Data Science with Agentic AI Course in Vijayawada

Master the future of Artificial Intelligence with Codegnan’s Data Science with Agentic AI Course in Vijayawada. This industry-focused training program is designed to help students and professionals master Python, Data Science, Machine Learning, Generative AI, RAG Architecture, AI Agents, MCP, LoRA, and advanced LLM application development through hands-on training and real-world projects.

Whether you’re a beginner starting with Python or a professional looking to transition into AI and Data Science, this course provides complete practical exposure to building intelligent AI systems, predictive models, and production-ready applications used by modern enterprises.

Master the future of Artificial Intelligence with Codegnan’s Applied Agentic AI Course in Vijayawada. This industry-focused training program is designed to help students and professionals learn Generative AI, RAG architecture, AI agents, MCP, LoRA, and advanced LLM application development through hands-on training and real-time projects.

If you are a beginner starting with Python or a developer looking to transition into AI engineering, this course provides complete practical exposure to building production-ready AI systems used in modern enterprises.

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VIJAYAWADA

Our Collaborations

Powerful Partnerships, Greater Impact

Building bridges between learning and real-world success.

100 Days Intensive AI Training Program

Personalized 1:1 Mentor Guidance

Industry-Focused Agentic AI Curriculum

Hands-on Practical & Project-Based Learning

Lifetime Access to LMS & Learning Resources

Real-Time AI/LLM Application Development

Placement Assistance with Mock Interviews

Course Overview

Data Science with Agentic AI Course Overview in Vijayawada

Our Data Science with Agentic AI Course is designed to take learners from Python programming fundamentals to advanced Data Science, Machine Learning, Generative AI, and Agentic AI application development. Students gain hands-on experience analyzing real-world datasets, building predictive models, developing Retrieval-Augmented Generation (RAG) applications, and creating autonomous AI agents using the latest tools and frameworks.

Agentic AI course overview

The curriculum combines strong Data Science foundations with cutting-edge AI technologies, ensuring learners graduate with practical skills that employers demand. By the end of the program, students will be able to collect, analyze, visualize, and interpret data, build machine learning models, develop intelligent AI applications, and deploy production-ready AI systems capable of solving real-world business challenges.

Our Training Program Includes

  • 100 Days Intensive AI & Data Science Training
  • Python Foundation to Advanced AI
  • Data Science & Machine Learning
  • Data Analysis & Visualization
  • Real-Time AI Projects
  • Agentic AI & Multi-Agent Systems
  • RAG Architecture & Vector Databases
  • Fine-Tuning & LoRA
  • Placement Support & Mock Interviews
  • Industry-Oriented Practical Sessions

Why Codegnan?

Why Choose Codegnan’s Data Science with Agentic AI Course in Vijayawada

Get Trained by Industry Experts

Learn from experienced mentors who work on real-world AI and software development projects.

Beginner-Friendly Learning Path

The course starts with Python fundamentals and gradually moves into advanced AI systems and agent development.

Build Real-World Projects

Gain practical exposure by building voice assistants, RAG systems, AI agents, and multi-agent workflows.

Placement Assistance & Career Guidance

Receive dedicated support for resume building, mock interviews, and AI career preparation.

Industry-Focused Curriculum

Learn technologies and frameworks currently used in modern AI application development.

Learn Through Practical Implementation

Every module includes practical assignments, coding sessions, and project-based learning.

Learning Path

What You’ll Learn

A step-by-step roadmap designed to take you from fundamentals to job-ready expertise.

You'll Have

Everything You Need to Become
Job-Ready

Industry-recognized certification, modern tools, real-world projects, and dedicated placement support — all in one complete program.

Placement Support

Real-World Projects

Tools you'll learn

Tools You’ll Learn

Applied Agentic AI Certificate by Codegnan

Industry-Recognized Certification

Curriculum

Data Science with Agentic AI Course curriculum in Vijayawada

Applied Agentic AI Course in Vijayawada covers AI agents, LLMs, automation workflows, vector databases, and real-world AI applications with hands-on projects.

