MLOps Certification Course Online with GenAI

Enroll now in the MLOps certification course online offered by Grras to develop hands-on experience in Machine Learning, Generative AI, Agentic AI, MLOps, LLMOps, and Cloud AI. This 100-hour, comprehensive training program is tailor-made for DevOps and Cloud professionals looking to transition into the field of AI Engineering. Starting with basic Python and Machine Learning knowledge, this program will take you to the next level – working with LLMs, RAG, Agentic AI, MLOps, and production AI. Along with that, this program provides you with the credential of GRRAS Certified GenAI & MLOps Engineer with a unique QR code on LinkedIn.

150k+ Placemenets to Date
600+ Hiring Partners
76 Lakhs Highest Annual

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Flexible Learning Modes to Fit Your Schedule

Interactive Classroom Sessions
Live Virtual Instructor-Led Classes
Self-Guided Online Modules
Corporate Onsite Training

Build an Impressive Portfolio

Expand Your Career Opportunities

Stay Ahead with Industry Trends

Master Cutting-Edge Development Tools

Career Scope After MLOps Certification Course Online

The synergy of AI and infra skills has led to the creation of many job opportunities for those professionals who can create and manage AI solutions in a production environment. Upon completion of the MLOps certification program, some of the roles one could pursue include AI/LLMOps Engineer, MLOps Engineer, GenAI Application Developer, Agentic AI Engineer, Cloud AI Engineer, and DevOps Engineer with specialization in AI. This course will help the students combine knowledge of Machine Learning, Generative AI, RAG, Agentic AI, MLOps, LLMOps, Kubernetes, Docker, CI/CD, and cloud AI solutions into a single production skill set.

Designation

Annual Salary

Hiring Companies

₹8–15 LPA (Entry-Level), ₹15–25 LPA (Mid-Level), ₹30+ LPA (Senior-Level)

Data Scientists extract insights from structured and unstructured data using Python, R, SQL, and machine learning frameworks to drive strategic decision-making.

₹6–15 LPA (Entry-Level), ₹15–25 LPA (Mid-Level), ₹25–40+ LPA (Senior-Level)

Machine Learning Engineers develop predictive models, design algorithms, and deploy AI solutions using tools like TensorFlow, PyTorch, and Scikit-learn.

₹6–12 LPA (Entry-Level), ₹12–25 LPA (Mid-Level), ₹25+ LPA (Senior-Level)

Data Engineers build scalable data pipelines, manage databases, and optimize data flows for analysis.

₹8–20 LPA (Entry-Level), ₹20–35 LPA (Mid-Level), ₹35+ LPA (Senior-Level)

AI Specialists design and develop intelligent systems, focusing on natural language processing, computer vision, and AI-driven solutions.

₹5–10 LPA (Entry-Level), ₹10–18 LPA (Mid-Level), ₹18+ LPA (Senior-Level)

Statisticians use statistical methods and tools to analyze data, interpret results, and make recommendations for business and research purposes.

₹8–18 LPA (Entry-Level), ₹20–35+ LPA (Mid-Level)

NLP Engineers work on language-based AI systems, such as chatbots, sentiment analysis tools, and speech-to-text systems, using Python and NLP libraries.

Career Scope After MLOps Certification Course Online

Annual Salary

₹8–15 LPA (Entry-Level), ₹15–25 LPA (Mid-Level), ₹30+ LPA (Senior-Level)

Hiring Companies

Data Scientists extract insights from structured and unstructured data using Python, R, SQL, and machine learning frameworks to drive strategic decision-making.

Annual Salary

₹6–15 LPA (Entry-Level), ₹15–25 LPA (Mid-Level), ₹25–40+ LPA (Senior-Level)

Hiring Companies

Machine Learning Engineers develop predictive models, design algorithms, and deploy AI solutions using tools like TensorFlow, PyTorch, and Scikit-learn.

