Generative AI Training Course

Mastering Generative AI for Tomorrow’s Innovations with Agentic AI and RAG Applications.

What you'll learn

Hands-on coding skills to implement AI & ML models.
Supervised, unsupervised & reinforcement learning techniques.
Understand statistics, probability, and optimization for building AI systems.
Build deep learning models for text, images, and structured data.
Create NLP applications like chatbots, sentiment analysis, and text classification
Develop CNN models for computer vision, image recognition, and object detection.
Use Generative AI to create text, images, and intelligent content
Work with popular Large Language Models such as GPT, Gemini, Llama, and Groq.

Explore access and fine-tune open-source AI models.
Build AI-powered workflows & intelligent applications.
Advanced methods like chaining, PEFT, RAG & context optimization.
Design autonomous AI agents for decision-making & automation.
Create Retrieval-Augmented Generation (RAG) applications for real-world use cases
Build AI agents & workflows without programming.
End-to-end applications combining ML, GenAI & AI Agents.

Our Training Process

Practical Session

Assignment

Projects

Be Job Ready

Interview Preparation

Resume Building

Key Highlights

Personalised career coach
90% Practical Training
Certification
100% Placement Assistance
Study material
Instant doubt solving
Mock Interviews
Case studies and Projects

Generative AI Training Course

Python Fundamentals

Python Basics: Syntax, Variables, Data Types
Input and Output Operations
Operators and Expressions
Conditional Statements
Loops
Data Structures: Lists, Tuples, Sets, Dictionaries
Comprehensions and Iterations
Hands-On Exercises: Scripts, condition checks, sorting data, dictionary

File Handling & Data Wrangling with NumPy

Reading & Writing Files
CSV Parsing
Error Handling
NumPy Arrays & Operations
Indexing, Slicing, Reshaping
Mathematical & Aggregation Functions
Multi-Dimensional Arrays
Hands-On Exercises: File parsing, CSV analytics, NumPy statistics

Data Analysis with Pandas

Pandas DataFrames & Series
Loading Data (CSV, Excel, SQL)
Filtering, Sorting, Grouping
Handling Missing Data
Data Cleaning & Transformation
Date & Time Handling
Merging & Joining DataFrames
Hands-On Exercises: Sales analysis, data cleaning, merging datasets

Exploratory Data Analysis & Visualization

Descriptive Statistics
Matplotlib & Seaborn Visuals
Correlation Analysis
Outlier Detection
Advanced Visualizations
Multi-Panel Charts
Hands-On Exercises: EDA reports, heatmaps, dashboards

Advanced Data Management & Databases

SQLAlchemy Basics
ORM Queries
SQL to Pandas Integration
Writing Data Back to Databases
Views, Stored Procedures, Optimization
Hands-On Exercises: Database analytics & reporting

Statistics for Data Analytics

Univariate, Bivariate & Multivariate Analysis
Distributions & Probability
Hypothesis Testing
Confidence Intervals
Correlation & Covariance
Inferential Statistics
Hands-On Exercises: Statistical analysis using real datasets

Introduction to Machine Learning

ML Concepts & Use Cases
Supervised vs Unsupervised Learning
Regression & Classification
Forecasting
Hands-On Exercises: Churn analysis & fraud analysis

ML with Scikit-Learn

Regression modeling
Feature scaling
Model evaluation
K-Means clustering
Hands-On: House price prediction, model optimization

Supervised & Unsupervised ML

Linear & logistic regression
Decision trees & random forests
SVM, KNN
PCA & LDA
Hands-On: Stock prediction, customer segmentation

Deep Learning Foundations

Neural networks
TensorFlow & PyTorch setup
Tensors & computation graphs
Basics of building and training models
Hands-On: Build basic neural networks, Visualize computation graphs in TensorFlow

Deep Neural Architectures

Artificial Neural Networks (ANN)
Convolutional Neural Networks (CNN)
Recurrent Neural Networks (RNN)
Transfer learning
Hands-On: ANN, CNN & RNN implementations

Advanced Neural Networks

Long Short-Term Memory Networks (LSTM)
Graph Neural Networks (GNN)
Advanced Recurrent Architectures: Bidirectional RNN, GRU
Hyperparameter tuning
Hands-On: Time-series & graph models

NLP & Text Analytics

Introduction to NLP concepts
Text preprocessing
Tokenization & stemming
NLTK
Text classification
Sentiment analysis
Hands-On: Spam & sentiment models, Preprocess a text dataset using NLTK, Build a text classification model, Experiment with a text generation model

Foundations of Generative AI

Evolution of Generative AI: From ML to LLMs
Transformer architecture: Attention, encoder-decoder, self-attention
Types of LLMs: GPT, BERT, T5, Falcon, Claude
Closed-source vs Open-source models

