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Generative AI & Agentic AI

Data Science with Generative AI & Agentic AI Course in Bangalore – 2026

Join the best Data Science with Generative AI & Agentic AI course in Bangalore! Learn Python, ML, Deep Learning, LLMs, RAG, LangChain & more from industry experts. 412 Hours | Certification | Placement Support.

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Data Science with Generative AI & Agentic AI Course in Bangalore info:

Master Python, Machine Learning, Deep Learning, LLMs, RAG, Fine-Tuning, LangChain & MLOps — India’s Most Comprehensive AI Program

Our Data Science with Generative AI & Agentic AI Course in Bangalore is designed for freshers, graduates, software professionals, and career-switchers who want to become industry-ready AI and Data Science engineers in 2026.

This 412-hour industry-aligned program covers everything from Python Programming, Statistics, Machine Learning, and Deep Learning to cutting-edge topics like Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Prompt Engineering, LLM Fine-Tuning, Agentic AI with LangChain, Multi-Modal AI, and End-to-End MLOps Deployment.

You will work on real-world capstone projects, live case studies, and hands-on labs that prepare you directly for high-demand roles in Data Science, AI Engineering, NLP, and Generative AI development.

With 100% practical sessions, industry mentors, project-based learning, placement assistance, and certification, this is Bangalore’s most job-focused Data Science and Generative AI training program.

Whether you are a complete beginner or a professional looking to upskill into AI, our flexible online & classroom batches (weekday/weekend) are designed to fit your schedule.

Enroll now and get a Free Demo Class + AI Learning Resource Kit!

What is Data Science with Generative AI?

Data Science with Generative AI is the combination of traditional data skills — like statistics, machine learning, and data analysis — with the latest breakthroughs in Generative AI and Large Language Models (LLMs).

Companies worldwide are looking for professionals who can not only analyze data but also build intelligent AI-powered applications using tools like GPT, LLaMA, LangChain, and RAG pipelines.

This program trains you on both — making you a complete AI-ready data professional.

Why Learn Data Science with Generative AI in 2026?

The AI and Data Science job market in India is exploding. Every industry — from banking and healthcare to e-commerce and SaaS — is actively hiring professionals who can build data-driven and AI-powered solutions.

Key market facts:

India’s AI market is projected to reach $17 billion by 2027

Data Scientist and AI Engineer roles are among the top 5 fastest-growing jobs globally

Generative AI skills command 40–60% salary premiums over traditional data roles

LLM and RAG engineering roles are among the highest-paying in tech today — averaging ₹12–25 LPA for mid-level professionals

Career Opportunities After This Course

Top Job Roles:

Data Scientist — Build predictive models, analyze data, and create business insights using Python, ML, and statistical tools. Average Salary: ₹7–18 LPA.

AI/ML Engineer — Design and deploy machine learning and deep learning models for real-world applications. Average Salary: ₹10–22 LPA.

Generative AI Engineer — Build LLM-powered applications, RAG pipelines, and fine-tuned AI systems. Average Salary: ₹12–28 LPA.

NLP Engineer — Develop natural language processing solutions using transformers, LLMs, and embeddings. Average Salary: ₹10–20 LPA.

MLOps Engineer — Manage the full lifecycle of ML models — from training to deployment and monitoring. Average Salary: ₹10–22 LPA.

AI Product Developer — Build intelligent AI-powered products using LangChain, Agentic AI, and LLM APIs. Average Salary: ₹12–25 LPA.

Why Choose Cambridge Infotech for This Course?

✔ Industry-aligned 20-pillar curriculum covering the complete AI ecosystem ✔ Experienced industry trainers with real AI project backgrounds ✔ 100% hands-on practical sessions and live capstone projects ✔ Covers both classical Data Science and next-gen Generative AI ✔ Dedicated placement cell with resume, portfolio & interview support ✔ Flexible weekday, weekend, online, and classroom batches ✔ Trusted by 10,000+ students across Bangalore

Who Should Take This Course?