Annual Salary

₹6–12 LPA (Entry-Level), ₹12–25 LPA (Mid-Level), ₹25+ LPA (Senior-Level)

Hiring Companies

Data Engineers build scalable data pipelines, manage databases, and optimize data flows for analysis.

Annual Salary

₹8–20 LPA (Entry-Level), ₹20–35 LPA (Mid-Level), ₹35+ LPA (Senior-Level)

Hiring Companies

AI Specialists design and develop intelligent systems, focusing on natural language processing, computer vision, and AI-driven solutions.

Annual Salary

₹5–10 LPA (Entry-Level), ₹10–18 LPA (Mid-Level), ₹18+ LPA (Senior-Level)

Hiring Companies

Statisticians use statistical methods and tools to analyze data, interpret results, and make recommendations for business and research purposes.

Annual Salary

₹8–18 LPA (Entry-Level), ₹20–35+ LPA (Mid-Level)

Hiring Companies

NLP Engineers work on language-based AI systems, such as chatbots, sentiment analysis tools, and speech-to-text systems, using Python and NLP libraries.

Course Snapshot

Skills Covered

Complete Course Curriculum

Get hands-on training on an organized MLOps, Generative AI, and Agentic AI journey through our 100-hour sequenced course at Grras. Our course starts with fundamentals of Data Science and Machine Learning and covers Deep Learning, LLMs, Prompt Engineering, RAG, Agentic AI, Open Source LLMs, MLOps, LLMOps, and Cloud AI. Our program is highly practical, includes multiple labs and ends with a production-ready capstone project.

Course Details

Mode: Live Interactive Hybrid + Recorded Lectures
Duration: 100 Hours
Learning: 100% Practical Labs
Scheduling Options: Weekday & Weekend
Support: Live Q&A + 24/7 Virtual Labs
Certification: GRRAS Certified GenAI & MLOps Engineer
Capstone: Production-ready, deployed AI System

Who Should Enroll

Linux Engineers & System Administrators aspiring for AI engineering
DevOps Engineers aspiring to gain AI/ML and Agentic AI skills
Cloud Engineers who work with AWS, Azure, or GCP aspiring for AI specialization
Red Hat / RHCE professionals looking for the next step in their career
Professionals with scripting background & little/no ML experience
Infra Professionals interested in GenAI, MLOps, LLMOps, & AI automation

Course Outcomes & Skills You Master

Python for AI: Foundation on Python, APIs, JSON & Automation
Machine Learning: Data Handling, EDA, Supervised & Unsupervised Learning
Deep Learning & LLMs: Neural Networks, Transformers, LLM Fundamentals & APIs
Generative AI: Building Applications with LLMs & Prompt Engineering
RAG: Working with Embeddings, Vector Databases, Retrieval Pipelines, & Enterprise Knowledge Systems
Agentic AI: Agents & Multi-Agent workflows with LangChain, LangGraph, CrewAI, AutoGen
MLOps & LLMOps: MLflow, DVC, Docker, Kubernetes, CI/CD, Model Monitoring, Deployment
Cloud AI: AWS Bedrock, SageMaker, Azure AI Studio, Azure OpenAI, Google Vertex AI

Hands-On Learning

18 hands-on modules with lab activities and mini-projects
Practical infrastructure and DevOps use cases for AI
Real-world processes like log analytics, incident management, and runbook automation

Production Skills

Create containerized versions of AI applications with Docker
Implement AI applications using Kubernetes
Construct CI/CD workflows for ML models and AI applications
Monitoring of model performance, latency, cost, and drift

Career Development

Build ready-to-present AI projects
Capstone tracks with production focus
Skills in AI, GenAI, MLOps, LLMOps, and Cloud AI roles

Begin your DevOps to AI Engineering journey with us!

Begin your journey into MLOps, GenAI & Agentic AI with Grras.

Data Science Course Curriculum

Our industry-aligned curriculum spans 8 comprehensive modules, from database fundamentals to advanced Generative AI. Each module combines theoretical concepts with practical implementation, ensuring you master both the science and art of data-driven decision making through hands-on projects and real-world applications.

