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Agentic AI with Python
Agentic AI with Python Training in Nepal Learn to Build Autonomous AI Agents with Hands-On Practical Training Future-Ready, Project-Based & Industry-Focused Program Master the next generation of AI by learning how to design, build, and deploy intelligent agents that can reason, plan, use tools, remember context, and solve real-world problems. No unnecessary theory. No outdated concepts. Only practical skills that help you build the AI systems shaping the future. What You Will Be Able To Do After This Training You will learn how to: Build intelligent AI agents using Python Design autonomous systems beyond traditional chatbots Integrate Large Language Models into real applications Implement memory and Retrieval-Augmented Generation (RAG) systems Connect AI agents with APIs, databases, and external tools Develop multi-agent collaborative workflows Build applications using LangChain and LangGraph Fine-tune LLMs using modern techniques Test, optimize, and deploy production-ready agents Create end-to-end Agentic AI solutions Future-Ready Agentic AI Skills You will master how to: Design and develop autonomous AI agents Engineer effective prompts and reasoning workflows Implement planning and decision-making capabilities Enable long-term memory and contextual understanding Build agents capable of tool usage and automation Develop scalable multi-agent architectures Fine-tune models efficiently using PEFT and LoRA Deploy reliable and secure AI systems Build the intelligent systems that modern organizations are adopting today. What You Will Learn (Modules Covered) Introduction to Agentic AI Foundations of AI & Machine Learning Large Language Models (LLMs) Agent Architectures & Design Patterns Reasoning, Planning & Decision Making Memory, RAG & Knowledge Systems Tool Use & API Integration Multi-Agent Systems LangChain & LangGraph Frameworks Testing, Evaluation & Optimization Deployment, Ethics & Security Fine-Tuning Large Language Models Capstone Project Development Who This Course Is ForPerfect for: Python developers exploring AI applications AI and Machine Learning enthusiasts Software engineers building intelligent products Data professionals transitioning into Generative AI Students aiming for careers in emerging technologies Professionals seeking future-ready AI skills 2 Basic Python programming knowledge is recommended. Why This Training Is Different Learn by building real AI agents from scratch Practical labs in every module Industry-relevant frameworks and workflows Project-driven learning approach Exposure to modern Agentic AI patterns Focus on implementation, not just concepts Capstone project showcasing real-world applications Tools & Technologies You Will Learn Python OpenAI APIs LangChain LangGraph Vector Databases Hugging Face PEFT / LoRA Retrieval-Augmented Generation (RAG) Tools Docker Deployment Concepts API Integrations Git & Development Tools …and many more. Career Opportunities After This Training After completing this course, you can: Work as an AI Engineer Become an Agentic AI Developer Build autonomous business applications Develop enterprise AI solutions Contribute to Generative AI projects Freelance on AI implementation projects Create and launch your own AI products Start Building the Future with Agentic AI Agentic AI is transforming how software interacts, reasons, and automates tasks. This training is designed to help you: Learn practical skills → Build intelligent agents → Develop real projects → Advance your AI career Frequently Asked Questions (FAQ) – Agentic AI with Python Training in Nepal What is Agentic AI? Agentic AI refers to intelligent systems capable of reasoning, planning, making decisions, using tools, and autonomously completing tasks to achieve specific goals. Do I need prior experience to join this course? Participants should have fundamental Python programming knowledge and a basic understanding of programming concepts. Prior AI experience is beneficial but not mandatory. What frameworks will I learn? You will work with industry-relevant technologies such as LangChain, LangGraph, OpenAI APIs, vector databases, Hugging Face, and RAG systems. Will this course include hands-on projects? Yes. Every module includes practical exercises, and the course concludes with a capstone project where you build a real-world AI agent. Can this training help me in my career? Absolutely. Agentic AI skills are increasingly in demand across industries, opening opportunities in AI engineering, software development, automation, and intelligent product design. 4 Will I receive a certificate? Yes. Participants who successfully meet the completion criteria will receive a certificate upon completion of the training.
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DATA SCIENCE AND MACHINE LEARNING IN PYTHON
Course SynopsisThis course is targeted for beginners who want to learn how to think and write meaningful pieces of code or read codes written by someone else in Python. This course teaches how to map literary description of a problem (requirement) to an application/library coded in Python. This is a core basic level course that is essential for anyone who has no prior programming experience but wishes to be a professional Python engineer in future. Required Textbooks Chris Albon, “Machine Learning with Python Cookbook”, O’Reilly Media Inc. US.LazyProgrammer, “Deep Learning in Python”, LazyProgrammer, US.Oliver Theobald, “Machine Learning for Absolute Beginners”, Scatterplot Press. Completion CriteriaAfter fulfilling all of the following criteria, the student will be deemed to have finished the Module: Has attended 90% of all classes held.Has received an average grade of 80% on all assignment. Has received an average of 60% in assessments.The tutor believes the student has grasped all of the concepts and is ready to go on to the next module. PrerequisitesBasic knowledge about programming, bits/bytes, procedures, classes, computer architecture, etc. If you just have theoretical knowledge that is perfectly okay but you should have strong convictions on what programming is, and what you hope to achieve from this class.Willing and eager to spend at least 10-20 hours (Varying from student-to-student) per week outside of the training class to self-study and practice.There is no prior educational level requirement for this course. Anyone from 10+2 student to someone who is doing their PHD in Genetic Engineering is welcome to take this course.If you are only interested in theory and have no interest/patience in spending at least 10 hours every week throughout the duration of the course, then this course might not be for you.
