Hands-on Learning Environment
Our bootcamp provides a collaborative space where students learn by doing, with expert guidance.
Expert-Led Sessions
Learn directly from industry professionals with years of experience in AI and machine learning.
Collaborative Projects
Work together on real-world problems and build your portfolio while learning.
Interactive Discussions
Engage in meaningful conversations about AI concepts and applications.
Practical Coding Sessions
Develop your skills through hands-on coding exercises and real-time feedback.
Problem-Solving Focus
Learn to approach complex AI challenges with structured problem-solving techniques.
Join Our Community
Become part of a growing network of AI professionals and enthusiasts.
Advance your AI skills
Master cutting-edge generative AI techniques and stay relevant with workforce trends
Learn hands-on, in-depth
Balanced in-person lectures and labs using sponsored LLM API keys
Immediate impact
Create a proof-of-concept AI workflow or RAG chatbot addressing a real business need in your organization
Who Should Attend?
The Forward-Thinking Data Analyst
Background:
Works with large datasets, performs data cleaning and reporting.
Goal:
Use NLP and generative AI to derive deeper insights, automate repetitive tasks, and enhance reporting with natural-language summaries.
The Aspiring AI Engineer
Background:
Familiar with Python and basic machine learning concepts.
Goal:
Master prompt engineering, fine-tune language models, and build end-to-end solutions that incorporate RAG for more accurate, context-aware responses.
The Tech-Savvy Consultant
Background:
Advises clients on technology adoption, change management, or operational efficiency.
Goal:
Gain hands-on practice in developing AI-driven case studies—enabling advanced client solutions, faster prototyping, and better strategic recommendations.
Learn, Build, Deploy in 4 Sessions
Foundations of Language Models, Prompt Engineering, and Natural Language Processing
Key Topics
- How LLMs process and generate text
- Foundational NLP concepts and preprocessing techniques
- Creating and refining prompts tailored to specific tasks
- Evaluating how variations in prompts affect model responses
- NLP tools like NLTK and spaCy for text manipulation
- Vector embeddings for text representation
Introduction to Retrieval-Augmented Generation
Key Topics
- RAG fundamentals and how it enhances LLMs
- Comparing standard LLM outputs with RAG-enhanced ones
- RAG architectures and design principles
- Advantages and limitations of RAG in real-world use
- Document chunking strategies for retrieval
- Embedding models and vector databases in RAG
Privacy, Security, and Domain-Specific AI Prototyping
Key Topics
- Privacy and security risks in RAG-based systems
- Best practices for protecting sensitive data
- Compliance concerns with enterprise and regulated data
- Detecting and mitigating hallucinations and model misuse
- Designing domain-specific AI prototypes using RAG and LLMs
Prototype Development, Demo, and Wrap-Up
Key Topics
- Finalizing and refining your domain-specific AI prototype
- Preparing clear and engaging presentations and live demos
- Communicating the relevance and impact of your solution
- Receiving constructive feedback from peers and stakeholders
- Reflecting on key takeaways and future AI applications
Learn from AI-CCORE Experts
Dr. Prashanti Manda
Lead Instructor
Brings expertise in AI research and development with a focus on practical applications and implementation.
Dr. Mahadevan Subramaniam
Director
Chair of Computer Science Department with extensive experience in AI research and industry applications.
Dr. Victor Winter
Deputy Director
Expert in software correctness and generative AI with years of teaching and industry experience.
P Ashish Kumar
AI Platform Engineer
Specializes in developing and optimizing AI platforms with expertise in machine learning infrastructure and deployment.
Vijayaragupathy Vijayaragunathapandian
AI Engineer
Focuses on cutting-edge AI research, specializing in natural language processing and deep learning techniques.
Upcoming Bootcamp Cohorts
AI Bootcamp
$1,000
Employer Reimbursement: Many employers cover professional development. Ask about our employer documentation.
What Our Participants Say
"The clear explanation of RAG architectures was excellent. The Langflow workshops effectively focused on practical principles, enabling hands-on learning."
"The detailed coverage of RAG approaches and chunking strategies, with emphasis on their functional differences, was valuable. The well-explained demonstrations and concept-focused exercises enhanced the learning experience."
"The Langflow build template was highly effective. The presentation was informative and created valuable opportunities to learn about various AI applications from other participants."