MLOps Certification Course Online with GenAI

Understanding Database & Connectivity

Introduction to Databases
Types of Databases (SQL and NoSQL)
Basics of SQL Databases
- Types of Keys
- Constraints
- Schema Design
CRUD Operations
- Create
- Read
- Update
- Delete
Types of JOINS
- Inner Join
- Left Join
- Right Join
- Outer Join
Aggregate Functions
- MIN
- MAX
- SUM
- COUNT
- AVG
Advanced SQL
- Triggers
- Stored Procedures
- Control Statements Implementation
- WITH Clause (CTE)
SQL Databases
- MySQL
- PostgreSQL
- SQLite
NoSQL Database
- MongoDB
Python Database Connectivity
- SQLite Connectivity
- MySQL Connectivity
- Libraries Used
  - SQLAlchemy
  - PyMySQL

Statistics & Mathematics

Descriptive Statistics
- Measures of Central Tendency
  - Mean
  - Median
  - Mode
- Measures of Spread
  - Deviation
  - Standard Deviation
  - Variance
- Frequency Distribution
- Quartile Deviation
- Data Distribution Visualization
  - Normal Distribution
  - Skewed Distribution
  - Kurtosis
Inferential Statistics
- Hypothesis Testing
  - p-value
  - Confidence Intervals
  - Chi-Square Test
- Probability Theory
  - Bayes’ Theorem
  - Probability Distributions
Linear Algebra for Machine Learning
- Matrices and Vectors
  - Transpose
  - Inverse
  - Determinants
- Eigenvalues and Eigenvectors
  - Application in PCA and Dimensionality Reduction

Data Science (Data Engineering, Analysis & Visualization)

Data Engineering & Preprocessing
- Data Extraction
  - APIs
    - Understanding API concepts
    - HTTP protocols and API methods (GET, POST, PUT, DELETE)
    - Working with APIs such as Google API, Weather API, Stock Market APIs
  - Databases
  - Web Scraping
  - Cloud Data Sources
  - Online Resources
    - Kaggle
    - Google Dataset Search
- Data Cleaning & Transformation (using Pandas and NumPy)
  - Handling Outliers
  - Data Skewness Treatment
  - Handling Missing, None, or Empty Values
  - Data Transformation Techniques
Exploratory Data Analysis (EDA)
- Data Analysis using Pandas
  - Working with 1D and 2D Data
  - Aggregate Functions
  - Data Filtering Techniques
  - Indexing and Slicing in DataFrames
  - Merging and Joining Multiple Datasets
  - GroupBy Operations
  - Sorting Data by Index and Values
  - Applying Multiple Mathematical Operations
- Feature Engineering
  - Converting Text Data to Numerical Format
    - One-Hot Encoding
    - Label Encoding
  - Data Scaling Techniques
Data Visualization
- Data Visualization Libraries
  - Pandas
  - Matplotlib
  - Seaborn
  - Plotly
- Building Live Graphs using Real-Time Data Animation
- Creating Interactive Dashboards using Streamlit

Machine Learning

Introduction to Machine Learning
- What is an Algorithm?
- Core Machine Learning Concepts
- Difference between Traditional Programming and Machine Learning
- Types of Machine Learning Algorithms
- Online Learning vs Offline Learning
- Understanding Training and Testing Data
Supervised Learning
- Regression Models
  - Simple Linear Regression
  - Multiple Linear Regression
  - Polynomial Regression
- Classification Models
  - Decision Trees
  - Random Forest
  - Support Vector Machine (SVM)
  - Naïve Bayes
  - K-Nearest Neighbors (KNN)
  - Logistic Regression
- Model Evaluation Metrics
  - Confusion Matrix
  - ROC–AUC Curve
  - Precision
  - Recall
  - F1 Score
  - Classification Report
  - Accuracy Score
  - R² Score
Unsupervised Learning
- Clustering Algorithms
  - K-Means Clustering
  - Hierarchical Clustering
- Dimensionality Reduction Techniques
  - Principal Component Analysis (PCA)
  - Linear Discriminant Analysis (LDA)
  - Autoencoders
Model Optimization & Deployment
- Hyperparameter Tuning
  - Grid Search
  - K-Fold Cross Validation
- Model Deployment
  - Flask
  - Pickle
  - Joblib
- Gradient Descent Algorithm

