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Gen AI Course in Bangalore

This Gen AI Course in Bangalore is built for engineers and technical professionals who want deeper implementation skill, not surface-level AI familiarity. The program focuses on fine-tuning, RAG, AI agents, evaluation, and production-minded Gen AI builds for teams that need stronger technical credibility.

Build LLM Systems
From prompting to workflow design
Ship Grounded RAG
Retrieval, reranking, and citations
Work Across Modalities
Text, vision, and multimodal pipelines
Deploy More Credibly
Evaluation, tracing, and runtime thinking

Advanced Gen AI Training in Bangalore for Engineers

Live Technical Sessions

Classes are live, mentor-led, and structured. The point is not just access to GenAI content, but technical teaching, implementation clarity, and real discussion.

Built for Full-Time Engineers

The format works for professionals managing demanding roles across Bangalore's product teams, startups, GCCs, and engineering organizations without depending on offline attendance.

Deeper Technical Coverage

The program focuses on fine-tuning, RAG, AI agents, evaluation, and deployment as connected engineering work instead of isolated AI buzzwords.

Project Work You Can Defend

You build portfolio-ready work that is easier to explain in technical interviews, product conversations, and architecture reviews.

Learning Format
Live Online with Mentor-Led Sessions and Recordings
Course Duration
5 Months
Next Cohort starts
27 Apr, 2026

Gen AI Course in Bangalore: Technical Highlights

LLM and Prompt Workflow Design

Work through prompting patterns, structured outputs, chaining logic, tool use, and workflow design so LLM applications behave more predictably.

Retrieval, Grounding, and Evaluation

Build RAG systems with chunking, hybrid retrieval, reranking, citations, and evaluation loops that make quality easier to inspect and improve.

Multimodal and Agent Workflows

Go beyond text-only use cases with VLMs, multimodal pipelines, agent patterns, tool orchestration, and MCP-style interface thinking.

Serving, Evaluation, and System Reviews

Inspect traces, review failure paths, think about latency and cost, and move systems toward more credible deployment and evaluation patterns.

Main Course Page

Explore the Full Gen AI Syllabus

This Bangalore page gives you the city-specific view. To explore the complete Generative AI curriculum, tools, projects, and certification details, use the main course page.

No signup required — explore at your own pace

What you'll find on the main page

Complete Module View

See the full curriculum structure beyond the Bangalore-specific narrative.

Project Scope

Review the broader project mix, case studies, and capstone depth in one place.

Certification Details

Understand how the certificate fits into the overall program structure.

Flagship Program View

Use the main page when you want the full non-city version of the course.

Industry-Recognized CertificationLive Mentor-Led SessionsPlacement Assistance4.9 ★ Average Rating

Why Engineers Learn Gen AI in Bangalore

Bangalore remains one of India's strongest contexts for learning Generative AI because product teams, GCCs, research groups, and applied AI startups all push beyond basic prompting into systems that need to work in production.

For professionals working across product engineering, internal AI tools, enterprise platforms, copilots, search-backed assistants, and multimodal workflows, the useful shift is no longer just AI awareness. It is the ability to build grounded, reviewable, and deployable GenAI systems. That is why RAG quality, evaluation, tracing, and runtime thinking matter as much as model familiarity.

Why Engineers Choose This Gen AI Course in Bangalore

The difference is not just the list of tools. It is the focus on system quality, reviewability, and delivery.

Feature
Learning Format
School of Core AI

Live mentor-led sessions with recordings, structure, and technical guidance.

Other Institutes

Often a mix of videos, limited interaction, or unclear live support.

Feature
Curriculum Depth
School of Core AI

Covers LLMs, RAG, LangChain, agents, multimodal workflows, evaluation, tracing, and deployment thinking as one connected workflow.

Other Institutes

Often focuses only on prompting, Python basics, or a lighter overview of AI tools.

Feature
Projects & Case Studies
School of Core AI

Projects focus on prompt workflows, RAG, multimodal pipelines, agents, and explainable architecture choices.

Other Institutes

Projects often stay closer to mini demos and are harder to defend in serious interviews.

Feature
Trainers
School of Core AI

Mentor-led guidance focused on real implementation choices, failure modes, and technical tradeoffs.

Other Institutes

Teaching often stays at the concept or tool-demo level.

Feature
Mentorship
School of Core AI

Review support, mentor feedback, and help presenting project work more credibly.