LLMs, Prompt Engineering & OpenAI
Integration

Prompt engineering
Understanding Chat, Completion, and Instruction-tuned models
Prompt Engineering techniques: Few-shot, zero-shot, chain-of-thought
OpenAI API: Usage, tokens, parameters
API integration with Python
Fine-Tuning & Customizing LLMs
Instruction tuning using domain-specific data
Use case: Creating a healthcare/legal/HR domain assistant
Best practices & deployment considerations

RAG Applications

RAG architecture
Text chunking, embedding models, similarity search
Use cases: Document Q&A, PDF bots, private chatbots
Combining LLMs with external knowledge

Vector Databases & Embeddings

What is a Vector DB
Choosing the right Vector DB (FAISS vs Pinecone vs Weaviate)
How embedding models work
Storing, indexing, and retrieving large document

Build AI Agents using LangChains

What is an AI Agent?
LangChain Agent architecture
Adding tools: search, calculator, DB access, email
Memory integration: BufferMemory, SummaryMemory
Build chatbots that reason and act

Multi-Agent Systems & LangGraph

Introduction to LangGraph for stateful workflows
Nodes, edges, state sharing
Multi-agent collaboration (e.g., PM → Dev → Analyst agents)
Conditional workflows, retries, and dynamic decision-making
Use cases: Autonomous workflows, research agents, AI coworkers

Deploying Generative AI & Agentic
Applications

FastAPI / LangServe to deploy your solution as an API
Build UIs using Streamlit / Gradio
Deployment platforms: Vercel, AWS, Streamlit Cloud
Logging, monitoring, human-in-the-loop workflows

MLOps with GCP

Introduction to MLOps
MLOps vs. DevOps
SDLC Basics
What is Cloud Computing
GCP Introduction

Version Control System

Git Essentials
Configuring Git
Branching
Git Workflow
Repo
Git Commands
Tracking and managing changes to code
Source Code Management
Tracking and Saving Changes in Files

CI/CD for ML Models

Introduction to CI/CD
CI/CD Challenges
CI/CD Implementation in ML
Popular DevOps Tools

Docker & Kubernetes for ML Deployment

Docker Architecture
Docker for Machine Learning
Continuous Deployment
Writing a Dockerfile to Create an Image
Installing Docker Compose
Configuring Local Registry
Container Orchestration
Application Deployment
Kubernetes Core Concepts

MLOPS with AWS SageMaker

Uploading datasets and training models in the cloud
Hosting real-time and batch endpoints
Autoscaling, monitoring, and billing control

End-to-End GenAI & RAG Projects for Data Scientists

Intelligent Agentic Ai Personal Assistant
Customer Support App
AI Resume Analyser
Product Recommendation System for Ecommerce
Social Media Sentiment Analysis and Trend Prediction/li>
Automated Model Deployment and Monitoring for
Customer Churn

Skills you will gain

Machine Learning Python Generative AI NLP Deep Learning RAG LLMs Agentic AI AI Agents GPT Hugging Face Data Science

Course Certification

Become a Certified Generative AI Expert with TryCatch Classes and enhance your career prospects to the next level.

This certificate serves as an official badge of your successful Machine Learning training course completion, highlighting your expertise.

Students Testimonial

Students Reviews

TryCatch Classes offers an excellent learning environment. All the teaching staff is exceptional. As a newcomer to web development, all concepts were explained clearly.

dnone

Full Stack Developer
Company

Hi my name is Bhagyashri Gunjate. I have completed full stack web development course from Trycatch and saying this happily that I also got my first job from TryCatch. Although I have gap of 4 years after completing my engineering Mohnish and Mehul Sir gave me confidence that I can do it and at this age also I can be succeed in web development field. Talented and passionate faculty helps me to resolve my query and made my base and logic strong. They initiated new ways of thinking to improve project query and my personal performance as well. Also this helped me to improve my speed to produce codes faster and get things done more accurately. Mehul Sir and Monish Sir was so helpful that they always kept my motivation and confidence high. They gave me projects that are more skilful and as per industry standards which directly helps me to get my first job journey. I highly recommend Try Catch classes to everyone who wanted to upscale their knowledge and career in Web Development field.

dnone

Full Stack Developer
Company

Jane Doe

Software engineer
Ola

Jane Doe

Software engineer
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Jane Doe

Software engineer
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Jane Doe

Software engineer
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Genuine reviews for our Generative AI Training Course

Darshan

Machine Learning Engineer

First and foremost, I was thoroughly impressed with the quality of education, it was on point of my expectations. They were able to break down complex concepts into easily digestible pieces, and their explanations were always clear and concise. Also every faculty present there is the industry expert himself.I also appreciated the emphasis that Try Catch Tech placed on hands-on learning. Rather than simply lecturing about the topic, the classes provided ample opportunities to put theory into practice. This approach not only helped me understand the concepts better, but it also gave me a sense of confidence when working with these technologies.Another aspect of Try Catch Tech that stood out to me was the supportive community that surrounded the classes. From fellow students to instructors, everyone was incredibly encouraging and willing to help each other out. This made for a collaborative learning environment that I truly appreciated. And their support is so much that even after completing my course I was always welcomed to sit and study there in the classes.Overall, I would highly recommend Try Catch Tech to anyone looking to learn anything from the course they offer. Personally I did python and machine learning which was a great experience for me. The quality of instruction, hands-on learning opportunities, and supportive community make it an excellent choice for both beginners and experienced programmers alike. Thank you, Try Catch Tech, for a wonderful learning experience!

