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Generative AI Course in Bangalore

  • BANGALORE'S ENTERPRISE GENAI PROGRAM | 2026 BATCH OPEN

Generative AI Course in Bangalore Built for Real Enterprise Outcomes

Master LLMs, RAG pipelines, LangChain, and Agentic AI across 18 production-focused modules. Build 4 deployable portfolio projects. Graduate with the skills that Bangalore’s GCCs and enterprise AI teams are actively hiring for right now.

  • Trainers with 10+ Years of Industry Experience
  • Hands-On Real-Time AI Projects
  • 90-Day Generative AI Training Program
  • Online and Classroom Training Available
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Generative AI Course in Bangalore – Batch Details

Below are the complete training details for the Generative AI Certification Course at
VKNOWTECH AI, designed for students and professionals who want to build practical skills
in modern AI technologies.

Course DetailsInformation
Course NameGenerative AI Master Training Program
Trainer NameJai Surya
Trainer Experience10+ Years Industry Experience
Next Batch Date20 May 2026
Batch TimingsMorning & Evening
Training ModeOnline & Offline (Instructor-Led)
Course Duration90 Days (3 Months)
Demo Class20 May 2026 – Free Demo Session
Contact Number+91 90100 91700
Email Addressadmin@vknowtech.ai

The Generative AI Skill Gap: Why Bangalore IT Professionals Must Upskill Now

Every quarter, Bangalore companies post more GenAI engineering roles than the city can fill. AI-
related job postings in India have grown over 40% in the last 12 months, and the professionals
being passed over are not the ones without AI awareness. They are the ones with awareness but
no applied skill.

The gap between knowing what ChatGPT is and knowing how to build a production-grade RAG
pipeline inside a Workday HCM environment is enormous. Closing that gap is precisely what this
program delivers.

Stop learning ChatGPT in a vacuum. The Bangalore market pays for engineers who can deploy Agentic AI inside enterprise firewalls, not for professionals who can write better prompts in a browser tab. If your current upskilling plan stops at prompt engineering, you are not upskilling. You are treading water.

If you are a Workday consultant, SAP professional, business analyst, or IT manager watching AI reshape your domain from the outside, this is the point where you stop watching.

See exactly what changes for your career

Book a free 30-minute demo session with our team and walk through the curriculum, the projects, and the placement outcomes.

Book Free Demo Class →

Build 4 Enterprise-Grade LLM Pipelines
Including a Live Workday HR Chatbot

This is not a course that ends with a certificate PDF and three weeks of API tutorials. You
graduate with four portfolio-ready, deployable GenAI projects that you can walk into any
technical interview and defend line by line.

Every project is reviewed by active AI engineers. Not teaching assistants following a rubric.
Engineers who have shipped production systems.

  • PROJECT 1

LLM-Powered Enterprise Document Q&A System

Build a full RAG pipeline with document splitting, vector store integration, hybrid retrieval, and cited responses. Designed for enterprise knowledge management use cases.

  • PROJECT 2

Multi-Step Agentic AI Workflow with Tool Integration

Design a ReAct agent that reasons, selects tools, executes multi-step tasks, and manages state. Built using LangChain’s full agent framework.

  • PROJECT 3

Domain-Specific Fine-Tuned Language Model

Fine-tune a base LLM on domain-specific data, configure tokenizers and GPU settings, and deploy via OLLAMA with performance optimization and quantization.

  • CAPSTONE

Live Workday HR Chatbot on a Production RAG Backend

The headline deliverable. A fully functional Workday HCM-integrated chatbot using LangChain, a vector store, and an OpenAI or local LLM backend. This is exactly what Bangalore’s enterprise AI teams are hiring for right now.

From Python Foundations to LLMOps: The
Full 18-Module Curriculum

The program begins at Python fundamentals and progresses to production deployment.
Every module builds on the last. There are no isolated rabbit holes, no disconnected tool
tutorials. It is one continuous engineering pathway.

