AI Accelerator Program
Building & EvaluatingAgentic AI Systems
Alessandro Romano
Senior Data Scientist
Kuehne+NagelDipanjan Sarkar
Head of AI & Community
Analytics VidhyaRaghav Bali
Principal Data Scientist
Delivery Hero
About the Course
Building & Evaluating Agentic AI Systems is a practical, end-to-end program focused on designing, building, deploying, monitoring and evaluating Agentic AI systems that work reliably in real-world settings.
With live instructor-led sessions, 10 Guided Projects and 5 Mini Project Assignments, you will learn how to work with large language models (LLMs) and add in custom context with prompt engineering and retrieval-augmented generation (RAG). Next, you will focus on designing and building single-agent and multi-agent systems using industry standard frameworks and languages including Python, LangGraph & LangChain.
You will also learn standard design patterns including routing, tool-use, planning, reflection, multi-agent as well as other important components including context engineering, memory and model context protocol (MCP) to optimize and build effective Agentic AI systems.
Finally you will learn how to enable observability (AgentOps) focusing on evaluation, tracing and monitoring using methodologies and frameworks like LLM-as-a-Judge, agentic evals & LangSmith.
Prerequisites
You should be comfortable writing code in Python. Prior exposure to Generative AI is helpful but not required. What matters most is that you can code and understand core programming concepts.
Tools & Platforms
- Python (Jupyter Notebooks using Google Colab)
- LangChain, LangGraph
- Gemini and OpenAI APIs (OpenAI keys would be provided for the duration of the course when needed)
- Tavily Search API, Chroma DB, Ragas, DeepEval, Opik, LangSmith
- ChatGPT, Gemini, Google AI Studio, Claude
Instructors
Alessandro Romano is a Senior Data Scientist, AI Engineer, and international speaker with a strong focus on building reliable, production-ready AI systems. With over 10 years of experience across mobility, logistics, and digital platforms, he has led and contributed to projects in dynamic pricing, demand forecasting, fraud detection, and large-scale experimentation systems.
In recent years, Alessandro has specialized in agentic AI and LLM-based architectures, designing multi-agent systems for tasks such as automated code review, decision support, and intelligent workflow orchestration. His technical expertise spans Python, modern ML stacks, vector databases, and cloud-native deployment of AI services.
Dipanjan Sarkar is currently the Head of Artificial Intelligence & Community, Analytics Vidhya. He is also a published Author, and Consultant, boasting a decade of extensive expertise in Machine Learning, Deep Learning, Generative AI, Computer Vision, and Natural Language Processing. His leadership spans Fortune 100 enterprises to startups, crafting end-to-end AI products and pioneering Generative AI upskilling programs.
A seasoned advisor, Dipanjan advises a diverse clientele, from Engineers and Architects to C-suite executives and PhDs, across Advanced Analytics, AI Strategy & Development. Recognitions include "Top 10 Data Scientists in India, 2020," "40 under 40 Data Scientists, 2021," "Google Developer Expert in Machine Learning, 2019," and "Top 50 AI Thought Leaders, Global AI Hub, 2022,", Google Champion Innovator title in Cloud AI\ML, 2022 alongside global accolades including Top 100 Influential AI Voices in LinkedIn.
Raghav Bali is a Principal Data Scientist at Delivery Hero, a leading food delivery service headquartered in Berlin, Germany. With 13+ years of expertise, he specializes in research and development of enterprise-level solutions leveraging Machine Learning, Deep Learning, Natural Language Processing, and Recommendation Engines for practical business applications.
Besides his professional endeavors, Raghav is an esteemed mentor and an accomplished public speaker. He has contributed to multiple peer-reviewed papers and authored more than 8 books, including the second edition of his well received book Generative AI with Python and Pytorch. Additionally, he holds co-inventor credits on multiple patents in healthcare, machine learning, deep learning, and natural language processing.
Who Should Enroll
- Data Scientists & Analysts
- Machine Learning, Deep Learning & Generative AI practitioners
- Data, Business & Technology Professionals
- GenAI & Agentic AI enthusiasts
- STEM Graduates
Data Professionals & Developers
Seeking hands-on Agentic AI experience with LangGraph & LangChain
ML & GenAI Practitioners
Strengthening portfolios with end-to-end projects
Business Professionals
Applying GenAI & Agentic AI to real-world business problems
Key Features
Live Classes
5 hours/week
Projects
10 Guided Projects
Assignments
5 Mini-Project Assignments
Cohort Experience
Discussion forum
Office Hours
Weekly discussions & QA
Recordings
Lifetime access
Resources
All session materials
Certification
Course completion certificate
Support & Trust
7-day money-back guarantee, T&C
Course Curriculum
12 Live Sessions • 30 Learning Hours • 10 Guided Projects
Week 1Essentials of Generative AI & Prompt Engineering
14–20 Feb 2026
Essentials of Generative AI & Prompt Engineering
14–20 Feb 2026
14 Feb · 8-10:30 PM IST
Introduction to Generative AI & Agentic AI
- Learn core Generative AI, LLM, RAG, and Agentic AI concepts
- See real-world demos on popular LLM platforms
- Get started with key frameworks and environment setup
15 Feb · 8-10:30 PM IST
Prompt Engineering & LangChain Essentials
- Learn prompt engineering and LangChain basics
- Apply advanced prompting techniques hands-on
- Work with multimodal prompts across formats
- Mini Project: Research & report generation using prompt engineering
18 Feb · 8–9 PM IST
Week 1 Recap & Discussion on Mini Project 1 Solution (Optional)
Join in to discuss and ask any questions on the content or projects covered in Week 1. We will also release the solution code for Mini Project 1 Assignment and discuss it briefly during this time
Recordings available post-session
Capstone Projects
Multi-Agent Research Assistant
Build an intelligent research system with specialized agents for web search, data analysis, and report generation using LangGraph. Build an intelligent research system with specialized agents for web search, data analysis, and report generation using LangGraph.
Frequently Asked Questions
A short, live, cohort-based, instructor-led program designed to upskill professionals in AI through hands-on learning. You’ll learn live with a small group, interact directly with the instructor, and work on real-world projects rather than watching pre-recorded videos.
It’s fully live. All sessions are conducted in real time on Zoom, with fixed schedules and active participation expected.
The program lasts for 4-6 weeks, with 3-5 hours of commitment per week, making it manageable alongside your regular job.
Yes. You’ll receive a certificate of completion once you’ve successfully completed all assignments. The certificate reflects your hands-on skills in practical AI applications.
Yes, the program is designed to teach practical, real-world skills that can be immediately applied to your current job or projects.
You will have access to weekly office hours where you can ask the instructor questions and a dedicated community space for peer interactions and doubt clearing.
If you miss a live session, you will have access to the recorded session, which you can watch at your convenience. However, we encourage you to attend live to maximize engagement and learning.
Yes, we offer a 7-day money-back guarantee. The 7-day period starts from the first day your cohort starts. If you’re not satisfied with the program during the first 7 days, you can request a full refund by contacting our support team.