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
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
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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.
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- May 23, 2026
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Transcript with Skills Breakdown (Python, ML, DeepLearning,LLMs,RAG, Longchain&More.,)
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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: