execution. Human approval. Compiled pipelines.
Foundations of AI Agent Development
What AI agents are, how they work, and the building blocks behind them
Memory. Reasoning. Tools. Planning. Orchestration.
Retrieval-Augmented Generation (RAG)
FAISS. ChromaDB. Vector search pipelines
Embeddings. Semantic retrieval. Grounded, context-aware responses.
Context Engineering
7 methods for building stable, production-ready agents
Context offloading. Compaction. Layered action spaces. Dynamic tool selection.
Model Context Protocol (MCP)
Reusable, configurable AI agents with server–client separation
FastMCP. Stdio vs SSE. Context files. Modular toolchains.
Full-Stack AI Agent Applications
Gradio apps. Interactive dashboards. Geospatial views
Gradio, Folium, interactive dashboards
Enterprise-Grade AI Agents
Advanced Agent Projects in Multiple Industries
Combined frameworks. High-complexity use cases. Latest tools and LLMs.
︾
How I Think and Teach AI Agent Systems
Before you decide, you can watch how I approach real AI agent design.
This is a full lesson showing how I reason about architecture, frameworks, and production trade-offs.
︾
How You’ll Build and Master AI Agents
PHASE 1 - BUILD REAL-WORLD AI AGENTS
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01. Learn the Foundations of AI Agent Development
LLMs. Vision Models. Text to Speech. Custom Tools. Flow Engineering.
Understand how AI agents actually work and the building blocks behind them.
02. Build Multi-Agent Systems with 5 Top Frameworks
LangGraph · LangChain · Google ADK · Pydantic AI · CrewAI · OpenAI Swarm
Learn how to design and coordinate single-agent and multi-agent systems across leading frameworks.
03. Build Domain-Specific & Custom AI Agents
Healthcare. Legal. Cybersecurity. Supply chain. Finance. Insurance. Aviation. Smart Cities. Geoscience. Software. Incident Operations. Tax. Accounting. LinkedIn Marketing.
Learn how to translate business problems into domain-specific agent architectures. You’ll master how to adapt agents to different domains and make them truly usable, intelligent, and task-aware.
PHASE 2 - BUILD EXPLAINABLE REPRODUCIBLE AI AGENTS
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04. Build Retrieval-Augmented Generation (RAG)
FAISS Vector Database. ChromaDB Vector Database.
Learn how to build a complete RAG pipeline from embedding documents, to building vector databases, to running semantic search enabling accurate, grounded, and context-aware responses from LLMs.
05. Work with Voice, Vision & Multi-Modal AI
Object Detection. Text to Speech. Image Classification. Face Recognition. OCR. Tabular Data.
Build agents that speak (via ElevenLabs), see (with vision models), and reason across text, image, video, and tabular data.
06. Use the Right Models and APIs for the Job
Hugging Face. Groq. Gradio. DeepSeek R1. GPTs. LLaMA. Together AI.
Work with GPT, Gemini, Claude, Deepseek, LLaMA, and Groq via APIs for advanced reasoning and generation. Build interfaces with Gradio and visualize structured data with Folium. Use Hugging Face to access almost 3M+ pre-trained models for high-performance vision APIs powering use cases like pneumonia detection, license plate recognition, and vehicle detection.
07. Model Context Protocol (MCP) – Build Reusable, Configurable AI Agents
Reusable Agents · Server/Client Architecture · FastMCP · Stdio vs SSE
Master MCP-based agent architecture, from context and toolchains to reusable servers and clients. Build 3 complete MCP systems with LangChain and the OpenAI SDK.
PHASE 3 - BUILD PRODUCTION AI AGENTS
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08. Master 15 AI Agent Design Patterns with Google ADK
ReAct · Router · Reflection · Plan & Execute · Orchestrator-Worker · HITL · More
Learn the reusable architectural patterns behind reliable agent systems.
