CourseFlix

AI Agents Masterclass

0h 0m 0s
English
Paid

AI Agents Masterclass gives you a clear, practical path into agent development. You work with real tools and build agents that solve real tasks. The goal is simple: you learn how agents think, act, and work in production systems.

Why This Course Stands Out

You focus on practice from the start. You build more than ten agents, and each one solves a clear task. This helps you see how agents behave in real conditions.

Hands-on Work

You create agents for data work, search, content tasks, support tasks, and workflow steps. Each agent has code, logic, and a live demo.

Modern Frameworks

You work with tools used in current AI products:

  • CrewAI
  • AutoGen
  • OpenAI Agents SDK
  • Google ADK
  • LangGraph

You see how each tool is built and where it fits best.

Engineer Mindset

The course shows you how to think like an agent engineer. You learn how to plan agent logic and handle state and memory.

Core Skills

  • designing clear agent steps
  • tracking state and memory
  • setting up agent-to-agent talk
  • picking the right design for each task
  • scaling agents for real use

Projects You Build

You build working agents from the first lessons. Each project covers one problem and shows you how to solve it with tools and rules.

Sample Projects

  • an agent that reads and sorts news
  • a job search agent that filters roles
  • a research agent that forms clear findings
  • AI assistants and chatbots
  • a basic investment helper
  • a tool that creates YouTube Shorts and covers
  • AI tutors and consultants

Who Should Join

  • developers who want to enter agent work
  • engineers who work with LLMs or automation
  • founders and product leads building AI features
  • people who want to replace manual tasks with agents

The level is intermediate. You only need basic programming skills.

What You Will Learn

By the end, you will know how modern agents work and how to use the right tool for each job.

  • understand core agent design ideas
  • pick and use the right framework
  • plan and build agents for real tasks
  • create a small portfolio of agent projects
  • apply agents in products and automation

About the Author: Nomad Coders

Nomad Coders thumbnail
Nomad Coders is a space for creativity and programming education where you not only acquire essential skills but also bring a functional project to life. Our approach involves learning by working on real tasks. Join us to learn programming practically and efficiently!

Watch Online 151 lessons

This is a demo lesson (10:00 remaining)

You can watch up to 10 minutes for free. Subscribe to unlock all 151 lessons in this course and access 10,000+ hours of premium content across all courses.