Other Institutes

Support is often limited or not built around real technical review.

Feature
Working Professional Fit
School of Core AI

Designed for people who need strong teaching and technical access without offline attendance.

Other Institutes

Schedule and support quality are often not designed around serious full-time professionals.

Feature
Interview and Portfolio Value
School of Core AI

You leave with systems and tradeoffs you can explain clearly in interviews and project discussions.

Other Institutes

Learners often finish with examples that do not travel well into technical evaluation.

How Advanced Gen AI Training in Bangalore Works

01

Live Technical Sessions

Live classes focus on building real GenAI systems, not just slides. Concepts are taught alongside practical workflow design, system reasoning, and implementation tradeoffs.

02

Recordings and Flexible Learning

Sessions are recorded so working professionals can revisit architecture explanations, debugging walkthroughs, and implementation details when needed.

03

Build RAG, Fine-Tuning, and Agent Workflows

Progress through project work covering LLM applications, RAG systems, fine-tuning concepts, agent workflows, evaluation, and deployment-oriented implementation.

04

Architecture Reviews and Technical Feedback

Questions around architecture, tool choice, RAG quality, evaluation, and debugging get addressed through technical reviews rather than being left to self-study.

05

Technical Portfolio and Interview Reviews

Practice technical discussions around GenAI architecture, RAG design, evaluation, and system tradeoffs so your portfolio work is easier to defend.

06

Mentor Support for Advanced Builders

Get help with project storytelling, interview preparation, resume framing, and role mapping for technically demanding GenAI positions.

RAG, Fine-Tuning, and Agent Projects in Bangalore

You will leave with project work that looks like systems building, not just AI prompting.

Expect work across prompt workflows, grounded RAG, multimodal pipelines, evaluation harnesses, trace-aware debugging, and deployment-minded GenAI applications. The goal is to leave with projects you can explain in interviews, engineering discussions, and product reviews.

Technical Skills You Will Build in This Gen AI Course

01

Build Serious LLM Applications

Move from simple prompts into workflow design, structured outputs, chaining logic, tool use, and application patterns that are easier to maintain.

02

Work Across the Modern GenAI Stack

Build depth across LLMs, VLMs, retrieval systems, vector databases, multimodal workflows, agents, evaluation, safety, and deployment-oriented implementation.

03

Build Projects with Production Awareness

Implement end-to-end builds that include prompt and retrieval design, traces, evaluation, latency and cost thinking, and deployment patterns that go beyond notebook demos.

04

Explain Your Work More Credibly

Leave with a capstone, portfolio-ready projects, and clearer reasoning around model choice, RAG design, agent behavior, evaluation results, and deployment decisions.

Gen AI Course Syllabus and Roadmap in Bangalore

1

Weeks 1-2: Foundations

  • Python refresh, notebooks, and reliable prompting patterns
  • Tokens, embeddings, vector search, and structured outputs
2

Weeks 3-4: LLMs and VLMs

  • Model selection, serving choices, and runtime basics
  • Fine-tuning concepts, VLM basics, and document or OCR-oriented workflows
3

Weeks 5-7: RAG Systems

  • Chunking strategy, metadata, retrieval design, and hybrid search
  • Reranking, grounding, citations, semantic caching, and quality review
4

Weeks 8-9: Agents and Orchestration

  • LangChain, LangGraph, CrewAI, tool use, and retries
  • Memory, orchestration choices, and MCP-style workflow patterns
5

Weeks 10-12: Evaluation and Safety

  • DeepEval, RAGAS, review sets, and evaluation logic
  • Guardrails, safety policies, and red-teaming mindset
6

Weeks 13-16: Deployment and LLMOps

  • Tracing, observability, latency and cost thinking
  • Cloud deployment patterns, CI/CD basics, and production-minded release decisions

Gen AI Certification Course in Bangalore

Earn a verifiable certificate after completing the program and project reviews, with demonstrated work across LLM systems, RAG workflows, multimodal pipelines, evaluation, tracing, and deployment-oriented implementation.

Certificate of Completion

Issued by School of Core AI upon successful completion of the programme

Generative AI Learning Community in Bangalore

Learn with engineers, analysts, developers, and AI practitioners in live cohorts. The community value comes from mentor reviews, shared repos, mock interviews, and peer conversations that remain useful after class hours.