09. Production AI Agent Engineering | Advanced Module
12-Layer Production AI Agent Stack
Business Understanding · Data Understanding · Knowledge Engineering · Model Engineering · Context Engineering · Semantic Engineering · Agent Engineering · Loop Engineering · Evaluation Engineering · Harness Engineering · Infrastructure Engineering · Continual Learning
Loop Engineering & Harness Engineering
Retries · Feedback Loops · Human Gates · Evals · Observability
Graph Engineering | Road Infrastructure - End to End
GraphRAG · Network Reasoning · Routing · Infrastructure Decisions
Continual Learning | Wind Turbine Maintenance - End to End
Episodic Memory · Evaluation · Learning Signals · Continual Learning · Controlled Continual Learning · Context Gating · Isolation Forest
Forward Deployed Engineering | Incident Operations - End to End
AgentSpecs · Meta Agents · Domain MCP · Safety Validators · Audit Trails
Context Engineering
Compaction · Context Isolation · Dynamic Tool Selection · Layered Action Spaces
Core Building Blocks of Production AI Agents
Reasoning · Memory · Orchestration · Evaluation · Monitoring · Reliability
Enterprise Projects End to End:
- Medical Emergency Department System
- Wind Turbine Maintenance System
- Cyber Defense System
- $5B Supply Chain System
- Insurance Claims System
- Road Infrastructure System
- Incident Operations System
PHASE 4 - BUILD FASTER WITH CLAUDE CODE
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10. Claude Code as Building Accelerator
Skills · Meta Skills · Plugins · Hooks · MCP · Worktrees · Sub-agents
Use Claude Code to accelerate planning, architecture, coding, testing, and evaluation of production AI agents.
Claude Code Plugin Showdown: Building a Medical AI Agent
Benchmark 5 top Claude Code plugins by having each design a production medical AI agent, then compare them across 13 production criteria with LLM-as-judge scoring, rankings, and token usage.
Insurance Claims AI Agent Team - End to End
Build a production-grade 5-agent insurance claims system with vision-based damage checks, policy validation, risk scoring, payout recommendations, human review, 72 production evals, a Gradio dashboard, full audit trail, and reusable Claude Skill + plugin packaging.
+BONUS
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AI Agent Zero to Hero – Deep Dive
Foundations. Agent Logic. Framework Comparison. Deployment Thinking. Strategy.
Get a structured overview of AI Agents and a deep dive into how real-world systems are built, orchestrated, and deployed.
This 30-minute, 5-part module gives you the essential building blocks and strategic clarity to connect all the dots from goals, tools, and memory... to reflection, collaboration, and long-term agent reasoning.
By the end, you'll have built 20 end-to-end projects across 16 industries, from agent design to production-grade, enterprise-ready systems, accelerated by Claude Code.
︾
Is This Training for You?
✔ Who This Is For
Based on 3,200+ enrolled professionals.
- AI Engineers, AI Scientists & Data Scientists ready to build Production AI Agent systems beyond prompts and prototypes
- Software Engineers & Developers who want to build complete, real-world agentic applications
- Product Owners & Product Leads who need to understand what AI agents can realistically deliver and how to turn them into products
- CTOs, CEOs & Founders building AI-powered products, teams, or businesses
- Technical Leads & Engineering Leads responsible for designing, evaluating, or leading AI initiatives
- Enterprise Architects, Solution Architects, Cloud Architects, AI Architects & GenAI Architects designing scalable AI Agent architectures and production systems
- STEM Graduates, Bachelor’s & MSc Students, Professors, PhDs, Postdocs & Researchers who want practical, industry-relevant AI Agent skills
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✔ Prior Knowledge
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Python: Basic to intermediate coding required. No need to be an expert.
-
AI/ML Concepts: Familiarity recommended no need for a PhD.
―
✔ Hardware Requirements
- Any standard computer is sufficient. No high-end hardware or dedicated GPU is required. You can work with Google Colab, Cursor, VS Code, Antigravity, and other standard development environments.
If that sounds like you, you’re exactly who this training was built for.
︾
Projects You’ll Build:
20 End-to-End AI Agent Systems across 16 industries
Full Python Code Included
Build in Google Colab, Cursor, Antigravity & VS Code
1. Hospital AI System ≫ LangGraph Module
Build Physician, Radiologist, and Reception Agents, integrated into a Gradio dashboard with vision models and patient database retrieval.
2. Smart Airport Crew ≫ OpenAI Module
Automate Check-In, Passport Control, and Security Check using multi-agent coordination (Swarm) and face detection.
3. Geo Intelligence Agents ≫ OpenAI Module
Use Folium to visualize maps, routes, and locations dynamically, ideal for Smart Cities or urban planning.
4. Financial Advisor Agents ≫ CrewAI Module
Design an intelligent agent that provides investment advice, personal finance breakdowns, and budget alerts with structured data.
5. Travel Planner Agents ≫ CrewAI Module
Build a multi-agent system that selects destinations, books hotels, suggests itineraries, and responds via voice (ElevenLabs), all within a Gradio interface.
6. Traffic Flow Analyzer ≫ PydanticAI Module
Forecast congestion using real-time data and time series agents with interactive plots and dashboards in Gradio.
7. License Plate Detection System ≫ PydanticAI Module
Detect and tag vehicle plates using object detection + Hugging Face models, and store results in a searchable vector DB.