Freshers & Graduates — BCA, B.Tech, B.Sc., MCA, or any stream looking to enter the AI field → Software Developers — Looking to transition into Data Science or AI Engineering → Data Analysts — Wanting to upgrade skills into Machine Learning and Generative AI → Working Professionals — From IT, finance, or other industries looking to upskill → MBA & Business Graduates — Who want to leverage AI for business analytics and strategy → Entrepreneurs — Who want to build AI-powered products and services

Data Science with Generative AI + Agentic AI – Course Content

Lesson 1: Introduction to Python, Installation, IDEs– 2 Hours

Lesson 2: Variables, Data Types, Type Conversion – 2 Hours

Lesson 3: Operators and Expressions – 2 Hours

Lesson 4: String Manipulation – 2 Hours

Lesson 5: Control Flow (Conditional Statements & Loops) – 6 Hours

Lesson 6: Lists, Tuples, Sets, Dictionaries – 4 Hours

Lesson 7: Functions & Lambda Expressions – 4 Hours

Lesson 8: Map, Filter, Reduce – 2 Hours

Lesson 9: List Comprehension & Introduction to OOP – 2 Hours

Lesson 10: OOP Concepts (Classes, Objects, Encapsulation) – 2 Hours

Lesson 11: Inheritance & Polymorphism – 2 Hours

Lesson 12: Abstraction (Modules & Packages) – 2 Hours

Lesson 13: Case Study – 2 Hours

Lesson 14: Exception Handling – 2 Hours

Lesson 15: File Handling (File I/O) – 4 Hours

Lesson 1: Introduction to NumPy & Array Basics – 2 Hours

Lesson 2: Array Creation & Manipulation – 2 Hours

Lesson 3: Mathematical & Statistical Functions, Random Numbers – 2 Hours

Lesson 4: Array Operations & Broadcasting – 2 Hours

Lesson 1: Introduction to Pandas – 2 Hours

Lesson 2: Loading Data & Pandas Data Structures – 2 Hours

Lesson 3: Indexing, Selecting & Filtering – 2 Hours

Lesson 4: Working with Columns – 2 Hours

Lesson 5: Aggregations & Grouping – 2 Hours

Lesson 6: Sorting & Ranking – 2 Hours

Lesson 7: Merging, Joining & Concatenation – 2 Hours

Lesson 8: Pivot Tables & Crosstabs – 2 Hours

Lesson 9: Data Visualization using Pandas – 2 Hours

Lesson 1: Introduction to Matplotlib – 2 Hours

Lesson 2: Plotting & Plot Types – 2 Hours

Lesson 3: Subplots & Layouts – 2 Hours

Lesson 4: Customization, Legends & Annotations – 2 Hours

Lesson 1: Introduction to Seaborn & Comparison with Matplotlib – 2 Hours Lesson 2: Categorical & Distribution Plots – 2 Hours Lesson 3: Relational Plots, Heatmaps & Matrix Plots – 2 Hours Lesson 4: Faceting, Styling & Customization – 2 Hours Lesson 5: EDA Hands-on Project – 2 Hours Lesson 6: EDA Hands-on Project – 2 Hours

Descriptive Statistics – 14 Hours

Lesson 1: Introduction to Statistics & Data Types – 2 Hours

Lesson 2: Measures of Central Tendency – 2 Hours

Lesson 3: Measures of Dispersion – 2 Hours

Lesson 4: Distribution & Shape of Data – 2 Hours

Lesson 5: Data Visualization – 2 Hours

Lesson 6: Correlation & Covariance – 2 Hours

Lesson 7: Descriptive Statistics in Python – 2 Hours

 

