Learn Artificial Intelligence in Tirupati with a practical focus on agentic AI, Generative AI, LangChain, OpenAI API, Hugging Face, vector databases, and deployment workflows. You will build agent-based and LLM-driven projects using tools from the syllabus and software stack, with training that is aimed at real project work, not just theory.
14,200+ (Placed)
Freshers to IT
7,100+ (Placed)
Non-IT to Tech
5,800+ (Placed)
Career Gap Fillers
6,400+ (Placed)
Upskilling Success
24,999₹
In 60 Days + Placement
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Learning AI is useful only when you can show practical work and explain it well in interviews. Inventateq supports learners in Tirupati with course-aligned preparation so they can move toward roles that use generative AI, agentic workflows, and LLM tools in real projects.
AI skills are used in analytics, automation, chatbot development, and product teams across IT services, startups, and data-driven businesses. Salary grows as you move from project support work to building and deploying AI systems independently.
Artificial Intelligence Average Salary by Experience
AI skills are used in analytics, automation, chatbot development, and product teams across IT services, startups, and data-driven businesses. Salary grows as you move from project support work to building and deploying AI systems independently.
Artificial Intelligence Average Salary by Experience
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Inventateq teaches Artificial Intelligence in Tirupati with a project-first approach that follows the actual syllabus: agentic AI, prompt engineering, tools and function calling, memory, frameworks, evaluation, deployment, and Generative AI projects. The training stays practical and tool-based, so learners can connect concepts to working implementations instead of memorizing definitions.
We stand apart through our commitment to:
Live online Artificial Intelligence batches from Tirupati follow the same course plan and project flow as classroom training. You can attend from home, learn from the same mentors, and complete assignments with support during the session.
Students who want to start an AI, data, or analytics career with practical training.
Professionals who want to move into AI, automation, or LLM-based project work.
People with Excel, SQL, or Python basics who want to add AI skills.
Beginners who can follow a structured course and want clear project-based learning.
Learners aiming for roles like AI Analyst, Data Analyst, or Business Analyst.
Mode: Classroom and live online training
Focus: Agentic AI and Generative AI
Project work: Hands-on assignments and guided builds
Certification: Course completion certificate
No prior AI experience is required to start the course.
Rated 4.9/5
Inventateq keeps the Artificial Intelligence course practical from the first module to the last project. Learners in Tirupati work through AI frameworks, prompt design, tool use, memory, evaluation, and deployment in a sequence that matches how real AI applications are built.
By the end of the course, learners have worked through agentic AI, Generative AI, memory systems, evaluation, and deployment tasks. The goal is to help you speak about AI projects confidently and show a portfolio that reflects real implementation work.
You learn how to design agents that can reason, act, call tools, and manage steps across a workflow. This includes ReAct, planning, multi-agent patterns, and human-in-the-loop control.
You work on OpenAI API, LangChain, Hugging Face, vector databases, and chatbot-style projects. The course includes a medical chatbot build and deployment flow.
You practice function calling, schema-based tools, short-term and long-term memory, and state management. These are the parts that make an AI application stable and useful.
You learn how to trace failures, measure agent behavior, and use observability tools like LangSmith and Phoenix Arize. This helps when outputs are inconsistent or workflows break.
You gain exposure to Docker, FastAPI, AsyncIO, and cloud deployment patterns. The course shows how AI projects move from notebook-style work to usable services.
You get practice explaining your work clearly for AI, data, and analytics roles. That makes your projects easier to present in interviews and portfolio reviews.
This certification shows that you have completed structured training in agentic AI, Generative AI, tool use, memory, evaluation, and deployment. It helps employers see that you have trained on practical AI workflows, not only theory.
Earn this certificate upon successful completion of our training program.
Validate your skills with recognized industry credentials.
Earn this certificate upon successful completion of our training program.
Yes, the course is suitable for beginners because it starts with the evolution from NLP to LLMs, chatbots, and agents. The concepts are taught in a sequence that builds understanding gradually. If you can follow basic computer and internet usage, you can start the course.
Yes, the syllabus includes practical work such as a research agent, a data analyst agent, and a medical chatbot project. You also work with function calling, memory, evaluation, and deployment. The training is designed to make you build and explain real project outputs.
The course covers tools and platforms such as OpenAI API, LangChain, Hugging Face, Pinecone, LangGraph, AutoGen, CrewAI, LangSmith, Phoenix Arize, Docker, FastAPI, Playwright, and Selenium. The software column also supports Python, Jupyter-style workflow, and deployment tools used in modern AI projects. These tools are used in the curriculum, not just listed as names.
Yes, placement support is included to help learners prepare for interviews and present their work properly. You get help with resumes, project discussion, and mock interviews. The focus is on roles related to AI, data, analytics, and business support.
Yes, working professionals can join if they want to move into AI-related work or add LLM and automation skills to their profile. The course covers applied topics that are useful for current project environments. Online and classroom options make it easier to balance learning with work.
The curriculum is organized in a multi-week format covering agentic AI, Generative AI, projects, and deployment. Exact pacing can vary by batch, but the structure is detailed enough to cover both foundations and advanced topics. You can choose the mode that fits your schedule and learning speed.
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