8. Legal Document AI System ≫ Google ADK Module
Build a 5-step production-ready legal AI agent that validates business constraints, profiles data uncertainty, benchmarks document parsers (Docling vs. LlamaIndex vs. PyPDF), routes and audits complex legal documents via Google ADK multi-agent flow, and standardizes the entire pipeline as a reusable MCP server, with fail-safes, human-in-the-loop escalation, and OCR quality gates built in.
9. Tax & Accounting AI Agents ≫ Google ADK Module
Master every essential agent architecture by building 9 progressive patterns, from single agents with Tool-Use, ReAct, Structured Output, and Memory, to compound multi-agent systems using LoopAgent, SequentialAgent, ParallelAgent, and a full Orchestrator-Worker pipeline, all applied to a real Accounting & Tax domain using Google ADK, Docling, Pydantic, and Gemini.
10. LinkedIn Marketing AI Agents ≫ Google ADK Module
Build an end-to-end LinkedIn lead generation system with 29 agents across 6 agentic systems, applying 6 advanced design patterns including Self-Consistency CoT, ReWOO, Reflexion, AdaPlanner, HITL, and LLMCompiler, covering ICP analysis, market research, profile optimization, 30-day content planning, human approval gates, and a full content pipeline, all wrapped in a Gradio app using Google ADK and Gemini.
11. Math & Weather Agents ≫ MCP Module
Design a minimal MCP client-server agent using Langchain that handles dynamic math questions and weather updates via multiple servers.
12. News Summarizer Agent ≫ MCP Module
Use OpenAI SDK with MCP to create a news summarization agent that returns clean, markdown-style summaries, with stdio.
13. Air Quality Analyzer ≫ MCP Module
Build an MCP-based Langchain agent that analyzes pollution levels using external datasets as resource, with real-time insights via a modular client-server setup.
14. Insurance Claims Agent Team ≫ Claude Code Module
Build a production-grade multi-agent insurance claims system using Claude Code that validates claim completeness, cross-checks vision-analyzed damage against customer stories and repair estimates, verifies policy coverage, scores risk anomalies, and calculates final payout recommendations with human review routing. Intake, Damage Evidence, Policy, Risk, and Payout agents coordinate through LangGraph, backed by 72 production evals, a Gradio dashboard, and a full audit trail, then packaged as a reusable Claude Skill and Claude Code plugin with hooks.
15. $5B Flower Supply Chain ≫ Advanced Module
Build a production-grade end-to-end multi-agent AI system processing 43M flowers per day, integrating vision agents, synthetic data generation, species identification, RAG with ChromaDB, dynamic pricing, and a Gradio dashboard using Gemini Pro Vision, DeepSeek, PydanticAI, and LangGraph.
16. Cybersecurity ≫ Advanced Module
Build a production-grade multi-agent cyber defense system that ingests raw logs, flags anomalies instantly, classifies threat severity, runs live intelligence lookups, and auto-generates structured security reports. Ingest, Detect, Classify, and Report agents coordinate through LangGraph StateGraph workflows with ReAct reasoning, shared memory, and Python tool-calling.
17. Incident Operations System ≫ Advanced Module
Build an end-to-end Forward Deployed Engineering system with 3 FDE Meta Agents for Discovery, Architecture, and Evaluation that use reusable Skills + a domain MCP server to generate a validated AgentSpec. Dynamically build 5 Production AI Agents for a Theme Park Incident Operations System from that specification with LangGraph, deterministic safety validators, human approval for high-risk actions, production evals, and SQLite observability with a complete audit trail.
18. Road Infrastructure Agent System ≫ Advanced Module
Build a graph-powered 3-Agent System for Road Health, Maintenance Planning, and Closure Impact. Transform real OpenStreetMap road data into a road-network graph with OSMnx and NetworkX, then use LangGraph agents for graph-based routing, maintenance prioritization, and closure-impact analysis.
19. Medical Emergency Department AI System ≫ Advanced Module
Build an end-to-end Production AI Agent system for a Medical Emergency Department using the 12-Layer Engineering Stack. Design intake, triage, decision-support, and routing workflows while applying Business & Data Understanding, Knowledge, Model, Context, Semantic, Agent, Loop, Evaluation, Harness, and Infrastructure Engineering, plus Continual Learning. Handle missing data, context selection, task-specific models, Generate → Verify → Retry → Escalate loops, repeatable evals, trace capture and replay, operational fallbacks, and controlled production improvement.