Natural Language Processing (NLP)

Text Preprocessing & Feature Engineering
- NLP Techniques using NLTK
  - Tokenization
  - Stemming
  - Lemmatization
- Word Embedding Concepts
  - One-Hot Encoding
  - TF-IDF (Term Frequency–Inverse Document Frequency)
  - Word2Vec
Building NLP Models
- Sentiment Analysis
- Document Classification
- Named Entity Recognition (NER)

Deep Learning & Neural Networks

Neural Network Fundamentals
- Stochastic Gradient Descent (SGD) Algorithm
- Activation Functions
  - ReLU
  - Sigmoid
  - Softmax
- Backpropagation Algorithm
- Neurons
- Weights
- Bias and Variance
- Hidden Layers
Building & Training Neural Networks
- Building and Training Models using TensorFlow and Keras
- Loss Functions
- Optimization Techniques
Convolutional Neural Networks (CNNs)
- Creating CNN Models with Multiple Layers
- Image Classification Models
- Transfer Learning Concepts
  - ResNet
  - VGG
  - MobileNet
Recurrent Neural Networks (RNNs) & Transformers
- Embedding Concepts
- Building RNN Models with Multiple Layers
- Transformer Architecture
  - Encoders
  - Decoders
- BERT and GPT for NLP Applications

Generative AI (Including Retrieval-Augmented Generation – RAG)

Introduction to Generative AI
- Importance of Generative AI
- Architecture of Generative AI Systems
- Encoder-Based Concepts
  - Generative Adversarial Networks (GANs)
  - Variational Autoencoders (VAEs)
- Understanding Large Language Models (LLMs) and Their Working
- Implementing Various LLMs using Open-Source APIs
Fine-Tuning Large Language Models
- Adapting GPT and BERT for Custom Applications
- Fine-Tuning Models using Hugging Face
Retrieval-Augmented Generation (RAG)
- Enhancing LLMs with Real-Time Data Retrieval
- Document Chunking and Text Splitting Techniques
- Embedding Generation
- Vector Databases and Vector Search
  - FAISS
  - Pinecone
  - ChromaDB
Building AI-Powered Assistants
- Real-World AI Chatbots and Applications

Cloud Computing

Introduction to Cloud Computing
- What is Cloud Computing and Its Benefits
- Cloud Service Models
  - Infrastructure as a Service (IaaS)
  - Platform as a Service (PaaS)
  - Software as a Service (SaaS)
Popular Cloud Platforms
- Overview of Major Cloud Platforms
  - Amazon Web Services (AWS)
  - Microsoft Azure
  - Google Cloud Platform (GCP)
- ML and Data Services Offered by Each Platform
Storage and Compute Services
- Object Storage Services
  - Amazon S3
  - Azure Blob Storage
- Virtual Machines and Scalable Compute Engines
Cloud Databases
- SQL Databases
- NoSQL Databases
Machine Learning Services
- Cloud ML Platforms
  - Azure ML Studio
  - AWS SageMaker
  - Google Vertex AI
- Drag-and-Drop ML Workspaces to
  - Build Models
  - Train Models
  - Optimize Performance
  - Deploy Models
Model Integration & Monitoring
- Integrating Python Scripts and Prebuilt Modules
- Model Versioning and Experiment Tracking
- Model Performance Monitoring and Analysis
- Support for Real-Time and Batch Inference

Real-World Projects in the MLOps Certification Course

This MLOps Certification Course Online offers real-life experience through hands-on labs and projects, along with a capstone project for production. Throughout the course, students develop applications related to FastAPI, machine learning models, LLM APIs, RAG pipelines, AI agents, multi-agent systems, and cloud AI products. In the capstone project, the learner will get to select production tracks, such as Autonomous DevOps Incident Response Agent, Enterprise Private GPT Knowledge Assistant, and Multi-Agent Infrastructure Automation System.

