Learn agentic AI and generative AI in San Francisco with hands-on work on OpenAI API, LangChain, LangGraph, AutoGen, CrewAI, Hugging Face, Pinecone, FastAPI, Docker, and cloud deployment. You will build practical agents, workflow systems, and deployable AI projects based on the syllabus in this course.
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
Free Session
Get Job with our Guaranteed Placement Support Program
Learning AI is only useful when you can show real projects and explain them well in interviews. Inventateq focuses on that part too, with resume support, project guidance, and interview preparation built around the roles that follow this course in San Francisco. The goal is to help you move from training into practical AI, analytics, and automation jobs.
San Francisco has steady demand for AI, analytics, automation, and data roles across tech, product, consulting, and business teams. Salaries grow with your ability to design agents, deploy workflows, and handle tools, memory, and evaluation properly.
Artificial Intelligence Average Salary by Experience
San Francisco has steady demand for AI, analytics, automation, and data roles across tech, product, consulting, and business teams. Salaries grow with your ability to design agents, deploy workflows, and handle tools, memory, and evaluation properly.
Artificial Intelligence Average Salary by Experience
4.7/5 Google Rating | 1,432+ Verified Reviews
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4.7 / 5
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Success Result: Our students are competing at global levels. Watch their placement journey here.
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4.7/5 · 1,432+ Verified Reviews
Inventateq teaches artificial intelligence in a practical way, with a clear path from concepts to working agents and deployable projects. The syllabus covers agentic AI, prompt engineering, tools and function calling, memory architectures, multi-agent systems, guardrails, evaluation, and cloud deployment, so learners can actually build and explain what they build.
We stand apart through our commitment to:
Live online training is available for learners in San Francisco who want the same class structure from home or work. Sessions are interactive, practical, and guided by the same syllabus, with project work, doubt clearing, and mentor feedback included.
Good for beginners who want an entry path into AI, data, and automation roles.
Useful for developers, analysts, and engineers moving into agentic AI and LLM workflows.
Fits people already working with data who want to add AI tools, memory, and deployment skills.
A practical option for learners from non-AI backgrounds who want guided training.
Works for anyone who wants to understand how AI agents are built and deployed.
Duration: Covers the full AI syllabus in a structured training flow.
Mode: Available as classroom and live online training.
Format: Theory, practicals, assignments, and project work are included.
Batch Timing: Weekday and weekend batch options are available.
No prior AI background is needed to start this course.
Rated 4.9/5
Inventateq keeps the training practical from the first class. You move through the syllabus by building agents, connecting tools, testing memory, and deploying working projects instead of only reading concepts.
By the end of the course, you will have worked on structured AI workflows, multi-agent systems, and deployable applications. You will also understand how to explain the tools, decisions, and limitations behind what you built.
You will create agents that can reason, act, use tools, and handle structured outputs. The course moves from a basic ReAct loop to more advanced agent frameworks and workflows.
You will connect agents to functions, web actions, vector databases, and external APIs. That gives you practical experience with the same type of integration used in real projects.
You will learn how long-running AI systems store context, past actions, and outcomes. That helps you build systems that do more than answer one prompt at a time.
You will practice collaboration patterns such as manager-worker, debate, and sequential handoffs. This makes the course useful for automation and orchestration roles.
You will prepare services for cloud deployment using FastAPI, Docker, and async workflows. That makes your work easier to show to employers.
You will have project stories, technical practice, and placement support that help you speak confidently about AI tools and design choices.
The certification shows that you have completed practical training in agentic AI, generative AI, tools, memory, evaluation, and deployment. It helps employers see that your learning is project-based and tied to current AI workflows.
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.
Validate your skills with recognized industry credentials.
Yes, the course starts with the basics of agents, LLMs, and prompting before moving into advanced workflows. A beginner can follow it if they are willing to practice regularly and complete the assignments. Mentors also help with questions during the training.
Yes, the syllabus includes practical exercises such as a Research Agent, a Data Analyst Agent, and an end-to-end medical chatbot. You also work with function calling, memory, evaluation, and deployment tasks. The training is built around doing, not just listening.
Yes, placement support is part of the course structure. You get help with resume preparation, interview practice, and presenting your projects clearly. The support is tied to the roles that typically follow this training, such as data analyst, business analyst, and AI engineer.
Yes, many learners start from a non-AI background and build up step by step. The course explains concepts in a practical way and connects them to tools and projects. If you can follow a structured learning path, you can join and progress.
Yes, live online training is available and follows the same syllabus as the classroom batch. You can attend from home while still getting mentor interaction, project guidance, and doubt clearing. It is a good option if you want flexibility without losing structure.
The syllabus is structured across multiple weeks and covers foundational to advanced AI topics. It includes agentic AI, generative AI, vector databases, open-source LLMs, and deployment work. The exact pace can depend on the batch mode and schedule.
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