20. Wind Turbine Continual Learning System ≫ Advanced Module
Build a self-improving Production AI Agent System for Wind Turbine Maintenance across 5 progressive versions. Combine Pattern Recognition and Isolation Forest anomaly detection with Episodic Memory, Agent Evaluation, Learning Signals, Continual Learning, and Controlled Continual Learning. Add Context Gating and applicability checks to prevent Negative Transfer, so learned expertise is applied only when relevant to the current incident. Includes 24 simulated North Sea wind turbines and 5 Gradio UIs to visualize how agent behavior improves over time.
You'll master world-class AI Agents tools and frameworks Claude Code, LangGraph, MCP, Google ADK, PydanticAI, CrewAI, and OpenAI Swarm, plus the Advanced Module, by building 20 real-world AI Agent projects across 16 industries and business domains.
︾
Your Instructor
Dr. Maryam Miradi - AI Expert, Educator, CEO & Chief AI Scientist
I began working in AI at age 17, building speech and image recognition systems. After earning my both Master’s degree and PhD in AI, I spent 20+ years building and leading real-world AI solutions for enterprises across 12 industries.
20+ Years Building AI in Production:
- 400+ Production AI Agents Built
- 3,200+ AI Professionals Trained across 130+ countries
- 160+ AI Projects across 12 industries
- PhD in AI, Machine Learning & Deep Learning
- 25 Publications and Books
- 5 International AI Awards
- Author of AI Agents: 50 Best Practices
- Speaker at PyData, AI Festival, Women in Data Science, and other international conferences
︾
Why AI Professionals Trust This Training
✱ Trusted by engineers, PhDs, and real-world builders in 130+ countries.
Extraordinary Expertise · Holistic · Comprehensive
Joachim M. Vis
AI Consultant | Germany
⭐⭐⭐⭐⭐
I have just Completed AI Agents Mastery and the Result is Mind-blowing!!
It was with great enthusiasm that I got to know Maryam's extraordinary expertise in the field of AI Agent technology. As an international lecturer of the AI Agents course, Maryam demonstrates a profound theoretical understanding and a special talent for tangibly and understandably communicating complex technologies.
What particularly impressed me was Maryam's holistic approach to AI agent implementation. Maryam combines different framework approaches such as LangGraph, CrewAI and OpenAI Swarm into a coherent overall concept and shows their practical application in a wide range of industries - from aviation to finance and healthcare.
Her course is ideal for getting started in AI Agent development. Maryam provides a solid technical foundation and a valuable overview of various frameworks and their possible applications. I particularly appreciate her open and supportive approach to questions, which makes the learning process so effective.
Exceptional Quality · Well-Chosen Projects · Outstanding Mentor
Tran Chanh Truc
AI Data Scientist | Vietnam
⭐⭐⭐⭐⭐
The AI Agents Mastery 7-in-1 course by Dr. Maryam Miradi clearly reflects an Exceptional Level of Dedication and care in both its Design and Delivery. Beyond the technical depth of the material, what stood out most was the deliberate way the course is structured to support learners at different stages, with common challenges anticipated and addressed proactively. The content feels refined through experience, featuring thoughtful explanations, well-chosen examples, and practical guidance that goes well beyond surface-level instruction.
Equally impactful is Ms. Miradi’s mentorship throughout the learning process, particularly her hands-on support when students get stuck. She consistently demonstrates attentiveness, patience, and a genuine commitment to student success by actively guiding learners through complex concepts, offering clear direction, alternative perspectives, and practical troubleshooting advice. Her responsiveness and willingness to engage deeply with students’ questions—often beyond what is minimally required—creates a supportive and encouraging learning environment. This combination of technical expertise, pedagogical dedication, and genuine mentorship not only accelerates learning but also builds confidence, making the course both professionally enriching and highly motivating.
Excellent Pace · Exceptionally Clear
Bachir Bekkaye
Senior Designer | USA
⭐⭐⭐⭐⭐
Maryam's course, AI Agents Mastery, is excellent. The pace is great, and everything is extremely well explained, especially for someone like me with basic Python knowledge and English as a second language. I've taken several courses before from various platforms, including Udemy, but yours stands out as the best by far hands down.
Deep Expertise ·
Real-World Experience
Maarten Majoor
Senior Data Scientist | Netherlands
⭐⭐⭐⭐⭐
Maryam offers a rare combination of in-depth technical expertise and experience in bringing high profile, complex Data Science solutions to fruition. This makes her a great mentor for both experienced and starting Data Scientists.
Transformative · Hands-On · Clear
Saranya Kamalasekaran
Data Scientist | USA
⭐⭐⭐⭐⭐
I recently completed the AI Agent Mastery course and found it incredibly valuable!