Car Price Predictor: Informed Valuations for the Used Car Market

#01

The Car Price Predictor project is a web-based application that allows users to estimate the selling price of used cars by inputting key details, such as mileage and year of manufacture. The application leverages a linear regression model, trained on historical data, to generate price predictions. Users can interact with…

LoanPredictor: Intelligent Loan Approval Estimator

#02

The Loan Prediction project is a web-based application that leverages data science to estimate loan approval outcomes. Users enter vital financial details, such as income and credit score, into an intuitive interface built with Flask. The system employs a Random Forest model, developed using Scikit-learn, which is trained on historical…

Wine Quality Predictor: AI-Powered Wine Assessment

#03

The Wine Quality Predictor project is a machine learning-based application designed to assess wine quality based on key chemical properties. Using a linear regression model built with Scikit-learn, the system analyzes features like acidity, alcohol content, and pH level to estimate a quality score. The project evaluates the model's accuracy…

IPL Score Predictor: Smart Cricket Score Estimation

#04

The IPL Score Predictor project is a machine learning-based model designed to estimate the final score of an IPL match based on key in-game factors. Using a linear regression model built with Scikit-learn, the system analyzes inputs like current runs, wickets, and overs to predict the total score at the…

Movie Magic: AI-Powered Movie Recommendation System

#05

The Movie Magic project is a machine learning-powered recommendation system designed to suggest movies based on user preferences and past ratings. Using collaborative filtering and content-based recommendation techniques, the model analyzes user behavior, movie details, and rating patterns to uncover personalized movie suggestions. The system evaluates its recommendation accuracy by…

E-Commerce Customer Spending Predictor: Data-Driven Insights for Business Growth

#06

The E-Commerce Customer Spending Predictor is a machine learning-based project that helps businesses understand and forecast customer spending behavior. Using a linear regression model built with Scikit-learn, the system analyzes key factors such as session length, time spent on the app, and other user interactions to estimate yearly spending. This…

Diabetes Prediction: AI-Powered Health Risk Assessment

#07

The Diabetes Prediction project is a machine learning-based model designed to assess the likelihood of diabetes in individuals based on key health indicators. The dataset, sourced from Kaggle, originates from the National Institute of Diabetes and Digestive and Kidney Diseases and includes features such as Number of Pregnancies, Insulin Level,…

Arrhythmia Classification AI-Powered ECG-Based Heart Health Assessment

#08

The Arrhythmia Classification project leverages machine learning to detect and classify different types of arrhythmia using ECG data. The dataset consists of 452 samples and 16 classes, including both normal and various arrhythmia conditions. A major challenge is the high-dimensional nature of the data, with 279 features exceeding the number…

Industry-Recognized Professional Certification

Receive a globally valued certification that validates your skills, practical knowledge, and job-ready expertise. This certification enhances your credibility, strengthens your resume, and helps you stand out to employers in competitive industries worldwide.

20000+

Professionals Trained
20+

Countries & Counting
100+

Corporate Served

Our Proven Track Record Shows that we Walk the Talk

Gajendra Singh

Data Analyst

Jaipur

The technical training in Data Analytics provided by the institute was comprehensive and well-structured. The curriculum covered essential concepts such as data cleaning, analysis, and...

Aditi Naruka

Cloud ops Engineer

Jaipur

Aditi Naruka has successfully completed the 4-month Devops and Cloud Computing program and secured a placement.

Raghav Bahad

Data Analyst

Jaipur

Raghav Bahad has successfully completed the 4-month Data Analyst program and secured a placement.