  • Introduction to Python
  • Python Operators
  • Python Conditional Statements
  • Python Loops
  • List Data Structure
  • Tuple Data Structure
  • Set Data Structure
  • Dictionary Data Structure
  • Python Functions
  • Regular Expression
  • OOP in Python
  • File Handling
  • Pandas
  • NumPy
  • Matplotlib
  • APIs
  • FastAPI
  • Logging
  • Pytest
  • Pydantic
  • Streamlit-1 Frontend Development
  • Streamlit-2 Advance Operations
  • Python Project – Part 1
  • Python Project – Part 2
  • “Introduction to Pandas
  • Important list of Operations in Pandas
  • Installing and Importing Pandas
  • Creating Series data structure
  • Update/Delete/Insert operation on Pandas Series”
  • “Introduction to Dataframes
  • Creating dataframe from list, Tuple, Set and dictionary
  • Converting a Series to DataFrame
  • Assigning the names to columns in dataframe”
  • “Data Input and Output in dataframe from CSV,
  • Data Input and Output in dataframe from Excel
  • Data Input and Output in dataframe from SQL
  • Data Input and Output in dataframe from JSON
  • View Data in DataFrame: Head(), Tail()
  • Shape of Dataframe
  • Select a single column in dataframe
  • Select Multiple Columns in dataframe”
  • “Renaming column name in dataframe
  • Creating a new column in dataframe
  • Deleting column in dataframe
  • Replace specific values in Dataframe
  • Data Types of columns in dataframe
  • Convert Data Type
  • unique values in a column
  • Statistical summary with Describe()
  • Fillter data based on a Condition
  • Filter using Where() function”
  • “loc & iloc
  • Filtering based on condition using loc & iloc
  • Dataset value updates using loc & iloc
  • at & iat
  • Sorting Rows by Values and index
  • Change index column, Reset index to default integers”
  • “Handling NaN / Null values
  • Check for NaN values total
  • drop null value “”rows””
  • drop null value “”columns””
  • Replace NaN with value”
  • “Find Duplicate Rows (Entire Row Match)
  • get sum of duplicate rows
  • Find Duplicates in a Specific Column
  • Drop all duplicate rows (keep first occurrence)
  • Delete entire rows based on specific column duplicate values
  • Handling inconsistent data
  • Use of title(), lower(), strip() functions
  • Data transformation using apply()
  • Data transformation using map()”
  • “Introduction to Numpy
  • Important Numpy Operations
  • Installing & Importing NumPy
  • Creating 1D, 2D, and 3D numpy arrays
  • Keyword usage: dtype, ndim, shape”
  • “Specific type of Numpy arrays
  • Create a 1D/2D/3D array of zeros
  • 1D/2D/3D array of ones
  • 1D/2D/3D array of any Constant value
  • creating Identity Matrix
  • Numpy random package
  • 1D/2D/3D array of uniformly distributed random values b/w 0-1
  • Uniform() method: Uniformly distributed with any range
  • random() method
  • randn() method
  • choice() method
  • seed() method”
  • “Create sequence, shuffle, Permutation and Linearly spaced values
  • arange() method
  • shuffle() method
  • permutation() method
  • linspace() method
  • Array Shape & Reshaping & Transpose
  • shape() method
  • reshape() method
  • ravel() method”
  • “Transpose the array
  • Creating instant nD array
  • Size and Data Type of numpy Elements
  • Keywords: dtype, size
  • Data type conversion
  • Indexing & Slicing & Modifying
  • Modification, Insertion, Deletion operations”
  • “Mathematical & Statistical Operations
  • sum(), min(), max(), mean(), var(), std(), percentile(),
  • quantile(), argmax(), argmin(),log10(), log2(), log()
  • sqrt(), round(), floor(), ceil(), abs()
  • Sort string/integer array
  • Sorting in decreasing order using slicing”
  • Introduction to Matplotlib
  • Installing and Importing Matplotlib
  • Bar Chart
  • Horizontal Bar Chart
  • Histogram
  • Line Plot
  • Multiple line chart
  • Scatter Plot
  • Pie Chart
  • Donut Chart
  • Add text in the hollow center of Donut
  • Introduction to Seaborn
  • Installing and Importing Seaborn
  • Built-in Datasets in seaborn
  • line chart
  • scatter chart
  • Pair Plot
  • Heatmap
  • Categorical features relation : pivot table + HeapMap
  • Multi-Index & columns in pivot table
  • countplot()
  • Box plot
  • Density Plot
  • Violin plot
  • Regression Plot
  • FacetGrid
  • Joint Plots
  • 1.1 Feature Encoding
  • 1.1.1 Label encoding
  • 1.1.2 Ordinal encoding
  • 1.1.3 One hot encoding
  • 1.2 Feature Scaling
  • 1.2.1 Min-Max Scaling
  • 1.2.2 Standardization
  • 1.2.3. Robust Scaling
  • Introduction to ML
  • Linear Regression
  • Logistic Regression
  • Naive Bayes
  • Support Vector Machine
  • K Nearest Neighbors
  • Decision Tree
  • Performance matrices
  • Principal Component Analysis
  • XGBoost
  • KMeans
  • Bias and Variance

  • ML Project – Part1 : Data Cleaning
  • ML Project – Part2 : Feature Engineering
  • ML Project – Part3 : Model training
  • ML Project – Part4 : Deploy on Cloud

  • Introduction to Neural Networks
  • Backpropagation
  • Creating Neural networks
  • Intro to Natural Language Processing
  • NLP Project – Sentiment Analysis
  • NLP Project – Sentiment Analysis
  • Intro to Computer Vision
  • Convolutional Neural Network
  • YOLO
  • Introduction to Gen-AI
  • Gen AI vs AI Agent vs Agentic AI
  • Understanding the LLM
  • Transformers architecture
  • What is Context Window, Hallucination
  • Prompt Engineering and its Types
  • GenAI Voice Assistant Project – Part-1
  • GenAI Voice Assistant Project – Part-2
  • Understanding RAG architecture
  • Langchain framework installation
  • Groq and Ollama setup
  • Introduction to Vector Databse
  • Chroma DB installation and operations
  • Meta data filtering
  • Distance matircs
  • RAG Project – part1
  • RAG Project – part2
  • RAG Project – part3
  • Introduction to Agentic AI
  • Building Agent using Llama
  • Agents with Custom Tools
  • Reasoning Models
  • Reasoning Agents with Agno
  • Multimodal Agents
  • Smolagents
  • Google ADK
  •  
  • Introduction to MCP
  • Building MCP Server
  • A2A Protocol
  • Building Multi Agent Program
  • Design Pattern of Multi Agent System
  • Route Agent
  • Agentic AI Evaluation
  • Functional Evaluation
  • Functional Evaluation in Agno
  • Safety and Guardrails
  • Operational Matrix
  • Hands-on Perf Evaluation in Agno
  • Introduction to Fine-Tuning
  • LoRA
  • Quantization
  • QLoRA
  • Fine Tuning Llama with Unsloth
  • Agentic AI Project – Part 1
  • Agentic AI Project – Part 2
  • Agentic AI Project – Part 3

Become an Data Science with Agentic AI Expert in Vijayawada

Talk to our expert Applied Agentic AI mentors and learn how our practical training program in Vijayawada can help you build intelligent AI agents, automate workflows, and become job-ready for high-paying AI careers.

Skills Covered

Skills Covered in Data Science with Agentic AI Training Institute in Vijayawada

After completing the course, students will gain practical experience in:

  • Python Programming
  • AI Application Development
  • Prompt Engineering
  • LLM Integration
  • RAG Pipeline Development
  • Vector Databases
  • Multi-Agent Systems
  • AI Automation
  • AI Model Evaluation
  • Fine-Tuning & LoRA
  • API Development
  • AI Deployment Workflows

Your Personal LMS Platform

Everything you need to learn, practice, track, and get placed — in one place.