Module 1: Getting Started with Python
  • Understanding Programming and Coding Basics
  • Overview of Python Libraries, Modules, and Web Frameworks
  • Exploring Different Flavors of Python
  • What Makes Python Powerful? (Use Cases and Advantages)
  • Comparing Python’s Syntax with Other Programming Languages
  • Setting Up the Python Environment and IDE Installation
  • Utilizing the print Statement and Code Comments
  • Deep Dive into Python Data Types and Structures
  • Keyword Fundamentals and Variable Declaration
  • Type Casting and Conversions
  • Handling Standard Input and Output
  • Python Operators:
    • Arithmetic and Assignment Operators
    • Comparison and Logical Operators
    • Identity and Membership Operators
    • Advanced Output Formatting
  • Conditional Statements:
    • Understanding Python Indentation Rules
    • if, elif, and else constructs
    • Nested Conditionals and Shorthand Syntax
    • Real-world Conditional Examples
  • Iterative Statements (Loops):
    • The for Loop and while Loop Mechanics
    • Nested Looping Structures
    • Practical Examples of Iteration
  • Jump Statements:
    • Managing Loop Control with break, continue, and pass
  • String Manipulation: Object Basics, Splitting/Joining, Formatting, and Built-in Methods
  • Mastering Lists: Core Concepts, List Methods, Implementing Stacks & Queues, and List Comprehensions
  • Understanding Tuples: Creation, Built-in Functions, and Tuple Operations
  • Working with Sets: Set Basics, Mathematical Set Operations, and Relevant Functions
  • Dictionaries: Key-Value Mapping, Dictionary Functions, and Built-in Operations
  • How to Define and Invoke Functions
  • The return Statement vs. Standard Printing
  • Managing Parameters and Arguments (Keyword & Arbitrary Arguments)
  • Creating User-Defined and Nested Functions
  • Practical, Real-World Function Applications
  • Classes and Objects: Defining Classes, Instantiating Objects, and Real-World Modeling
  • Exploring the __init__, self, and super() Keywords
  • Inheritance Models: Single, Multiple, Multilevel, and Hierarchical Inheritance
  • Polymorphism: Implementing Method Overloading and Overriding
  • Encapsulation: Managing Public, Private, and Protected Access Modifiers
  • Data Abstraction: Working with Abstract Base Classes (ABC) and Abstract Methods
  • Introduction and Installation of NumPy
  • Working with the N-dimensional Array (ndarray)
  • Array Creation, Data Types, and Attributes
  • Indexing, Slicing, and Advanced Indexing Techniques
  • Array Broadcasting and Iteration
  • Array Manipulation and Splitting
  • Core NumPy Functions: Binary, String, Mathematical, Statistical, and Arithmetic Operations
  • Sorting, Searching, Counting, and Byte Swapping
  • Matrix Libraries and Linear Algebra Fundamentals
  • Pandas Setup and Architecture overview
  • Understanding Pandas Series, DataFrames, and Panels
  • Core Functionalities and Descriptive Statistics
  • Data Reindexing, Iteration, and Sorting
  • Handling and Cleaning Text Data
  • Data Selection, Filtering, and Indexing
  • Advanced Pandas Features: Window Functions, Date/Time Operations, Timedeltas, and Categorical Data
  • File Input/Output (I/O) Tools and Basic Data Visualization via Pandas
  • Introduction to Matplotlib
  • Crafting Visual Narratives from Data
  • Basic Statistics:
    • Descriptive vs. Inferential Statistics
    • Variable Types, Measurement Scales, and Sampling Techniques
    • Frequency Distributions, Bar/Pie Charts, Box Plots, and Histograms
    • Central Tendency (Mean, Median, Mode) and Dispersion (Variance, Standard Deviation)
    • Outlier Detection, Skewness, Normal Curves, and Z-scores
  • Probability Theory:
    • Probability Basics, Addition, and Multiplication Rules
    • Permutations and Combinations
    • Discrete/Continuous Random Variables and Probability Distributions
  • Advanced Statistics:
    • Binomial and Normal Distributions
    • Correlation Analysis (Pearson & Spearman)
    • Central Limit Theorem and Confidence Intervals
    • Hypothesis Testing (Null/Alternative Hypotheses, Type I & II Errors, One/Two-Tailed Tests)
  • CPU vs. GPU architecture for Data Processing
  • Supervised vs. Unsupervised Learning (Classification, Regression, Clustering)
  • Model Evaluation Metrics and Understanding Errors
  • Exploring ML Frameworks (Scikit-Learn, TensorFlow, Keras)
  • Exploratory Data Analysis (EDA)
  • The Bias-Variance Tradeoff
  • Linear Regression:
    • Mathematical Core and Scratch Implementation
    • Building Models with Scikit-Learn
    • Calculating Errors: Mean Squared Error (MSE), Absolute Error
  • Logistic Regression:
    • Math and Scratch Implementation
    • Scikit-Learn Integration
    • Classification Metrics: Accuracy, Precision, Recall, F1-Score
  • Decision Trees:
    • Architecture (Roots, Internal Nodes, Leaves) and Splitting Criteria (Gini, Entropy, Info Gain)
    • Algorithms (ID3, CART, C4.5/C5.0)
    • Overfitting Prevention (Pre/Post Pruning)
    • Handling Missing Values and Categorical Data
    • Evaluating via Confusion Matrix and ROC/AUC curves
  • Random Forests:
    • Ensemble Learning (Bagging, Boosting, Stacking)
    • Architecture, Bootstrapping, and Feature Randomness
    • Out-of-bag (OOB) Estimation and Feature Importance
    • Hyperparameter Tuning and Bias Mitigation
  • Core Terminology: Corpus, Tokens, and N-grams
  • Tokenization Techniques (Whitespace, Regex)
  • Text Normalization (Stemming vs. Lemmatization)
  • Part-of-Speech (POS) Tagging
  • Embeddings: One-hot Encoding vs. Word Embeddings (Word2Vec, GloVe), Positional Embeddings, and Subword Tokenization (BPE).
  • Encoder Architecture: Self-Attention Mechanisms, Layer Normalization, and Feed-Forward Networks.
  • Decoder Architecture: Masked Self-Attention, Contextual Understanding, and Autoregressive Generation.
  • The “Attention Is All You Need” Paper: Analyzing the 2017 breakthrough, overcoming RNN/LSTM limits, and understanding the foundation of modern models like BERT and GPT.
  • Core Structure and Components of Effective Prompts
  • Strategies: Zero-shot, Few-shot, and Chain-of-Thought Prompting
  • Utilizing Prompt Templates and Variables
  • Testing, Iteration, Best Practices, and Avoiding Common Pitfalls
  • Framework Overview, Installation, and Architecture (Models, Prompts, Chains, Agents)
  • Text Processing: Summarization, Sentiment Analysis, Translation, and Content Generation
  • Memory Management: Buffer, Summary, Window, and Entity Memory
  • LLM Chains: Sequential, Router, and MapReduce Chains
  • RAG & Question-Answering: Vector Stores, Embeddings, Document Splitting, and Context Citing
  • Chatbot Development: Conversation Flow, Persona Customization, and Fallback Handling
  • AI Agents: ReAct Agents, Tool Integration, and State Management
  • Evaluating Responses, A/B Testing, and Cost Optimization
  • Detailed breakdown of API structures, costs, limits, pros/cons, and Fine-Tuning for:
    • OpenAI Models
    • Meta Llama
    • Anthropic Claude
    • DeepSeek
  • Downloading and Running Local Models
  • Environment Setup, Tokenizers, and GPU Configuration
  • Terminal Usage, CLI Prompts, and Tuning Parameters (Temperature, Top-p)
  • Python/Transformer API Integration
  • Performance Optimization and Model Quantization
  • Deployment Best Practices: Error Logging, API Security, Scaling, and Production Considerations