Suhaib Illyas

Python developer

Jaipur

Suhaib Illyas has successfully completed the 3-month PYTHON program and secured a placement.

Gourav Khatri

Data Analyst

Jaipur

Gourav Khatri has successfully completed the 4-month Data Analyst program and secured a placement.

Shamrez Khan

MIS Executive

Jaipur

Shamrez Khan has successfully completed the 4-month Data Analyst program and secured a placement.

Arbaj Khan

Graphic Designer

Jaipur

Arbaj khan has successfully completed the 4-month Ui Ux design program and secured a placement.

Why Choose Grras Solutions?

The demand for skilled data science professionals is skyrocketing as industries leverage data to gain strategic insights and optimize operations. Frompredictive analytics to AI-powered solutions, data science is transforming business.

Industry-Aligned Curriculum

Master a curriculum crafted and constantly updated by industry experts to match real-world trends, ensuring every concept and project builds job-ready, future-proof skills.

Personalized Career Support

Receive one-on-one mentorship, resume reviews, mock interviews, and complete placement assistance through our 500+ hiring partners to accelerate your tech career.

Expert Mentorship

Learn directly from certified professionals with years of hands-on experience who guide you through every module, project, and career milestone personally.

Real-World Projects

Gain practical exposure by working on live, industry-grade projects that mirror real business challenges, strengthening your technical execution and problem-solving abilities.

Proven Track Record

Join thousands of successful learners who have launched rewarding tech careers through Grras. Our consistent placement results, trusted partnerships, and alumni success stories speak for the quality of our training.

From Training to Placement A Roadmap to Success

Navigate your professional journey with a comprehensive guide that transforms learning into opportunity. Discover proven strategies to build skills, gain experience, and secure your ideal position in today’s competitive job market.

Building Strong Foundation

Expert Training sessions

Focus on industry-relevant skills

Hands on projects & Assignments

Real-world projects to implement learned concepts.

Performance Tracking

Weekly tests to assess progress
Sharpening Interview Readiness

Mock Interviews

Mock sessions with real-time feedback from experts

Expert Sessions

Host industry experts for advanced technical guidance

Skill Refinement Tasks

Focus on problem-solving, critical thinking, and domain expertise
Communication & Aptitude Skill Development

Effective Communication & Presentation Skills

Through interactive classes, students enhance both verbal and non-verbal communication, while also learning to present their ideas clearly, confidently, and effectively.

Aptitude & Logical Reasoning Training

Enhances students' problem-solving, analytical thinking, and numerical ability-preparing them for competitive exams and placement tests.
Resume building masterclasses

Step by step guidance

Help students structure professional, impactful resumes
Bridging the Gap

Industry networking

* Partner with top companies for hiring pipelines
* Conduct webinars and sessions with recruiters

Placement coordination

* Connect candidates to aligned opportunities
* Organize hiring events and recruitment drives
Advance interview boot camp

Stress Management Techniques

Equip students to handle high-pressure interview situations

Scenario-Based Training

Prepare students for various interview formats, including case studies, coding rounds, and group discussions
Personalized 1:1 guidance

Individual Sessions

* Address specific weaknesses and barriers to success.
* Develop personalized improvement plans

Expert Training sessions

Focus on industry-relevant skills

Hands on projects & Assignments

Real-world projects to implement learned concepts.

Performance Tracking

Weekly tests to assess progress

Mock Interviews

Mock sessions with real-time feedback from experts

Expert Sessions

Host industry experts for advanced technical guidance

Skill Refinement Tasks

Focus on problem-solving, critical thinking, and domain expertise

Effective Communication & Presentation Skills

Through interactive classes, students enhance both verbal and non-verbal communication, while also learning to present their ideas clearly, confidently, and effectively.

Aptitude & Logical Reasoning Training

Enhances students' problem-solving, analytical thinking, and numerical ability-preparing them for competitive exams and placement tests.

