Coming Soon
Beginner
Agentic AI for Beginner: Build AI Agents From Scratch
Learn to build intelligent AI agents from scratch using LLMs, memory, reasoning, tool integration, RAG, and automation workflows. Develop autonomous AI solutions that perform real-world tasks, enhance productivity, and streamline business processes through hands-on projects
Recommended Course Audience
Pre-Required Skills
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Basic Python programming knowledge
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Understanding of Generative AI and LLM fundamentals
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Familiarity with Prompt Engineering concepts beneficial
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Interest in AI automation and intelligent systems helpful
Course Highlights
16 modulesLearn to design, build, and deploy intelligent AI agents using Large Language Models, prompt engineering, memory systems, tool integration, reasoning, RAG, multi-agent collaboration, automation, and modern agent frameworks. By the end of this course, learners will create autonomous AI solutions capable of solving real-world business and productivity challenges.
Introduces Agentic AI concepts, AI agents, agent lifecycle, core components, types of agents, real-world applications, and the differences between traditional AI, Generative AI, and Agentic AI.
Explains how LLMs power AI agents through reasoning, language understanding, embeddings, context windows, decision-making, and API integration while addressing limitations and practical considerations.
Covers Python fundamentals required for agent development, including functions, APIs, JSON processing, file handling, exception management, environment variables, and project setup.
Teaches effective prompt design techniques including zero-shot, few-shot, chain-of-thought, ReAct prompting, structured outputs, and prompt optimization for intelligent agent behavior.
Guides learners through creating a complete AI agent, covering agent architecture, task execution, decision-making workflows, response generation, and interactive user experiences.
Introduces external tool integration, function calling, API connectivity, structured outputs, and dynamic action execution, enabling agents to perform real-world tasks effectively.
Explores memory management techniques including short-term memory, long-term memory, conversational memory, context retention, personalization, and persistent memory architectures.
Focuses on enhancing agents with external knowledge using embeddings, vector databases, semantic search, document retrieval, and knowledge-based question-answering systems.
Covers planning strategies, task decomposition, goal-oriented workflows, reasoning techniques, reflection methods, self-correction mechanisms, and multi-step problem-solving approaches.
Introduces collaborative AI systems where multiple agents communicate, coordinate, distribute tasks, and work together to solve complex problems efficiently.
Provides an overview of popular agent development frameworks including LangChain, LangGraph, CrewAI, and AutoGen, helping learners understand modern agent-building ecosystems.
Demonstrates how agents automate workflows, orchestrate tasks, respond to events, improve productivity, and streamline business operations through intelligent automation.
Introduces no-code and low-code platforms such as n8n for building AI-powered workflows, integrating services, and creating automation solutions without extensive coding.
Covers deployment fundamentals, cloud concepts, API-based deployment, monitoring, maintenance, security considerations, performance optimization, and production readiness practices.
Applies course concepts through real-world projects and industry scenarios, enabling learners to design, build, evaluate, and present practical AI agent solutions.
$199.00
This course is coming soon. Enrollment is not yet open.
For any support or technical enquiries, please reach out to info@solixacademy.com
Level
:
Beginner
Modules
:
16
Duration
:
60 hours