Get the complete module breakdown

Request the full 18-module curriculum PDF with project briefs, tools list,
and weekly session plan.

Download Full Curriculum →

VKNOWTECH AI vs Generic AI Courses: The
Enterprise Integration Advantage

Most Generative AI courses in Bangalore teach you to call the OpenAI API from a Jupyter
notebook, walk you through pre-built LangChain tutorials, hand you a certificate, and call
it job training. That is not how enterprise AI works.

VKNOWTECH AI is the only training institute in Bangalore with native enterprise ERP expertise
embedded into its GenAI curriculum. Our instructors have deployed LLM-based
automation tools inside live Workday HCM and Workday Finance environments.

A generic AI certificate will not save your job. Applying LLMs to your
specific domain, whether that is Workday, SAP, or Oracle, is what
makes you irreplaceable. Domain specificity is the moat. Generic
certificates are noise.

Ready to see the difference first-hand?

Join a live demo class and experience the enterprise-first teaching approach before you commit to enrollment.

Join a Live Demo Session →

Who Is Teaching You? Meet Our Active Enterprise AI Architects

A course that affects your career trajectory and your financial future should be taught by people who are currently working in the field. Not people who last deployed an AI system three years ago.

VKNOWTECH AI’s instructors are active AI solutions architects and enterprise technology consultants. They have implemented RAG pipelines for enterprise data retrieval, built Agentic AI workflows for HR and finance process automation, and fine-tuned domain-specific models for Indian enterprise environments.

They teach from production logs, deployment post-mortems, and the hard-won knowledge you only get from breaking things in real environments and fixing them under deadline pressure. Every concept in this curriculum has been tested against a real client problem.

