Become an AI Engineer
Build an AI Agent
Become an
AI Engineer
Our AI Engineer MasterClass will teach you how to build an enterprise-grade agent.
Master AI (LLM) Engineering
Get hands-on experience of an ML Engineer in a 5-week Online program led by AI Tech Lead.
- 5 Weeks
- Online program
- 18 Hours
- Instructor-led classes
- 1 Instructor
- AI Tech Lead
- 4 Modules
- End-to-End Development
Our Agent TechStack
Gain hands-on experience as an AI Engineer in our 5-week online program, led by an AI Tech Lead.
Work with cutting-edge tools and frameworks used in real-world AI systems, including data pipelines, context management, agent framework and deployment.
Learn to build a production-grade financial analyst agent that performs financial analysis with realtime stock and news data.
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Data Pipeline Layer
Build realtime data pipeline for news and stock price data. Ingest them in databases like Snowflake and ElasticSearch
- Snowflake
- Scraper
- Orchestration
- Websocket
Context Layer
Store realtime data in RAG using Pinecone and manage memory in cache them using Redis
- Redis
- Orchestration
- Embedding
- Pinecone
- FAISS
Agent Layer
Build an agent stack with the state-of-the-art LLMs (i.e. Deepseek R1 and GPT o3-mini. Build custom tools that enables agents to apply ML
- GPT
- Deepseek
- Claude
- LangChain
- Evals
Deployment Layer
Deploy the model to Kubernetes services on Google Cloud and monitor agent Ops using LangSmith
- LangSmith
- FastAPI
- Githb Actions
- Logs
- Kubernetes
Who Should Enroll?
Master skills in building AI solutions using tools and frameworks, tailored for developers, analysts and aspiring engineers.
AI Developers
You're a developer looking to integrate AI (LLM) into your applications, optimize performance, and scale AI-driven solutions.
Data Scientists and Analysts
You already work with data and want to advance your skills in AI (LLM) engineering, real-time ML pipelines, and model deployment.
University Students
You're a student aiming to break into AI, LLM, ML engineering, gain hands-on experience, and get job-ready for top tech roles.
AI Directors and CTOs
You're a tech leader looking to refine your knowledge in MLOps, AI system design, and large-scale deployment.
Your Instructor
For the past nine years, I've worked as an AI, ML, and data science practitioner, previously at a Google. Now, I run AI projects as an external consultant for startups, developing and deploying scalable AI solutions. As your instructor, I will guide you through the ins and outs of building and deploying scalable AI systems. Excited to work with you all!
LinkedInOur Class Schedule
Our class is held online every Tuesday and Thursday for five weeks, from 8:30 to 10:30 A.M. PST / 11:30 A.M. to 1:30 P.M. EST / 5:30 to 7:30 P.M. CET. The final session will be dedicated to showcasing your capstone project.
| Topic | Date | Time (EST) |
|---|---|---|
| Agent Foundation - Architecture, Logic, LLM and Core Components | Mar 18, 2025 | 11:30 AM - 1:30 PM |
| Agent Frameworks & Prompt Engineering with Prompt Management | Mar 20, 2025 | 11:30 AM - 1:30 PM |
| Embedding, Data Pipeline, Tools & Retrieval | Mar 25, 2025 | 11:30 AM - 1:30 PM |
| Memory Management with Redis | Mar 27, 2025 | 11:30 AM - 1:30 PM |
| Agent Evaluation | Apr 1, 2025 | 11:30 AM - 1:30 PM |
| Agent API with FastAPI and Streamlit Client | Apr 3, 2025 | 11:30 AM - 1:30 PM |
| Agent Deployment with Kubernetes | Apr 8, 2025 | 11:30 AM - 1:30 PM |
| Agent Ops with LangSmith | Apr 10, 2025 | 11:30 AM - 1:30 PM |
| Demo Day | Apr 17, 2025 | 11:30 AM - 1:30 PM |
AI Engineer Certification
Upon the completion of the 5-week program and capstone project deliverable, you will receive a certification that showcases your skills in AI agent development and deployment.
Join Our AI Engineer MasterClass
Become an AI Engineer Expert
Our class is held online every Tuesday and Thursday for five weeks, from 8:30 to 10:30 A.M. PST / 11:30 A.M. to 1:30 P.M. EST / 5:30 to 7:30 P.M. CET. The final session will be dedicated to showcasing your capstone project.
What's included
- 18 hours of live classes
- 4 modules
- 1 AI instructor
- Certification
- Best practices in AI engineering
- Cohort-based learning
- Discord channel
- Alumni community
Frequently asked questions
Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email at dan@aischool.com and we'll get back to you as soon as we can.
- Am I ready for the masterclass?
- This course is an intermediate/advanced course in AI engineering. We expect that you have had 1-year of professional experience in ML/AI or currently studying computer science, machine learning as a student..
- What is the pre-requisite knowledge for the masterclass?
- We expect that you already grasp the basics of Python programming.
- How advanced in this course?
- We will teach best practices in AI engineering in major areas of AI engineering from data, context, frameworks and deployment.
- How much coding do I need to know?
- This is an applied course leveraging existing LLM solutions like Deepseek and OpenAI APIs, we will not be delving into mathematics in thise course.
- What is the tech stack covered in the course?
- We will use Python, LangSmith, Colab, Docker, Cloud (e.g. Google Cloud Platform), FastAPI.
- I won't be able to attend some of the class, will the class be recorded? And, how long is the access?
- Yes, the class will be recorded, and you will have access to it for a year.
- What goes on in the Discord group?
- You will gain access to community of instructors, your peers in current masterclass and alumni to exchange ideas and upskill in AI engineering together.
- What happens after I purchase?
- You will receive an onboarding content, including Discord group access and Zoom invites to your classes.
- Can I get a company reimbursement?
- Yes, we will send you an invoice that enables you to reimburse the purchase.
- How do I get the AI Masterclass certification?
- After completion of the Capstone project, you will receive the AI Masterclass Certification which you can display on your professional portfolio (e.g. resume, LinkedIn).