Our Advantage

Why Our Placement System Creates Job-Ready

A Structured, Interview-Focused Training Model Designed for Real Industry Success

Placement-Oriented Training That Converts Skills Into Jobs

🔴 The Challenge

Many students learn concepts but struggle with interviews due to lack of practical exposure, communication skills, and structured preparation.

🟢 Our Approach

We combine industry-driven curriculum, real-world coding practice, soft skills training, and mock interviews to ensure students are fully prepared for hiring processes.

We don’t just teach concepts — we train you to crack interviews.

What this means?

  • Curriculum designed based on current industry demand
  • Strong focus on problem-solving & real-world scenarios
  • Regular coding challenges & performance assessments
  • Resume-building & LinkedIn optimization sessions
  • Mock interviews (Technical + HR rounds)
  • Soft skills & communication training

Dedicated Career Acceleration Team

🔴 The Challenge

Students often lack access to direct hiring connections and structured interview follow-ups.

🟢 Our Support System

A dedicated placement team works with you on referrals, interview coordination, and company-specific preparation.

What this means?

  • Dedicated placement assistance team
  • Interview opportunities with 70–100+ hiring partners
  • Company-specific interview preparation
  • Job referrals & walk-in updates
  • Career guidance even after course completion
  • Support for freshers & career switchers

Placement-Oriented Training That Converts Skills Into Jobs

🔴 The Challenge

Many learners quit due to confusion, lack of feedback, or no guidance.

🟢 Our Mentorship Model

Experienced trainers provide continuous guidance, structured feedback, and one-on-one mentorship sessions.

You’re never learning alone — we guide you at every step.

What this means?

  • One-on-one mentorship from experienced trainers
  • Regular doubt-clearing sessions
  • Code reviews & performance feedback
  • Personal learning roadmap guidance
  • Continuous support throughout the course

Certification That Validates Real Skills

🔴 The Challenge

Generic certificates don’t reflect actual industry readiness.

🟢 Our Mentorship Model

Our Java Full Stack certification reflects hands-on project work and real technical capability.

What this means?

  • Industry-recognized Java Full Stack Certification
  • Validates technical & practical skills
  • Adds strong value to resume & LinkedIn profile
  • Boosts credibility during interviews

Your Journey

Your Journey At Codegnan

Daily Practice, hands-on real-time projects and consistent feedback – your growth depends on the energy and effort you bring in every single day.

Sairam Uppugundla - Codegnan Mentor
Vertical Line

Hands-on Data Science with Agentic AI Course you will work on

Hands-on Applied Agentic AI projects give you real-world experience by building AI agents, automation workflows, and LLM-powered applications, helping you gain practical skills, problem-solving ability, and industry-ready confidence.

GenAI Voice Assistant

1. GenAI Voice Assistant

Build intelligent AI voice assistant systems capable of understanding and responding to user inputs. Learn speech processing, conversational AI workflows, and LLM-powered response generation. Gain hands-on experience in creating interactive AI assistant applications.

Led By Puneet Kansal

Senior Mentor who have experience of 9 Years.

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RAG-Based-AI-Applications

2. RAG-Based AI Applications

Develop AI systems integrated with vector databases and retrieval-augmented generation pipelines. Learn how to build applications that retrieve, process, and generate accurate contextual responses. Work on practical projects using modern AI frameworks and embedding technologies.

Led By Puneet Kansal

Codegnan logo

Senior Mentor who have experience of 9 Years.

Multi-Agent-AI-Systems

3. Multi-Agent AI Systems

Learn how autonomous AI agents collaborate, reason, and complete complex tasks efficiently. Understand agent orchestration, memory handling, task planning, and AI communication workflows. Build intelligent multi-agent systems for automation and advanced AI problem-solving.

Led By Puneet Kansal

Senior Mentor who have experience of 9 Years.

