Welcome to AI Automation Workflow, AI Voice Agent, Vector Database, MCP course. This is a comprehensive project based course where you will learn how to automate many repetitive tasks using AI, build a variety of AI agents, connect your AI model with vector database, and integrate model context protocol server. This course is a perfect combination between AI automation and AI agents, making it an ideal opportunity to practice your artificial intelligence skills while improving your technical knowledge in large language models and prompt engineering.
In the introduction session, you will learn the basic fundamentals of AI automation and AI agents, such as getting to know their use cases and their workflow. Then, in the next section, you will learn about vector databases and how it enables AI models to store knowledge long term, retrieve the most relevant information through similarity search, and generate context aware responses that are far more accurate than prompt only outputs. Afterward, in the next section, we will start building AI automation workflows using tools like Zapier, Make, and n8n.
Firstly, we are going to build an AI email responder. It is an automation that reads incoming emails, understands the intent and tone, and generates professional replies instantly while still allowing you to approve before sending. Following that, in the second project, we will create an AI customer feedback analyzer, which automatically collects customer feedback from multiple platforms and performs sentiment and keyword analysis to summarize insights.
In the third project, we will build AI expense categorization, a system that scans receipts or transaction records and automatically assigns them to the proper accounting categories. In the fourth project, we will develop a Smart Inventory System, an automation that monitors product stock levels, predicts when items are running low, and notifies you or triggers purchase orders automatically. Then, in the fifth project, we are going to set up AI appointment booking automation, where AI will schedule appointments based on your availability and send meeting reminders.
In the sixth project, we will build AI content marketing automation, a workflow that takes your business updates or product information and generates article drafts, social media captions, and scheduled posts. Then, in the next section, we will build AI agents using tools like Relay App, Gumloop, Vapi, Voiceflow, Eleven Labs, and Zapier. We are going to build a variety of AI agents, for example, lead generation agent, product research agent, supply chain contract analyzer agent, and voice agents for receptionist, customer support, and sales. In addition, we are also going to do a little bit of programming using Python. We are going to build an AI data analysis agent using Llama and we are also going to build an AI multi agent system for project management using Gemma.
Then, after that, we are going to build an AI Food Recipe Generator that is fully connected to a Pinecone vector database, enabling the AI model to automatically analyze the ingredients you currently have and generate personalized recipe ideas based solely on the items available in your food inventory. Lastly, at the end of the course, we will learn about MCP server integration, specifically, we will create Zapier MCP server and connect it to Google Sheet and Mistral AI, so the AI model will be able to interact with external tools.