"When I enrolled, I had seven years of Workday HCM configuration experience and zero Python. I left with a RAG-based Workday document retrieval system on GitHub, a fine-tuned model trained on HCM policy documentation, and a job offer within 11 weeks of completing the course."

Raghav S.

Former Workday HCM Consultant now AI Solutions Engineer at a Bangalore GCC

Who Is This Generative AI Course
in Bangalore Designed For?

This program is built for professionals who want to apply Generative AI inside their
specific domain. Not for people looking for a surface-level AI awareness course that
checks a box on their LinkedIn profile.

Workday HCM and Finance Consultants

Automate workflows using LLMs and position yourself as the AI-native professional that every enterprise implementation team needs in 2026.

Software Developers and IT Professionals

Move from traditional development into AI engineering roles that pay two to four times more. The transition requires real deployed systems, not just course completions.

Business Analysts and Data Professionals

Go beyond dashboards. Start delivering AI-powered decision systems that make you central to your organisation's AI adoption, not peripheral to it.

Fresh Graduates Targeting AI Engineering Roles

Competing in Bangalore's entry-level AI market requires a portfolio, not just a degree. Four real projects backed by a GenAI certification is how you stand out.

Non-Technical Managers in HR, Marketing, and Operations

You need enough depth to lead AI adoption inside your organisation without being dependent on external consultants for every decision.

Can a Non-Coder or Business Professional Without a Technical Background Join This Program?

Yes. Module 1 starts from programming basics and Python environment setup. You do not need prior coding experience, a data science background, or a computer science degree to enroll.

The progression is deliberate and tested. By Module 6 you are writing object-oriented Python. By Module 11 you are building Machine Learning models. By Module 16 you are deploying LangChain-based chatbots. Every step is structured to build on the last.

Not sure if this course fits your background?

Book a free 30-minute call with our admissions team for an honest assessment of where you will be after completing the program.

Discuss Placements

The ROI of Upskilling: Why Enterprise GenAI
Roles Command Rs 18L to Rs 28L in
Bangalore

A Generative AI Engineer with enterprise integration experience in Bangalore is currently
one of the rarest and most compensated profiles in the city’s tech market. The salary data
from our alumni and from Bangalore’s active job postings is consistent across role types.

The credential alone will not get you there. The portfolio, the deployed projects, and the
ability to defend your technical choices in an interview are what close the offer. The
professionals who leave with real portfolio projects get hired. The ones who leave with
just a certificate go back to job portals.

Weekend and Evening GenAI Batches for
Bangalore Working Professionals

The biggest reason Bangalore professionals do not finish AI courses is simple: the course
was designed for someone who does not have a full-time job. VKNOWTECH AI builds its
schedule around your life, not the other way around.

All three formats include the same mentor-led project reviews, the same curriculum, and the same
certification pathway. You are not getting a second-class version of the course because you chose
flexibility.

  • WEEKEND BATCH

Saturday and Sunday

3 hours per session. Designed for professionals who cannot afford weekday commitments. 16-week completion timeline.

  • WEEKDAY EVENING

Mon, Wed, Fri | 7 PM to 9 PM

For professionals who want to complete faster without sacrificing depth. Finished in approximately 12 weeks.

  • SELF-PACED

On Your Own Schedule

Access all recorded sessions at your own pace with weekly mentor check-ins and a dedicated WhatsApp support group.

Next batch starts soon

Seats in each cohort are capped at 20 to maintain mentor quality.Check current availability for your preferred batch format.

Check Batch Availability →

What Is the Total Fee for the Generative AI Course and Are EMI Options Available?

The complete program fee is communicated transparently during your free demo session. It includes everything: the full 18-module curriculum, all project reviews, the Generative AI certification, and 6 months of placement support.

EMI options are available at zero processing cost through partner financial institutions. Early enrollment discounts apply to the current batch. There is no hidden fee for the recorded session library, the WhatsApp mentor group, or the GitHub portfolio review session.

We do not lock pricing behind inquiry forms to manufacture urgency. You will see the full fee structure in your first conversation with our team, alongside all EMI options. The goal is for you to make an informed decision, not a pressured one.

Get the full fee breakdown and EMI options

Request the complete pricing sheet along with the batch schedule and current availability.

Get Full Fee Details →

Which Tools and Technologies Will You
Master Inside This Training Program?

This is the complete production stack you will work with across the 18 modules. Every tool
listed is used in a hands-on project context, not a demo walkthrough.

