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Regex Software

Machine Learning & Deep Learning Program

(Batches Start in November, December 2025 & January 2026)

About The Program

With the belief to build a healthy ecosystem as per the Industry Standards REGex Software brings an  Industrial Training/Internship Program on “Machine Learning and Deep Learning”. We organize Machine Learning and Deep Learning  Industrial Training/Internship Program for improving the knowledge and skills of the Students/Professionals, so that they can become specialized in the field of Machine Learning and get their Dream Job in Software Development Field in Big MNCs.

REGex Software Services’s “Machine Learning and Deep Learning” program is a valuable resource for beginners and experts. This program will introduce you to Python, Machine Learning, Deep Learning etc. from Basics to Advance. If you want to become Machine Learning Expert, REGex introduce this program for you.

Key Benefits & Perks

  • Get Summer Internship Offer Letter
  • Need to Spend Min. 5 hours with REGex
  • Get Internship Project Completion Certificate
  • No Previous Knowledge Required
  • Get Summer Training Certificate
  • Get Performance based Letter of Recommendation (LOR)

November Batches Dates

Batch 1: 03rd November 2025
Batch 2: 10th November 2025
Batch 4: 17th November 2025
Batch 4: 24th November 2025

December Batches Dates

Batch 1: 01th December 2025
Batch 2: 08th December 2025
Batch 3: 15th December 2025
Batch 4: 22th December 2025

January Batches Dates

Batch 1: 05th January 2026
Batch 2: 12th January 2026
Batch 4: 19th January 2026
Batch 4: 26th January 2026

Weekly Duration

Location

Participants

20 Hours Per week

Physical (Jaipur)
or 
Online (Google Meet)
25 – 30 per Batch

What you will Learn

Python

Machine Learning

Deep Learning

Generative Ai

Study Material

  • E-Notes
  • Assignments & Poll test
  • 100+ hours on demand Live Video Lectures
  • Access of Recordings & Study Material
  • Mentorship Support
  • Work on multiple Minor Projects & Use Cases
  • Work on Live Projects

Output

  • Able to think out of the box
  • Become expert in multiple technology domains like: Python, Machine Learning, Deep Learning
  • Understand working of ML models deployment with AWS
  • Build projects on multiple technology domains
  • Work on Use CASES & Projects
  • Learn to deploy your models on AWS Sagemaker or Google cloud Platform

Why Choose Us

Live Sessions

Live Sessions by Expertise Trainers and Access of Recorded Session is also available.

Live Projects
Get a chance to work on Industry Oriented Projects to implement your learning.
24*7 Support
24*7 Mentorship Support available for all Students to clear all of your doubts.
Opportunities
REGex provides Internship / Job opportunities to the best Students in different Companies.

Placed Students//Partnership

amazon
wipro
capgemini
google
microsoft
myntra
paytm
ibm
Cognizant
infosys
intel
hcl
hp
honeywell
oracle1
dell
fractal
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What People Tell About Us

Best IT Training and Internship Company in Jaipur. Highly recommended. Supportive faculties, Management, online and offline sessions access with recording access help every student to concentrate more on learning. Practical Learning and working on live projects with team is a main key highlights of REGEX.

Drishti Khandelwal Ex-Student, Django Batch

The experience of learning in the Institute is really good. I've joined the MERN full stack course doing well. Thanks to the mngt. To provide certified facility. Very helping in solving my queries and Institute provide me to practical knowledge and demo project to improve my skills..... Thnks to Regex software service

Gulshan S Arya Ex-Student, Mearn Stack

This training center is exceptional, providing me with extensive knowledge in various domains and technologies. I enrolled in the Python Django course eight months ago, where I learned website development. Prior to joining this coaching, I struggled with speaking English, but now I have gained the ability to communicate effectively. My experience has been extremely positive, and I strongly recommend joining The Regex Software Services at the earliest opportunity.

