Course Overview
Starting On Thursday, February 6th, 2025
This course offers a balanced mix of theoretical foundations and hands-on experience. Through a series of projects and labs, participants will gain practical knowledge and insights into the intricacies of AI agent development.
Join us to advance your expertise and stay at the forefront of AI technology.
Learning Outcome
By the end of this course, you should be equipped with the skills and knowledge required to design, implement, and manage AI agents in enterprise environments.
Schedule
| START DATE | THURSDAY, FEBRUARY 6th, 2025 |
|---|---|
| Periodicity | Meets every Thursday and Tuesday for eight weeks |
| Schedule | From 7 PM to 9:30 PM PST |
Skills You Will Learn
Agentic principles and best practices, harnessing multiple AI agents to build complex real-world AI applications, a deep-dive into the CrewAI framework
Prerequisites
The teaching faculty for this course comprises the instructor, a supportive staff of teaching assistants, and a course coordinator. Together, they facilitate learning through close guidance and 1-1 sessions when needed.
- Core concepts and foundational definitions of AI Agents
- Why AI Agents matter: Core value proposition and industry significance
- Differences between traditional automation and agentic systems
- Detailed analysis of successful AI agent deployments
- Industry-specific use cases: Logistics, Healthcare, Customer Service, and more
- Common pitfalls and lessons learned
- Deep-dive into frameworks: CrewAI, LangGraph, AutoGen, PydanticAI, Google Agent DevelopmentKit, and more
- Comparative analysis and selection criteria
- Hands-on sessions and practical implementations
We will go through a guided reading of some of the foundational papers in this field
- Understanding MCP tools and ecosystem integration
- Designing effective MCP prompts, tools, and resources
- Interactive labs: MCP integration exercises
- Protocols overview, including Google’s A2A
- Designing robust communication mechanisms for agents
- Real-world implementation case studies
- Techniques in supervised fine-tuning (SFT) of Large Language Models (LLMs)
- Domain-specific adaptation strategies
- Practical fine-tuning labs
- Core RL concepts: rewards, policy iteration, value iteration
- Exploration vs. exploitation strategies
- Interactive RL exercises
- RL-based fine-tuning methods specific to agent models
- Performance optimization using RL
- Hands-on RL training in simulated environments
- Challenges and strategies in MARL
- Agent cooperation and competition dynamics
- Collaborative and competitive multi-agent systems labs
- Comprehensive agentic system development and presentations
- Emerging trends: interpretability, scalability, ethics
- Resources for continued learning and exploration
Teaching Faculty
Asif Qamar
Chief Scientist and Educator
Background
Over more than three decades, Asif’s career has spanned two parallel tracks: as a deeply technical architect & vice president and as a passionate educator. While he primarily spends his time technically leading research and development efforts, he finds expression for his love of teaching in the courses he offers. Through this, he aims to mentor and cultivate the next generation of great AI leaders, engineers, data scientists & technical craftsmen.
Educator
He has also been an educator, teaching various subjects in AI/machine learning, computer science, and Physics for the last 32 years. He has taught at the University of California, Berkeley extension, the University of Illinois, Urbana-Champaign (UIUC), and Syracuse University. He has also given a large number of courses, seminars, and talks at technical workplaces. He has been honored with various excellence in teaching awards in universities and technical workplaces.
Chandar Lakshminarayan
Head of AI Engineering
Background
A career spanning 25+ years in fundamental and applied research, application development and maintenance, service delivery management and product development. Passionate about building products that leverage AI/ML. This has been the focus of his work for the last decade. He also has a background in computer vision for industry manufacturing, where he innovated many novel algorithms for high precision measurements of engineering components. Furthermore, he has done innovative algorithmic work in robotics, motion control and CNC.
Educator
He has also been an educator, teaching various subjects in AI/machine learning, computer science, and Physics for the last decade.
Teaching Assistants
Our teaching assistants will guide you through your labs and projects. Whenever you need help or clarification, contact them on the SupportVectors Discord server or set up a Zoom meeting.
Kate Amon
Univ. of California, Berkeley
Kayalvizhi T
Indira Gandhi National Univ
Ravi Sati
Kalasalingam Univ.
Harini Datla
Indian Statistical Institute
Kunal Lall
Univ. of Illinois, Chicago
In-Person vs Remote Participation
Plutarch
Education is not the filling of a pail, but the lighting of a fire. “For the mind does not require filling like a bottle, but rather, like wood, it only requires kindling to create in it an impulse to think independently and an ardent desire for the truth.
Our Goal: build the next generation of data scientists and AI engineers
The AI revolution is perhaps the most transformative period in our world. As data science and AI increasingly permeate the fabric of our lives, there arises a need for deeply trained scientists and engineers who can be a part of the revolution.
Over 2250+ AI engineers and data scientists trained
- Instructors with over three decades of teaching excellence and experience at leading universities.
- Deeply technical architects and AI engineers with a track record of excellence.
- More than 30 workshops and courses are offered
- This is a state-of-the-art facility with over a thousand square feet of white-boarding space and over ten student discussion rooms, each equipped with state-of-the-art audio-video.
- 20+ research internships finished.
Where technical excellence meets a passion for teaching
There is no dearth of technical genius in the world; likewise, many are willing and engaged in teaching. However, it is relatively rare to find someone who has years of technical excellence, proven leadership in the field, and who is also a passionate and well-loved teacher.
SupportVectors is a gathering of such technical minds whose courses are a crucible for in-depth technical mastery in this very exciting field of AI and data science.
A personalized learning experience to motivate and inspire you
Our teaching faculty will work closely with you to help you make progress through the courses. Besides the lecture sessions and lab work, we provide unlimited one-on-one sessions to the course participants, community discussion groups, a social learning environment in our state-of-the-art facility, career guidance, interview preparation, and access to our network of SupportVectors alumni.
Join over 2000 professionals who have developed expertise in AI/ML
Become Part of SupportVectors to Inculcate In-depth Technical Abilities and Further Your Career.