  • PROGRAMMING & DATA
  • Python 3.x
  • NumPy
  • Pandas
  • Matplotlib
  • Scikit-Learn
  • Keras
  • Pandas
  • NLP & DEEP LEARNING
  • NLTK
  • Hugging Face
  • Word2Vec
  • BERT
  • GPT Architecture
  • BPE Tokenization
  • GENAI FRAMEWORKS
  • LangChain
  • OpenAI API
  • Anthropic Claude
  • Meta Llama
  • DeepSeek API
  • RAG & VECTOR SYSTEMS
  • Vector Stores
  • Embedding Models
  • RAG Pipelines
  • Hybrid Retrieval
  • Document Splitting
  • AGENTIC AI
  • ReAct Agents
  • Tool Integration
  • State Management
  • Multi-Step Workflows
  • MCP Interfaces
  • LOCAL LLMS & OPS
  • OLLAMA
  • Model Quantization
  • GPU Setup
  • API Security
  • Deployment
  • Error Logging

How 50 ERP and Workday Professionals Transitioned to AI Engineering Roles

When a Workday HCM implementation consultant with zero Python experience enrolled in our first enterprise GenAI cohort, he left with a RAG-based Workday document retrieval system, a fine-tuned model trained on HCM policy data, and a job offer as an AI Solutions Engineer at a Bangalore GCC within 11 weeks of completing the course.

That outcome is not an exception. It is the repeatable result for domain professionals who pair deep enterprise knowledge with applied LLM engineering skills. Generic freshers compete on volume. Domain professionals who add GenAI skills compete on irreplaceability.

Across our cohorts, professionals from Workday, SAP, Oracle, and traditional IT backgrounds have moved into AI-adjacent roles. The salary uplift ranges from 40% to over 100% for those making a full title transition.

Talk to an alumni from your domain

Request a connection with a VKNOWTECH AI alumni from a Workday, SAP, or IT background similar to yours before you enroll.

Request Alumni Refrence →

7 Most Asked Questions About the Generative AI
Course in Bangalore

The complete Data Science and Generative AI program runs across 18 modules, typically completed in 12 to 16 weeks depending on your batch format. Weekend batches run 16 weeks. Evening batches finish in approximately 12 weeks. Every format covers the identical curriculum with no shortcuts. Your learning pace does not compromise the depth of the program.

No prior coding experience is required. Module 1 starts from programming basics and Python environment setup. By Module 6 you are writing object-oriented Python. The curriculum is sequenced to take business professionals, domain consultants, and complete beginners to production-level GenAI development without skipping foundational logic.

VKnowTech is the only institute integrating Workday HCM and enterprise ERP context into GenAI training. Competitors teach generic LLM prompting and API calls. VKNOWTECH AI graduates build real enterprise chatbots, RAG pipelines, and Agentic AI systems deployable inside actual corporate environments. That domain specificity is the differentiator that converts training into a job offer.

Enterprise GenAI Engineers with RAG, LangChain, and Agentic AI skills are commanding Rs 12L to Rs 28L packages in Bangalore’s current market. Domain professionals adding GenAI to Workday or SAP expertise are seeing 40% to 100% salary uplift. Your outcome depends on portfolio quality, prior experience, and whether you complete the placement support program fully.

Yes. All three batch formats, including weekend, evening, and self-paced, are delivered live online with full recorded session access. Mentor reviews, portfolio feedback, and placement support are all conducted digitally via WhatsApp, Zoom, and GitHub. You do not need to commute or attend any offline session to complete the program.

You receive an industry-recognized Generative AI certification from VKNOWTECH AI confirming proficiency across LLMs, RAG, Prompt Engineering, LangChain, and enterprise AI deployment. The certification is backed by your GitHub portfolio of four real deployed projects, which carries significantly more weight in technical interviews than a standalone certificate document.

Yes. Six months of structured placement support is included, covering AI-role-specific resume reviews, mock technical interviews with active GenAI practitioners, and direct recruiter connections across Bangalore’s GCC and product company ecosystem. Our placement team works exclusively with AI and tech roles, not general job portals or aggregators.

The Generative AI Skill Gap
Widens Every Quarter.
Your Next Move Matters.

Bangalore’s AI job market is not waiting for you to feel ready. The professionals who
enrolled 12 months ago are already leading AI adoption inside their companies. The
window for first-mover advantage in your specific domain is narrowing every month.

Book Free Demo Class at VKNOWTECH.AI →