Mohit Sharma Ex-Student, python django

Competitive Programming is the best course they have - i am part of both python and C++ course. Cracked several interviews with their course, poll test & assignment are always new and beneficial. Best CP course you will find here, i hope this will be beneficial for you

Yaman Singh Ex-Student, CP Batch

Tushar sir is best in delivery. His approach is mind blowing. I have not found any gap although I am from U.S Lots of Big Data tools I have learnt like Hadoop, Hive, Spark, Sqoop & most amazingly Talend ETL Tools which was the most lovely part of training. every component is told in very simple terms with great practical approach

Josh Well Ex-Student, BigData Batch

I recently joined Python Django(Web Development - Full Stack)Course About Course: - I must say instructor makes every concept simple to understand - No Copy Paste,Every line of code is explained - Even given Assignments to work on - Even given Projects to work on If you looking to learn Python Django I highly recommend to go for this course

Salman Khan Ex-Student, Django Batch

I am from UK & loved the teaching. Competitive Programming was the best experience I had in coding. I can truly say the money I spend is worth it. Go for it guys!!

Jack Ryan Ex-Student, CP Batch

Placed Students

Gunjan Saini National Instruments
Gunjan Saini
National Instruments
Prem Wipro & IBM
Prem
Wipro & IBM
Purnima ponrajkumar Indium software
Purnima ponrajkumar
Indium software
sonal Wipro
sonal
Wipro
Mohammad Atash Shaikh Wipro
Mohammad Atash Shaikh
Wipro
Ayush Kumar srivastava Sopra
Ayush Kumar srivastava
Sopra
Sourav Dash Tek System
Sourav Dash
Tek System
Simran Khatri Techmatrix jaipur
Simran Khatri
Techmatrix jaipur
Madhav Sharma Cognizant
Madhav Sharma
Cognizant
Rajkishor. P. Game Redington India Ltd
Rajkishor. P. Game
Redington India Ltd
Bhuvan Nucleus software
Bhuvan
Nucleus software
Akshay Kachave Talent Sikha
Akshay Kachave
Talent Sikha
Vasavi Uppala NCR coperation
Vasavi Uppala
NCR coperation
Ashish Chauhan wipro
Ashish Chauhan
wipro
Pratik Choubey TCS
Pratik Choubey
TCS
Debarya Pal Accenture
Debarya Pal
Accenture
Vritika Vijay Kamra Larsen and toubro infotech
Vritika Vijay Kamra
Larsen and toubro infotech
Mihir Vatsa Infosys
Mihir Vatsa
Infosys
Divyansh Singh Sengar Infosys
Divyansh Singh Sengar
Infosys
Harsha Kumari Bank Of America
Harsha Kumari
Bank Of America
Vatan Gupta Accenture
Vatan Gupta
Accenture
Fardeen Khan Deloitte us
Fardeen Khan
Deloitte us
Divyanshi jain Deloitte
Divyanshi jain
Deloitte
Hritick goyal Ranjio
Hritick goyal
Ranjio
Sumodh c Sabu TCS
Sumodh c Sabu
TCS
Swati Accenture
Swati
Accenture
Nishant Kumar cognizant
Nishant Kumar
cognizant
Saquib Mansuri Circulants
Saquib Mansuri
Circulants
Dhanisha sharma TCS
Dhanisha sharma
TCS
Aditya Prasad Capgemini
Aditya Prasad
Capgemini
Sathvika Chekuri Barclays
Sathvika Chekuri
Barclays
Priyanshu Lasod Barclays Arcgate
Priyanshu Lasod
Barclays Arcgate
Jaya Mendhe Accenture
Jaya Mendhe
Accenture
Dipali Jp Morgan Chase & Co.
Dipali
Jp Morgan Chase & Co.
Meenal Hewlett-Packard
Meenal
Hewlett-Packard
Riya Khanna HSBC
Riya Khanna
HSBC
Muskan Hewlett-Packard
Muskan
Hewlett-Packard
Praveen Jangid Celebal Tech
Praveen Jangid
Celebal Tech
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Course Content