Inferential Statistics – 14 Hours

Lesson 1: Probability Concepts – 2 Hours

Lesson 2: Probability Distributions – 2 Hours

Lesson 3: Sampling & Central Limit Theorem – 2 Hours

Lesson 4: Confidence Intervals – 2 Hours

Lesson 5: Hypothesis Testing Basics – 2 Hours

Lesson 6: Common Hypothesis Tests – 2 Hours

Lesson 7: Inferential Statistics in Python – 2 Hours

Lesson 1: Regular Expressions – 4 Hours

Lesson 2: Web Scraping - 6 Hours

Lesson 3: Hands-on Project – 2 Hours

Lesson 1: SQL Basics & SELECT – 2 Hours

Lesson 2: ORDER BY, LIMIT, ALIAS – 2 Hours

Lesson 3: Aggregate Functions – 2 Hours

Lesson 4: GROUP BY – Deep Dive – 2 Hours

Lesson 5: String & Date Functions – 2 Hours

Lesson 6: JOINs – 2 Hours

Lesson 7: Subqueries – 2 Hours

Lesson 8: Window Functions – 2 Hours

Lesson 9: Set Operations – 2 Hours

Lesson 10: Hands-on Project – 2 Hours

Lesson 1: Supervised Learning – 30 Hours

Lesson 2: Unsupervised Learning – 14 Hours

Lesson 3: Feature Engineering & Selection – 4 Hours

Lesson 4: Model Creation – 4 Hours

Lesson 5: Model Evaluation – 4 Hours

Lesson 6: Hyperparameter Tuning – 4 Hours

Lesson 1: ML Pipelines – 2 Hours

Lesson 2: Streamlit – 4 Hours

What you'll learn

  • Write Python programs and use NumPy, Pandas, Matplotlib, and Seaborn for data analysis
  • Perform Exploratory Data Analysis (EDA) and apply statistical concepts to real datasets
  • Build, train, and evaluate Supervised and Unsupervised Machine Learning models
  • Design and train Artificial Neural Networks, CNNs, and RNNs using Deep Learning frameworks
  • Understand how Large Language Models (LLMs) work — including GPT, Claude, LLaMA, and Gemini
  • Write effective prompts using Zero-shot, Few-shot, Chain-of-Thought, and ReAct techniques
  • Build Retrieval-Augmented Generation (RAG) pipelines with vector databases like FAISS, Pinecone, and Chroma
  • Fine-tune open-source LLMs using LoRA, QLoRA, and PEFT techniques
  • Develop Agentic AI workflows and multi-step agents using LangChain
  • Build and deploy Multi-Modal RAG systems that process both text and images
  • Evaluate LLM outputs using BLEU, ROUGE, BERTScore, and LLM-as-a-Judge frameworks
  • Implement guardrails, prompt injection defense, and responsible AI practices
  • Deploy ML and GenAI models using Docker, FastAPI, and cloud-based infrastructure
  • Set up complete MLOps pipelines with experiment tracking, CI/CD, drift detection, and monitoring
  • Scrape data from the web, query databases using SQL, and work with structured/unstructured data

Prerequisites

  • Basic computer operating knowledge (Windows/Mac/Linux)
  • Logical thinking ability — no prior programming experience required
  • A laptop or desktop with at least 8GB RAM (16GB recommended for deep learning)
  • Willingness to dedicate 2–3 hours daily for practice
  • Curiosity and enthusiasm to learn AI and Data Science from scratch

Testimonials: Hear From Our Happy Students

Discover why we’re the top choice! Dive into our reviews and see why students love us. Join us today and experience excellence firsthand!

The Voice of Success: Explore Our Student Testimonials

Priya Ramesh
Priya Ramesh
The Data Science with Generative AI course at Cambridge Infotech was a complete game-changer for me. I came in with zero programming knowledge, and now I'm building RAG pipelines and LangChain agents on my own. The trainers explained every concept with real examples and never left any doubts unanswered. I got placed as a Junior AI Engineer within two months of completing the course.
Karthik Subramaniam
Karthik Subramaniam
I was a software developer for 4 years looking to shift into the AI space. This program gave me exactly what I needed — a deep understanding of Machine Learning, Deep Learning, and GenAI in one structured course. The LLM fine-tuning and MLOps sections were particularly excellent. The hands-on projects gave me real portfolio material for interviews.
Sneha Patil
Sneha Patil
Cambridge Infotech's Generative AI program is genuinely the most comprehensive course I've seen in Bangalore. The curriculum goes from Python basics all the way to Agentic AI and Multi-Modal RAG, which I couldn't find in any other institute. The trainers are passionate and the batch size is small enough that everyone gets individual attention.
Rajiv Anand
Rajiv Anand
Excellent course content and outstanding trainers. The sections on Prompt Engineering, RAG, and LangChain were very practically oriented — we didn't just learn theory, we built actual applications. The placement team was also very active and helped me prepare my resume and mock interviews. Highly recommend to anyone serious about an AI career.
Divya Nair
Divya Nair
I enrolled in the weekend batch while working full-time, and the flexibility was perfect. The course structure is very logical — each pillar builds on the previous one. By the time we reached LLMs and fine-tuning, everything made sense because the foundation was so solid. The capstone project really helped me consolidate everything I learned.
Mohammed Irfan
Mohammed Irfan
The Data Science and GenAI course at Cambridge Infotech exceeded my expectations. I especially appreciated how the curriculum covers both traditional ML and cutting-edge topics like LLM evaluation, guardrails, and responsible AI. These are topics that are rarely taught together. The instructors have actual industry experience, and it shows in the way they teach.
Ananya Krishnan
Ananya Krishnan
As a fresh graduate, I was worried this course might be too advanced. But the step-by-step approach from Python all the way to Agentic AI made it accessible and engaging. The EDA and Machine Learning projects were very hands-on, and the LangChain and RAG sections opened my eyes to what modern AI development really looks like. Great institute and supportive staff.
Suresh Babu
Suresh Babu
I had tried a few online courses before, but nothing compared to the structured, mentor-led experience at Cambridge Infotech. The combination of Data Science fundamentals and Generative AI is exactly what companies are looking for right now. The MLOps and deployment sections were very practical and directly applicable on the job. Placement support was also very helpful.

