Best Ai and GenAi Training & Job placement In Marathahalli Bengaluru
Generative AI Foundations and Applications Course Description
Generative AI is the foundation for building AI-powered applications. This course helps learners
understand how LLMs work, how prompts guide outputs, how embeddings represent meaning, and
how modern GenAI applications are designed and evaluated
Realistic outcome: By the end of this course, learners will be able to build practical
prompt-based applications, chatbot prototypes, semantic search tools, and RAG-based
document Q&A systems
Who Should Enroll ?
Students and graduates Build a practical AI project portfolio with guided labs and assignments.
Working professionals Learn how GenAI can be applied to business, productivity, and knowledge workflows.
Developers Use APIs, frameworks, and backend patterns to build LLM-powered applications.
Data analysts and tech learners Apply semantic search, document processing, and RAG to real information problems.
Learning Outcomes
- Understand AI, ML, Deep Learning, GenAI, LLMs, transformers, tokens, context windows, and embeddings.
- Design prompt-based AI workflows using role prompts, examples, constraints, and structured outputs.
- Use LLM APIs such as OpenAI, Gemini, Claude, and AWS Bedrock for application development.
- Build AI text summarizers, chatbots, semantic search apps, and document Q&A systems.
- Create Retrieval-Augmented Generation applications using vector databases and externaldocuments.
- Evaluate GenAI outputs for relevance, grounding, consistency, and usability.
Get Enroll Now
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Projects Learners Will Build
| Project | Objective | Skills Covered | Expected Output | Deployment Possibility |
|---|---|---|---|---|
| Prompt Engineering Portfolio | Create reusable prompt templates | Prompt design, structured outputs, evaluation | Documented prompt portfolio | GitHub |
| AI Text Summarizer | Summarize long-form content | LLM APIs, prompt tuning, UI flow | Working summarizer app | Streamlit or FastAPI |
| AI Chatbot | Build a conversational assistant | Chat flow, response handling, API integration | Interactive chatbot | Web app |
| Semantic Search App | Search documents by meaning | Embeddings, similarity search, indexing | Searchable document tool | Local or cloud |
| Document Q&A System | Answer questions from uploaded files | Chunking, retrieval, RAG | Document assistant | Streamlit/FastAPI |
| RAG Knowledge Assistant | Create a grounded knowledge assistant | Vector DB, retrieval tuning, citations | RAG prototype | AWS or container deployment |
Highly rated on Google
4.9/5
Course Duration
8 weeks
Learning Mode
Offline
Placement's*
100%
Certificate Positioning
Participants who complete the course requirements will receive a certificate of completion for Generative AI Foundations and Applications. The certificate reflects hands-on training in LLM fundamentals, prompt engineering, embeddings, vector databases, document Q&A, RAG workflows, and practical GenAI application development.
Final course outcome: Learners complete this course with a practical GenAI project portfolio and the foundation required for advanced Agentic AI systems.