Codegnan logo
AI-Automation-workflows

4. AI Automation Workflows

Create AI-driven workflows capable of automating real-world business operations and repetitive tasks. Learn how AI integrates with APIs, databases, and external tools for process automation. Build practical automation systems using modern AI frameworks and orchestration tools.

Led By Puneet Kansal

Senior Mentor who have experience of 9 Years.

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Is This Data Science with Agentic AI Course in Vijayawada Right for You?

01

1. Students Looking for AI Careers

Perfect for students who want to build careers in Artificial Intelligence and AI application development.

02

2. Working Professionals

Ideal for professionals planning to transition into Generative AI and Agentic AI roles.

03

3. Python Developers

Suitable for developers looking to upgrade into AI engineering and automation development.

04

4. Beginners Interested in AI

The structured curriculum helps beginners start from Python fundamentals and gradually move into advanced AI topics.

05

4. Tech Enthusiasts Interested in AI

Great for anyone passionate about LLMs, AI agents, automation, and future AI technologies.

Trusted by 4,000+ students and 850+ hiring partners

Google Business

Rated 4.8/5

Trustpilot

Rated 3.9/5

Google Business

Rated 4.8/5

4,080 +

Students Placed

850 +

Hiring Partners

1,900 +

Drives Conducted

25LPA

Highest Package

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Companies That Hire From Us

Companies hire from Codegnan

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Real student placement outcomes

Explore our features and discover how our comprehensive

learning platform transforms students into industry-ready professionals.

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Students' Success, Our Pride

Feedback from those who made it

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Learn from certified Data Science and Agentic AI experts in Vijayawada

Puneet Kansal

Puneet Kansal

AI,Gen AI & DSA mentor

Puneet Kansal is a forward-focused AI educator specializing in Generative AI, Agentic AI, Data Science, and Advanced Data Analytics, driving strong fundamentals in modern tech domains.
He brings deep expertise in DSA, competitive programming, and MAANG-level problem solving.
Blending research orientation with practical teaching, he is positioned as a PhD scholar and mentor shaping next-gen AI and data-driven talent

Fees

What is the fee of Data Science with Agentic AI Course in Vijayawada?

The Data Science with Agentic AI Course at Codegnan in Vijayawada is priced at ₹70,000, with a limited-time discounted fee of ₹55,000. This comprehensive program is designed to provide in-depth training in Agentic AI, Generative AI, Large Language Models (LLMs), AI agents, automation workflows, RAG applications, vector databases, and modern AI development tools.

The fee includes classroom training, real-time hands-on projects, placement assistance with 150+ drives annually, internship opportunities, and an industry-recognized certification upon successful completion. Students receive mentorship from experienced industry professionals and work on practical AI applications that prepare them for real-world careers in Artificial Intelligence and automation.

Data Science with Agentic AI Course in Vijayawada

Mobile Number

+91-6301341478

Location

40-5-19/16, Prasad Naidu Complex, P.B.Siddhartha Bus stop, Moghalrajpuram, Vijayawada, Andhra Pradesh, 520010.

Applied Agentic AI Course in Vijayawada FAQs

What is the best Data Science with Agentic AI course in Vijayawada?

Codegnan offers an industry-focused Data Science with Agentic AI Course in Vijayawada covering Python, Data Science, Machine Learning, Generative AI, AI Agents, RAG applications, LLM integration, and real-time AI project development with hands-on training.

Yes. The course starts with Python fundamentals and gradually progresses to Data Science, Machine Learning, Generative AI, and Agentic AI, making it ideal for beginners.

Yes. Students complete multiple Data Science, Machine Learning, and AI projects designed to simulate real industry use cases.

Yes. The curriculum covers supervised and unsupervised machine learning, Large Language Models (LLMs), RAG, AI Agents, and Agentic AI applications.

Yes. Students receive placement support, resume-building sessions, mock interviews, coding assessments, and access to hiring drives.

Engineer, Generative AI Engineer, Data Analyst, AI Application Developer, and AI Automation Engineer.

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