Engineer Peer Group in Bangalore

Live mentor access and recordings
Live mentor access and recordings
Peer learning and reviews
Peer learning and reviews
Shared repos and feedback loops
Shared repos and feedback loops
Mock interviews and prep groups
Mock interviews and prep groups
Career support and hiring signals
Career support and hiring signals
Learners and alumni work across product teams, consulting environments, GCCs, and enterprise AI groups in Bangalore and beyond.

Where Learners and Alumni Work

Generative AI Course Reviews in Bangalore

The most useful shift for me was moving beyond prompt demos into RAG design, evaluation, and trace-aware debugging. That made my project work much easier to explain as a real system.
RS
Rohit S.
GenAI Engineer
The course content was broad, but what mattered most was the structure. We were shown how to think about retrieval quality, tradeoffs, and system behavior instead of just learning tool names.
PM
Priya M.
Business Analyst
As someone moving deeper into Generative AI, I found the pacing practical. The program did a good job of breaking down complex topics without flattening the technical depth.
KN
Kavita N.
GenAI Engineer
Capstone reviews were strong. I got better at explaining model choices, RAG decisions, evaluation results, and failure cases instead of just showcasing final outputs.
RK
Rajesh K.
Applied AI Engineer

Companies Hiring Generative AI Talent in Bangalore

Google
Microsoft
Amazon AWS
Flipkart
Infosys
Wipro
TCS
Accenture
Cognizant
IBM
SAP Labs
Cisco
Oracle
Intel
Qualcomm
Bosch
Siemens
Capgemini
Deloitte
Tiger Analytics
Fractal Analytics
PhonePe
Swiggy
Meesho
Freshworks
AI Startups in Koramangala

Career Opportunities for Generative AI in Bangalore

Across Bangalore product teams, GCCs, research-heavy environments, and AI-first startups, the useful hiring signal is shifting toward people who can build systems that are grounded, reviewable, and deployable.

That makes skills like retrieval quality, multimodal design, evaluation, tracing, and rollout thinking more valuable than surface-level GenAI familiarity alone.

AI Engineer

Design end-to-end GenAI features with prompting, RAG, orchestration, evaluation, and safety guardrails that can actually survive product use.

Machine Learning Engineer

Build and deploy ML and LLM services, reason about latency and cost, and support the infrastructure and workflows behind production AI systems.

Data Scientist

Frame business problems, experiment with models, and increasingly work with GenAI tools for search, automation, summarization, and decision support workflows.

Research Scientist

Explore new architectures, fine-tuning methods, multimodal workflows, and evaluation techniques in research-oriented or frontier product teams.

AI Ethics / Safety

Support responsible AI efforts through safety reviews, bias checks, guardrails, evaluation policy, and deployment governance.

In-Demand Generative AI Skills in Bangalore

The shift in Bangalore is not just toward using LLMs. It is toward building GenAI systems that can be measured, improved, and integrated into real products and workflows.

1
RAG Architectures: Hybrid search, metadata filtering, scoring, reranking & RAG Fusion
2
LLM Serving & Inference: vLLM, TGI, Llama.cpp, and model quantization with GGUF
3
LangChain, LangGraph, CrewAI: Agents, workflows, retry loops, orchestration layers
4
Multimodal AI: Vision-language models (VLMs), document QA, captioning, OCR pipelines
5
Evaluation with DeepEval, RAGAS, and LLM-as-a-judge for generation quality & safety
6
Vector DBs: FAISS, Qdrant, Weaviate, Milvus + hybrid retrieval and versioned chunking
7
Cloud-native GenAI Deployments: Azure OpenAI, AWS Bedrock, GCP + CI/CD orchestration
8
LLMOps Fundamentals: Observability, guardrails, tracing with LangSmith, LangFuse, LangTrace
9
Speech + Audio + Multilingual Interfaces: Whisper, TTS, Indian languages, translation & voice agents

Compare Gen AI Learning Paths

If you are comparing broad Generative AI learning with adjacent specialization paths, start here.

Generative AI Course Fee in Bangalore

Single transparent fee covering complete training, real-world projects, certification and placement support. EMI and part-payment options are available with our counsellor.

Total Course Fee
64,999

Final fee, EMI plans and any ongoing offers will be confirmed by your counsellor based on your batch, mode and payment preference.

Generative AI Course in Bangalore FAQs

This Generative AI course is delivered live online with mentor-led sessions and recordings. Learners in Bangalore can join from home or work without depending on classroom attendance.