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Sudarshan Paranjape

Machine Learning Engineer

I completed TryCatch Group’s Data Science course, and it was an enlightening journey! The comprehensive curriculum covered essential topics, and the instructors were knowledgeable and approachable. Hands-on projects boosted my confidence, and provided ample resources. The supportive team promptly addressed queries, and industry case studies enriched the experience. The mentorship provided by Mohnish sir and Mehul sir was truly exceptional! Their expertise and passion for data science shone through in every aspect of the course. Highly recommended for all skill levels, this course lays a strong foundation for a successful data science career. Thank you, TryCatch Group, for this amazing learning opportunity!

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Mansi Rathod

Machine Learning Engineer

I wanted to go to USA to do my Masters in Data Science. So I joined Trycatch and completed the Data Science course at TryCatch. Anyone who’s willing to pursue Data Science in the future but has no to little knowledge about it, this class will definitely help you enhance your knowledge. Mehul and Mohnish being knowledgeable, will be there to guide you whenever needed. Overall experience was really good so I would definitely recommend this course.

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Google

Mansi Rathod

Machine Learning Engineer

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Jamil Shaikh

Machine Learning Engineer

I have done Data Science course from Trycatch Classes. I would recommend this course as it gives good idea about the field also the staff are friendly and helpful. This course has helped me to understand my subjects easily.

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Google

Jamil Shaikh

Machine Learning Engineer

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Google

Sujwal Shetty

Machine Learning Engineer

I had taken Python+ ML course here. The overall experience was very good, I got the internal switch to Data Science domain which i was looking for in my organisation. The faculty had great knowledge within the subject.

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Google

Pankit Rojasra

Machine Learning Engineer

In my experience, this class is hands-down the best option if you’re interested in a career in IT or computer coding. I completed the Data Science course here, and I can say all the faculty are highly knowledgeable, experienced, and effective instructors. Following the course, I secured an internship in the backend field with an insurance company.

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Google

Software Developer

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Google

Software Developer

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Google

Software Developer

lorem

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Student's Portfolio

UX-UI Designer

Mansi Sanghani

UX-UI Designer

Mansi Sanghani

UX-UI Designer

Mansi Sanghani

UX-UI Designer

Mansi Sanghani

UX-UI Designer

Mansi Sanghani

UX-UI Designer

Mansi Sanghani

UX-UI Designer

Mansi Sanghani

UX-UI Designer

Mansi Sanghani

UX-UI Designer

Mansi Sanghani

UX-UI Designer

Success Stories

Frequently Asked Questions (FAQs)

What is the duration of the course?

Total duration is approximately 4 months along with Live Projects.

Is there 100% Placement Guarantee after the course is over?

We provide 100% placement assistance in our Deep Learning & Generative AI training course in Mumbai.

Are there any prerequisites before starting Generative AI?

It is required to know Python before starting this Deep Learning & Generative AI in Mumbai.

Who teaches Generative AI?

At TryCatch, our team consists of seasoned experts with over 15 years of experience. A skilled Data Scientist will be guiding students, encouraging them to ask questions without hesitation, and enabling us to effortlessly address all your inquiries.

Is the course Online or Offline?

This Deep Learning & Generative AI course is available offline & online both. You may choose whatever is feasible for you.
Offline course can be done at our Borivali Branch in Mumbai.
Online Live Course can be done on Zoom.

Who can learn Deep Learning & Generative AI?

This course is designed for everyone, even if you’re studying Commerce, Arts, or Mechanical subjects, or if you’re still in school. It doesn’t matter what your background is, you can definitely learn this course.

Do I need prior experience inDeep Learning & Generative AI?

No, prior experience is not required.

What software and tools do I need for this course?

All the tools required for this training will be installed during the course

Will I receive a certificate upon course completion?

Upon completion of the course, you will receive an official global Deep Learning & Generative AI. This certificate serves as an official badge of your successful course completion, highlighting your expertise.

Can I interact with instructors and ask questions during the course?

Absolutely! Our instructors are always available to answer all your questions and solve your doubts.

Are there any real-world projects or case studies in the course?

Yes, we incorporate real-world projects and case studies into the course to help you apply what you’ve learned in practical scenarios.

Is there a money-back guarantee if I’m not satisfied with the course?

We offer a satisfaction guarantee. If you are not satisfied with the course within a specified timeframe, you can request a refund.