7 Sections
23 Lessons
3 Weeks
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Section 1: Foundations of GPT and LLMs
6
1.1
Basics of GPT
1.2
What Are LLMs? and Key Concepts
1.3
Transformer Architecture Explained
1.4
Practicals Section 1
1.5
Context Length in LLMs
1.6
Using Memory System to Solve Context Length Issues
Section 2: Prompt Engineering
3
2.1
Prompt Engineering & Types
2.2
Special Focus: Reasoning in LLMs Using Prompt Techniques
2.3
Practicals Section 2
Section 3: Understanding AI Agents - Agentic AI
3
3.1
Lesson 3.1: Understanding AI Agents
3.2
Lesson 3.2: Understanding Agentic AI and Its Difference with Agents
3.3
Lesson 3.3: Architecture of Agentic AI Systems
Section 4: Reasoning in LLMs and Its Role in Agentic Systems
5
4.1
Lesson 4.1: Understanding Reasoning and It’s Evolution in LLMs
4.2
Lesson 4.2: Reasoning’s Critical Role in Agentic Systems
4.3
Lesson 4.3: ReACT-Based Model Tuning
4.4
Lesson 4.4: Prompt-Based Model Tuning
4.5
Practicals Section 4
Section 5: Agentic Frameworks
2
5.1
Lesson 5.1: How to prepare your organization for implementation (SOP)
5.2
Practicals Section 5
Section 6: Agentic AI - A2A Future of Work
4
6.1
Lesson 6.1: Agent to Agent Future
6.2
Lesson 6.2: Agents, Protocols (MCP, Google A2A, Others), and A2A Future
6.3
Lesson 6.3: Cloud vs. Going Local with Edge AI: Privacy Concerns
6.4
Lesson 6.4: Future Employees and Their Role in Agentic AI World
Quiz
1
7.1
Quiz – L1 AI Agents
20 Minutes
12 Questions
Fundamentals of AI Agents and Building AI Agents with Low Code
Curriculum
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