Python

  • What is Python?
  • History and evolution of Python.
  • Python’s popularity and use cases.
  • Setting up Python (installation).
  • Running Python scripts and using the interactive shell.
  • Arithmetic Operators(+,-,*,/,//,%,**)
  • Comparison / Relational Operators (== ,!=)
  • Assignment Operators
  • Logical Operators
  • Bitwise Operators
  • Identity Operators
  • Conditional statements (if, elif, else).
  • Looping structures (for and while loops).
  • Iterating through sequences (lists, strings, dictionaries).
  • Range and enumeration.
  • Using break and continue.
  • Lists: creation, manipulation, and methods.
  • Tuples: creation, immutability, and uses.
  • Dictionaries: key-value pairs and operations.
  • Sets: unique elements and set operations.
  • List comprehensions.
  • Problem Solving on LeetCode question
  • What is a Function?
  • Types of Functions
  • Function Syntax (Structure)
  • Function Calling
  • Parameters vs Arguments
  • Scope and lifetime of variables.
  • Importing modules.
  • Creating and using custom modules.
  • What is a Module?
  • Types of Modules
  • Why Use Modules?
  • Importing Modules
  • What is a Package?
  • Why Use Packages?
  • Namespace Management
  • Popular Python Packages (numpy, pandas, flask, django, requests, matplotlib, etc.)
  • Reading from and writing to files.
  • Working with different file modes (read, write, append).
  • Using context managers with files.
  • Handling errors with try and except.
  • Raising exceptions.
  • Handling multiple exceptions.
  • Using the ‘finally’ block.
  •  
  • Classes and objects.
  • Attributes and methods.
  • Inheritance and encapsulation.
  • Polymorphism and method overriding.
  • Constructors and destructors.
  • NumPy basics & array manipulations
  • Pandas Series, DataFrames, indexing, merging,
    – Grouping
  • Matplotlib & Seaborn (basic plots, customization)
  • Real-world case studies.
  • Job opportunities and career paths.
  • Contributing to open-source projects.
  • Staying up to date with Python developments.

Machine Learning

  • Machine learning applications
  • ML vs DL
  • Basics of Python [Syntax]
  • Working with Pandas, Numpy & Matplotlib
    ■ Working with Missing Data
    ■ Data Grouping
    ■ Data Subsetting
    ■ Merging & Joining Data Frames
  • Importing Libraries & Datasets
  • Munging & handling missing data
  • Splitting the dataset into Training set & Test set
  • What is actual machine learning
  • Various Aspects of Data – type, Variables & Category
  • Machine Learning & its Various types
  • About Supervised & Unsupervised Learning
  • Understanding Simple Linear Regression
  • Understanding the P -Value
  • Support Vector Regression
  • K nearest neighbours
  • Logistic regression
  • Naive Bayes
  • Decision trees
  • Random forests
  • Bagging Boosting
  • Maximum likelihood classifier
  • Support vector machines

  • Principal Component analysis (PCA – Theory)

  • PCA with Case-Study

  • Linear Discriminant Analysis(LDA) for Dimension Reduction

  • Feature Selection to Select the Most Relevant Predictors

Deep Learning

  • NLP Intuition

  • Types of NLP

  • Classification vs Deep Learning Models

  • The Neuron

  • Activation function

  • How Neural network work & learn by itself

  • Gradient Descent

  • Stochastic Gradient Descent

  • Ethics of Deep Learning

  • What are convolutional neural networks [CNN] ?