Step by step guidance

Help students structure professional, impactful resumes

Industry networking

* Partner with top companies for hiring pipelines
* Conduct webinars and sessions with recruiters

Placement coordination

* Connect candidates to aligned opportunities
* Organize hiring events and recruitment drives

Stress Management Techniques

Equip students to handle high-pressure interview situations

Scenario-Based Training

Prepare students for various interview formats, including case studies, coding rounds, and group discussions

Individual Sessions

* Address specific weaknesses and barriers to success.
* Develop personalized improvement plans

Our mission revolves around our learners

Promising 100% #CareerSuccess!

Download Placement Report

600+ Hiring Partners Across Industries

Our extensive network of hiring partners spans various industries, offering diverse opportunities to kickstart your career.

Please read the following instructions carefully before you begin the test.

The test consists of a set number of multiple-choice questions.
Each question has four options, out of which only one option is correct.
You must complete the test within the allocated time limit.
You will be awarded 4 marks for each correct answer.
There is no negative marking for incorrect answers.
Ensure you have a stable internet connection before starting the test.
Once you begin, the timer will start automatically, and you cannot pause or restart the test.

Why Take This Test? (How It Helps You)

🏆 Boost Confidence: Regular testing helps you build accuracy, reduce exam fear, and strengthen conceptual understanding.
🕒 Time Management: Learn to solve questions effectively under real-time pressure.
📊 Performance Insight: Identify your strong and weak areas for focused improvement.
🎯 Exam-Like Experience: Experience a realistic test environment with structured scoring.
📚 Smart Preparation: Refine your study strategy using feedback and detailed analytics.

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Frequently Asked Questions

Yes, you’ll learn directly from experienced AI professionals with 1-on-1 guidance.

Yes, live Q&A sessions, discussion forums, and mentor support are available.

Yes, join hackathons, webinars, and group discussions to grow your network.

Yes, course materials and updates remain accessible for continued learning.

Thousands of learners have successfully completed AI & Data Science programs with Grras Solutions.

You’ll get an industry-recognized AI & Data Science certification from Grras Solutions.

Yes, it’s globally recognized and strengthens your resume internationally.

You can become a Data Scientist, AI Engineer, ML Engineer, Generative AI Specialist, or NLP Engineer.

Yes, resume building, mock interviews, LinkedIn/GitHub optimization, and placement training.

Placement assistance is provided through our dedicated job portal & network, with a high success rate.

Projects like Generative AI Chatbot, Sentiment Dashboard, Anime Face Generator, and Business Reporting Tools.

Yes, all projects simulate real-world scenarios to strengthen your portfolio.

Yes, from data preprocessing to model deployment.

A decent system is enough; cloud-based solutions like AWS SageMaker are also used.

Yes, they are designed to be shared on GitHub and LinkedIn.

Both options are available – online live classes and offline sessions at Jaipur.

Yes, flexible timings are designed for students, working professionals, and career changers.

Yes, learners can choose formats as per their convenience.

Recorded sessions and backup classes are available.

Yes, sessions and assignments are structured for flexible, self-paced learning.

Primarily Python, along with libraries like NumPy, Pandas, and Matplotlib.

You’ll learn TensorFlow, PyTorch, Hugging Face, LangChain, and AWS SageMaker.

Yes, Natural Language Processing (NLP) with transformers, LLMs, and RAG is a key module.

Yes, including chatbots, GANs, and image-to-image conversion models.

Yes, you’ll deploy models using AWS SageMaker and similar tools.

This course covers Data Science, Machine Learning, Deep Learning, and Generative AI with practical industry projects.

Aspiring AI engineers, data analysts, Python developers, students, working professionals, entrepreneurs, and freelancers.

Basic Python helps, but it’s not compulsory. We teach fundamentals before moving to advanced AI.

It is a 180-hour program, designed for in-depth learning and project-based training.

It blends theory, real-world projects, expert mentorship, and placement support, making you industry-ready.