The content was thorough, the instructor was clear and knowledgeable, and the hands-on project was particularly beneficial. I highly recommend this course to anyone looking to enhance their AI skills.
World-Class · Committed · Results-Driven
Penelope Rammos
Senior Data Scientist | Netherlands
⭐⭐⭐⭐⭐
Maryam is genuinely one of the best AI Experts in the World. She goes Beyond Limits to Solve Problems. She invested a lot in her students.
Intuitively Explained · Highly Applicable
Alexander Fox
Senior Director, IT | USA
⭐⭐⭐⭐⭐
Maryam is a clear and thoughtful instructor and a true expert in the field. She explains advanced concepts in a practical, easy-to-understand way. The material is well structured and immediately applicable, and I’m looking forward to continuing to build on what I’ve learned.
Comprehensive · Real-World · Engaging
Shubham Pandey
Generative AI Solution Architect | India
⭐⭐⭐⭐⭐
Comprehensive introduction to the Latest Advancements in Generative AI, with clear explanations and practical examples. The hands-on exercises helped solidify concepts, and the real-world case studies were especially insightful. Overall, it was a well-structured and engaging learning experience.
Practical. Engaging.
Vara Prasad Nittala
Senior Data Consultant | Canada
⭐⭐⭐⭐⭐
I appreciated how Maryam's course, AI Agents Mastery, the Langchain module enhanced my understanding of integrating language models with different data sources, making the course more practical and engaging.
Structured · Flexible · Practical
Amobi Onovo Ph.D
Data Scientist | USA
⭐⭐⭐⭐⭐
In Maryam's course, AI Agents Mastery, LangGraph has Structured examples and CrewAI has Great and flexible tool for agent orchestration.
Accelerating. Clear. Practical
Alexander Sehdeva
Risk Analyst | USA
⭐⭐⭐⭐⭐
In Maryam's course, AI Agents Mastery, Langchain from working through course videos I am still ahead of most of my firm in terms of understanding agents. I demoed some simple react agents and working on fancier stuff. CrewAI is pretty straightforward due to good presentation.
Actionable · Well-Structured
Abraham Akhigbe Ola
SOC Analyst | Germany
⭐⭐⭐⭐⭐
Awesome and very well put together. I can now use the application here to build AI agents for SecOps especially Incident response.
Modular · Structured · Mastery-Driven
Sandipta Narayan Biswas
Sr. Solutions Architect | India
⭐⭐⭐⭐⭐
The structural breaking of the modules and gradually deep diving and finally really, I'm mastering in the subject. Agent-Based Modularity. Task-Oriented Workflow Definition. Human-Like Collaboration Simulation. Multi-LLM Support. Open Source and Extensible.
In-Depth · Practical · Cross-Industry
Sai Kovvuri
Cloud Solution Architect | USA
⭐⭐⭐⭐⭐
I really liked the depth of the course and how the concepts are taught through real-world use cases across multiple industries. The coverage of different AI agent frameworks was especially helpful, particularly understanding which framework fits which type of use case.
Practical · Enterprise-Focused · Applicable
Narendra Pydi
Enterprise Gen AI Architect | USA
⭐⭐⭐⭐⭐
I really enjoyed the AI Agents Mastery program 7-in-1. As an AI & Enterprise Architect, I found the practical approach especially valuable for understanding how AI agents can be designed and applied to real-world enterprise use cases.
Inspiring · Motivating · Forward-Looking
Jose Noguera
Full time professor and posdoc researcher | Colombia
⭐⭐⭐⭐⭐
It’s a very inspiring and motivating course. It gives you a clear view of how AI agents can be applied to real-world challenges and encourages you to think beyond individual tools and instead think in systems. For someone working across AI, research, innovation, and digital transformation, the course offers valuable, practical use cases that can inspire future projects.
Expert · Efficient · Solution-driven
Dennis Breed
Process Manager IT | Netherlands
⭐⭐⭐⭐⭐
Maryam is a real expert in Artificial Intelligence and Data Science. She is also a warm and caring person. Her expertise saved us a ton of time every week. She also knows perfectly how to convert a complex question into an AI solution including GUI.
︾
I created AI Agents Mastery 7-in-1 from 20+ years of hands-on AI experience, so you can skip disconnected tutorials and master production-ready AI agents end-to-end.
Get the Complete 7-in-1 Full-Stack · 60% off
+ Free Future Modules · Lifetime Updates
AI Agents Mastery
7-in-1 | Full-Stack
Claude Code . MCP . Google ADK · CrewAI · OpenAI Swarm · Pydantic AI · LangGraph
Enroll Now for $549