Frequently Asked Questions

Got questions? We’ve got answers! Explore our FAQ section to find solutions to common queries. Dive in now!

The course is 412 hours in total, spread across 20 learning pillars covering Python, Statistics, Machine Learning, Deep Learning, Generative AI, LLM Fine-Tuning, RAG, LangChain, and MLOps. The estimated completion time is 9 to 9.5 months depending on your batch schedule.

No prior experience is required. This course is designed to take you from absolute basics — starting with Python programming — all the way to advanced Generative AI and Agentic AI development. Beginners and experienced professionals are both welcome.

Graduates of this program are qualified for roles such as Data Scientist, AI/ML Engineer, Generative AI Engineer, NLP Engineer, MLOps Engineer, Data Analyst, and AI Product Developer. These are among the highest-demand and highest-paying roles in the Indian tech industry in 2026.

A regular Data Science course typically covers Python, ML, and maybe some deep learning. This program goes significantly further — including Large Language Models (LLMs), Prompt Engineering, RAG pipelines, LLM Fine-Tuning, Agentic AI with LangChain, Multi-Modal AI, LLM Evaluation & Safety, and full MLOps deployment. It is a complete end-to-end AI engineering program.

Yes. The program includes multiple hands-on projects and case studies across all pillars — including an EDA project, ML model deployment project, deep learning applications, RAG-based chatbot development, LangChain agent building, and a final end-to-end MLOps capstone project.

  • You will gain hands-on experience with Python, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow/Keras, SQL, FAISS, Pinecone, Chroma, Weaviate, LangChain, Hugging Face Transformers, LoRA/QLoRA, Docker, FastAPI, Streamlit, and major LLM APIs including GPT, Claude, LLaMA, and Gemini.

Yes. Cambridge Infotech provides dedicated placement support including resume building, AI portfolio guidance, LinkedIn profile optimization, mock interviews, and direct hiring partner connections. We have a strong network of hiring companies across Bangalore and India.

Yes. We offer flexible learning modes to suit your schedule — including online live training, classroom training at our Bangalore centre, and both weekday and weekend batches. You can choose the format that works best for you.

Yes. Upon successful completion, you will receive an industry-recognized Data Science with Generative AI & Agentic AI certification from Cambridge Infotech. This certificate is recognized by hiring partners and can be showcased on LinkedIn and job applications.

The course fee varies depending on the batch type (online/classroom/weekday/weekend). Cambridge Infotech offers flexible EMI payment options to make the program accessible. Please contact our learning advisor at +91 9902461116 or fill out the enquiry form to get the latest pricing and batch schedule.

Data Science with Generative AI & Agentic AI course Corporate Training

Join our Corporate Data Science with Generative AI & Agentic AI course to enhance skills and elevate professional effectiveness. Benefit from EMI Options and Placement Assistance.

Upcoming Batch - Data Science with Generative AI & Agentic AI course

Join next batch and kickstart your journey. Elevate your communication skills and unlock endless opportunities. Benefit from flexible EMI options and placement support. Enroll now!

 

05/05/2026

Mon (Mon-Fri)

WEEKDAYS BATCH

10:00 am (IST)

(Class 1hr - 1:30Hrs)/Per Session

05/06/2026

Mon (Mon-Fri)

WEEKDAYS BATCH

10:00 am (IST)

(Class 1hr - 1:30Hrs)/Per Session

05/07/2026

Saturday

WEEKEND BATCH

10:00 am (IST)

(Class 4hrs)/Per Session

Data Science with Generative AI & Agentic AI course Completion Certificate

Earn a Industry-Recognized Certificate

Cambridge Infotech Certified Generative AI & Agentic AI (Digital + Physical)

 Verified LinkedIn Badge (Shareable on profiles)

Transcript with Skills Breakdown (Python, ML, DeepLearning,LLMs,RAG, Longchain&More.,)

Additional Certifications You’ll Earn

AWS Cloud Basics

 Git & GitHub Professional

Power BI / Tableau Fundamentals

SQL for Data Science

AI Project Deployment Basics

Cambridge Infotech Course Completion Certificate
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Companies our students are placed in

Companies

our students are placed in

The companies our students are placed in are a testament to the excellence of our program. Our education equips students with the skills and knowledge necessary to succeed in these top-notch organizations. Take a look at where our graduates have landed:

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