  • CNN Architecture

  • CNN Code preparation

  • Recurrent Neural Networks

  • Several layers

    ■ ReLLu Operation

    ■ Pooling

    ■ Flattering

    ■ Full Connection

  • Statistics

  • Sample Selection

  • Probability Theory

  • Hypothesis

  • Model Relationship

  • Model Fit

  • Descriptive Statistics

  • Types of Data

  • Qualitative Data

  • Histograms

  • Different Plots

  • Centrality and Spread

  • Outliers

  • Median, Mean, Mode

Generative AI

  • Introduction to Generative AI
  • Applications of GenAI:(Text generation, Image generation,Code generation)
  • Evolution of GenAI(From GANs to Transformers and beyond)
  • Introduction to RAG,Retriever,Generator
  • RAG ARCHITECTURE(Input query processing,Retrieval phase,Fusion of retrieved information with the LLM,Response generation)
  • Types of RAG models(RAG-Sequence,RAG-Token)
  • Project(Customer support bots with real-time information retrieval)
  • Introduction to Vector Databases , Key concepts(Vectors and embeddings,High-dimensional space representation)
  • Core Concepts(Indexing and searching vectors,Scalability challenges,Vector quantization techniques)
  • Popular Vector Databases(FAISS (Facebook AI Similarity Search),Milvus,Weaviate)
  • Transformer architecture:(Encoder and Decoder blocks, Multi-Head Attention,Scaled Dot-Product Attention,Positional Encoding)
  • Gemini architecture and its key features , Differences between Gemini and other LLMs (e.g., GPT, BERT)
  • Use cases of Gemini(Multimodal AI (text, images, audio),Content creation, Code generation and debugging)
  • APIs and Tools for Gemini:(Accessing the Gemini API, Authentication and integration)
  • Project (Create Chabot and Deploy it on Streamlit Cloud)
  • Agentic AI Using LangChain and LangGraph project(Business Start up Idea using current businesses in India )

Computer Vision

  • What is computer vision & its application
  • Face Detection ■ Adding more features & Categorization ■ Object Detection & Image creation ■ Working with Images & vectors
  • Facial Expression Recognition in Code (Binary / Sigmoid /Logistic Regression)
  • Object detection
  • Neural style transfer
  • YOLO
  • RCNNs
  • Resnet 50
  • Tensorboard
  • What are Vectors
  • Working with word Analogy
  • Text Classification
  • Pre Trained word vectors from word2vec
  • Language Models
  • Introduction to Tensorflow / Keras
  • Most used right now
  • Resources gathering
  • Keras dealing with Missing Data
  • Dealing with Categorical data

Model Deployment & Project

  • Create your own ML models
  • Deploy ML models
  • AWS Recognition
    • Titanic Classification
    • Carbon Emissions
    • Car price analysis
    • Drug Prediction
    • Hand written Digit Recognition
    • CIFAR 10
    • CIFAR 100
    • Cats vs dogs
    • Intel scene Classification
    • Transfer Learning
    • Object Detection

 Note: Content may Subject to Change by REGex as per Requirement

Download Program Brochure

Extra Sessions

Additinal Session on GIT, Linux, Docker, AWS Basics, Jenkins and many more for all students.

Projects you will work on

Live Client Projects With Development Team Under The Guidance Of Mentor
Project Use Cases

Fee Structure

Indian Fee (Physical)

Price: ₹75,000/- (Flat 66% off) => ₹25,000/-  
(Limited Period Special Offer)

Indian Fee (Online)

Price: ₹75,000/- (Flat 66% off) => ₹25,000/-  
(Limited Period Special Offer)

International Fee

Price: $1200 (Flat 66% off) => $400
(Limited Period Special Offer)

Fee Can be Paid as No Cost EMI of 6 Months @2500/Month.

Cashback Policy

  • You will get your Unique Referral Code after successful paid registration.
  • You will get Upto ₹1000 Cashback directly in your account for each paid registration from your Unique Referral Code (After Closing Registrations of this program) .
  • For Example:- If we received 10 paid registration from your Unique Referral Code then you will receive Upto ₹1000*10 = ₹10,000.
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(Batches Start from November, December 2025 & January 2026)

*It will help us to reach more
*Extra off is applicable on 1 time payment only. Seats can be filled or Price can be increased at any time. Refund policy is not available*