View Pricing
0:00
/
#1: 0.2 Welcome
All Course Lessons (151)
#Lesson TitleDurationAccess
1
0.2 Welcome Demo
00:00
2
0.3 Why So Many Frameworks
00:00
3
0.4 Course Structure
00:00
4
0.5 Requirements
00:00
5
0.6 Breaking Changes
00:00
6
1.0 UV
00:00
7
1.1 PyProject
00:00
8
1.2 Jupyter
00:00
9
2.0 Setup
00:00
10
2.1 Your First AI Response
00:00
11
2.2 Your First AI Agent
00:00
12
2.3 Adding Memory
00:00
13
2.4 Adding Tools
00:00
14
2.5 Adding Function Calling
00:00
15
2.6 Tool Results
00:00
16
2.7 Conclusions
00:00
17
3.0 Introduction
00:00
18
3.1 Your First CrewAI Agent
00:00
19
3.2 Custom Tools
00:00
20
3.3 News Reader Tasks and Agents
00:00
21
3.4 News Reader Crew
00:00
22
3.5 Conclusions
00:00
23
4.0 Introduction
00:00
24
4.1 Agents and Tasks
00:00
25
4.2 Context And Structured Outputs
00:00
26
4.3 Firecrawl Tool
00:00
27
4.4 Knowledge Sources
00:00
28
4.5 Conclusions
00:00
29
5.0 Introduction
00:00
30
5.1 Your First Flow
00:00
31
5.2 Content Pipeline Flow
00:00
32
5.3 Refinement Loop
00:00
33
5.4 LLMs and Agents
00:00
34
5.5 Adding Crews To Flows
00:00
35
5.6 Conclusions
00:00
36
5.7 Outro
00:00
37
6.0 Introducton
00:00
38
6.1 Email Optimizer Team
00:00
39
6.2 Deep Research
00:00
40
6.3 Conclusions
00:00
41
7.0 Introduction
00:00
42
7.1 Agents and Runners
00:00
43
7.2 Stream Events
00:00
44
7.3 Session Memory
00:00
45
7.4 Handoffs
00:00
46
7.5 Viz and Structured Outputs
00:00
47
7.6 Tracing
00:00
48
7.7 Conclusions
00:00
49
7.8 Welcome To Streamlit
00:00
50
7.9 Streamlit Data Flow
00:00
51
8.0 Chat UI
00:00
52
8.1 Conversation History
00:00
53
8.2 Web Search Tool
00:00
54
8.3 File Search Tool
00:00
55
8.4 Multi Modal Agent
00:00
56
8.5 Image Generation Tool
00:00
57
8.6 Code Interpreter Tool
00:00
58
8.7 Hosted MCP Tool
00:00
59
8.8 Local MCP Server
00:00
60
8.9 Conclusions
00:00
61
9.0 Introduction
00:00
62
9.1 Context Management
00:00
63
9.2 Dynamic Instructions
00:00
64
9.3 Input Guardrails
00:00
65
9.4 Handoffs
00:00
66
9.5 Handoff UI
00:00
67
9.6 Hooks
00:00
68
9.7 Output Guardrails
00:00
69
9.8 Voice Agent I
00:00
70
9.9 Voice Agent II
00:00
71
10.0 Introduction
00:00
72
10.1 ADK Web
00:00
73
10.2 Tools and Subagents
00:00
74
10.3 Agent Architecture
00:00
75
10.4 Agent State
00:00
76
10.5 Artifacts
00:00
77
11.0 Introduction
00:00
78
11.1 Content Planner Agent
00:00
79
11.2 Prompt Builder Agent
00:00
80
11.3 Image Builder Agent
00:00
81
11.4 Audio Narration Agent
00:00
82
11.5 Video Assembly
00:00
83
11.6 Callbacks
00:00
84
11.7 Conclusions
00:00
85
12.0 Introduction
00:00
86
12.1 LoopAgent
00:00
87
12.2 Agent Evaluations
00:00
88
12.3 API Server
00:00
89
12.4 Sever Sent Events
00:00
90
12.5 Invocation Flow
00:00
91
12.6 Runner
00:00
92
12.7 Deployment to VertexAI
00:00
93
13.0 Introduction
00:00
94
13.1 Your First Graph
00:00
95
13.2 Graph State
00:00
96
13.3 Recap
00:00
97
13.4 Multiple Schemas
00:00
98
13.5 Reducer Functions
00:00
99
13.6 Node Caching
00:00
100
13.7 Conditional Edges
00:00
101
13.8 Send API
00:00
102
13.9 Command
00:00
103
14.0 LangGraph Chatbot
00:00
104
14.1 Tool Nodes
00:00
105
14.2 Memory
00:00
106
14.3 Human-in-the-loop
00:00
107
14.4 Time Travel
00:00
108
14.5 DevTools
00:00
109
15.0 Introduction
00:00
110
15.1 Audio Extraction and Transcription
00:00
111
15.2 Summarizer Nodes
00:00
112
15.3 Thumbnail Sketcher Nodes
00:00
113
15.4 Human Feedback
00:00
114
15.5 HD Thumbnail Generation
00:00
115
16.0 Introduction
00:00
116
16.1 Prompt Chaining Architecture
00:00
117
16.2 Prompt Chaining Gate
00:00
118
16.3 Routing Architecture
00:00
119
16.4 Parallelization Architecture
00:00
120
16.5 Orchestrator-workers Architecture
00:00
121
16.6 Conclusions
00:00
122
17.0 Introduction
00:00
123
17.1 Email Graph
00:00
124
17.2 Pytest
00:00
125
17.3 Testing Nodes
00:00
126
17.4 AI Nodes
00:00
127
17.5 Testing AI Nodes
00:00
128
17.6 Testing AI Responses
00:00
129
18.0 Introduction
00:00
130
18.1 Network Architecture
00:00
131
18.2 Network Visualization
00:00
132
18.3 Supervisor Architecture
00:00
133
18.4 Supervisor As Tools
00:00
134
18.5 Prebuilt Agents
00:00
135
19.0 Introduction
00:00
136
19.1 Classification Agent
00:00
137
19.2 Feynman Agent
00:00
138
19.3 Quiz Agent
00:00
139
19.4 Conclusions
00:00
140
20.0 Introduction
00:00
141
20.1 A2A Using ADK
00:00
142
20.2 A2A For Dummies
00:00
143
20.3 RemoteA2aAgent
00:00
144
20.4 FastAPI Server
00:00
145
20.5 SendMessageResponse
00:00
146
21.0 Introduction
00:00
147
21.1 Conversations API
00:00
148
21.2 Sync Responses
00:00
149
21.3 StreamingResponse
00:00
150
21.4 Deployment
00:00
151
21.5 Conclusions
00:00
Unlock unlimited learning

Get instant access to all 150 lessons in this course, plus thousands of other premium courses. One subscription, unlimited knowledge.

Learn more about subscription