ML & DL Specialization With Python D-Jango

(Batches Start from April, May, June & July 2024)

About The Program

With the belief to build a healthy ecosystem as per the Industry Standards REGex Software brings a Training/Internship Program on “Machine Learning and Deep Learning With Python D-jango”. We organize Machine Learning, Deep Learning and Python D-jango 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 With Python D-jango” program is a valuable resource for beginners and experts. This program will introduce you to Python, Machine Learning, Deep Learning, HTML, CSS, JS, Django: – Function and Class Based Views, URL routing, Models, Rest-APIs etc. from Basics to Advance. If you want to become Machine Learning Expert, REGex introduce this program for you.

April Batches Dates

Batch 1: 10th April 2023
Batch 2: 17th April 2023
Batch 3: 24th April 2023

May Batches Dates

Batch 1: 5th May 2023
Batch 2: 12th May 2023
Batch 3: 22nd May 2023

June Batches Dates

Batch 1: 2nd June 2023
Batch 2: 12th June 2023
Batch 3: 23rd June 2023

July Batches Dates

Batch 1: 3rd July 2023
Batch 2: 10th July 2023
Batch 3: 21st July 2023

Weekly Duration

20 Hours Per week

Location

Physical (Jaipur)
or 
Online (Google Meet)

Duration

6 Months

Participants

25 – 30 per Batch

What you will Learn

Python

Duration: 25 - 30 Hours

Machine Learning

Duration: 35 - 40 Hours

Deep Learning

Duration: 35 - 40 Hours

Html

Duration: 25 - 30 Hours

Css

Duration: 35 - 40 Hours

Css

Duration: 35 - 40 Hours

Javascript

Duration: 35 - 40 Hours

Database

Duration: 35 - 40 Hours

D-Jango

Duration: 35 - 40 Hours

Study Material

  • E-Notes.
  • Poll Test & Assignments .
  • Over 300+ hours of Live Video Lectures available on demand.
  • Accessing lecture videos and notes.
  • 24*7 Mentorship Support
  • Engaging in real-time project assignments

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

What People Tell About Us

Placed Students

Course Content

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

  • Confusion matrix
  • Accuracy Paradox
  • CAP Curve
  • K-Mean Clustering Intuition
  • K-Mean selecting Numbers of Cluster
  • About Reinforcement Learning

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

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 & Projects

  • 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

Python D-jango

● HTML Level One Introduction
● HTML Part One Basics
● Basic Tagging
● Paragraph, Styles, Formating, Quotation, Lists
● Color, Links, Images Divs and Spans
● Blocks & Inline, Ids, Classes, Attributes
● Tables, IFrames
● Forms Basics, Input types and Attributes
● Form Elements and Labels
● Forms and Selections
● Some Advanced Topics

  • Introduction
  • Inline, Internal, External  CSS
  • The Anatomy of CSS Syntax
  • CSS Selectors
  • Classes vs. Ids
  • What Are Favicons?
  • Color, Background, Padding
  • Border, Margin, Box, Model
  • Outline, Text, Icons
  • Position, Float, Opacity
  • Creating Navigation
  • Creating Dropdown
  • CSS Forms, Counters
  • Website Layout
  • Bootstrap Introduction
  • Bootstrap Grid Layout System
  • Bootstrap Containers
  • Colors, Buttons, Table, Jumbotron, Containers
  • The Bootstrap Carousel
  • Alert, Badges, Spinner, Lockdown
  • Input Groups, Nav Bar, Dropdown
  • Bootstrap Cards
  • The CSS Z-Index & Stacking Order
  • Media Query Breakpoints
  • Advanced CSS – Combining Selectors
  • Advanced CSS – Selector Priority
  • Introduction
  • Basics, Connecting Javascript, Data Type, Solutions, Operators, Control Flow
  • Javascript Variables
  • Naming and Naming Conventions for Javascript Variables
  • String Concatenation
  • String Lengths and Retrieving the Number of Characters
  • Basic Arithmetic and the Modulo Operator in Javascript
  • Conditions, Boolean, Comparison
  • Loops, Regular Expressions
  • Closures, Callbacks, and Recursion
  • Document Object Model (DOM)
  • Selecting HTML Elements with Javascript
  • Manipulating and Changing Styles of HTML Elements with Javascript
  • The Separation of Concerns: Structure vs Style vs Behaviour
  • Manipulating HTML Element Attributes
  • Adding Event Listeners to a Button
  • Higher Order Functions and Passing Functions as Arguments
  • Objects, their Methods and the Dot Notation
  • Understanding Callbacks
  • Adding Animation to Websites

● Introduction
● Angular Fundamentals
● Display Data and Handling Events
● Building Reusable Components
● Directives
● Template Driven Forms
● Consuming HTTP Services
● Routing and Navigation

● Introduction and Set-Up
● Numbers, Strings
● Lists, Tuple, Sets & Dictionaries
● Conditions, Loops, Operators
● Functions, Iterator, Scope
● Object Oriented Programming
● Modules and Packages
● Decorators
● Some Libraries – Important for Python

● Django Installation and Configuration
● MVC Applied to Django and Git
● Basic Views, Django Command Overview

• First View: Dynamic Content
• Mapping URLs to Views
• Processing a Request
• URL configurations and Loose Coupling
• 404 Errors
• Second View: Dynamic URLs
• A Word About Pretty URLs
• Wildcard URL patterns
• Django’s Pretty Error Pages

• Template System Introduction
• Creating & Rendering Template Objects
• Multiple Contexts, Same Template
• Basic Template Tags and Filters Tags
• Using Templates in Views
• Template Loading
 get_template()
• The include Template, Template Inheritance Tag

• Defining Models in Python
• Installing the Model
• Basic Data Access
• Adding Model String Representations
• Inserting, Filtering & Updating Data
• Selecting Objects
• Retrieving Single Objects
• Ordering & Slicing Data
• Deleting Objects
• Making Changes to a Database Schema
• Adding Fields
• Removing Fields
• Removing Many to Many Fields
• Removing Models

  • Introduction to Admin
    • Admin Templates
    • Ordering Fields
    • Adding Search
    • Adding Filters
    • Adding Fields
    • Editable List View
  • Creating a User Authentication
    • Setting Up A Simple User Authentication System
    • Login and Session Variables
    • Cookies
    • Permissions
    • Social Registration
    • Form Validation
  • Frontend
    • URL Template Inheritance
    • Template Filters and Custom Filters
    • Template Language and Static Files
    • Twitter Bootstrap Integration
    • Static File Compression and Template Refactoring
  • Upload Image
    • Add Pillow requiremen
    • Modify recipe model
    • Add tests for uploading image to recipe
    • Add feature to upload image
  • Preparing The Storefront
    • Product Display
  • Adding a Shopping Cart
    • Images
    • Dynamic Content/Page Creation
  • Payment Gateway
    • PayPal Integration / Paytm / Google Pay / PhonePe

• Search
• Creating a Feedback Form
• Processing the Submission
• Custom Validation Rules
• A Custom Look 
• Creating Forms from Models

• URL configuration Tricks
• Streamlining Function Imports
• Using Multiple View Prefixes
• Special-Casing URLs in Debug Mode
• Using Named Groups
• Understanding the Matching/Grouping Algorithm
• Passing Extra Options to View Functions
• Using Default View Arguments
• Special-Casing Views
• Capturing Text in URLs
• Including Other URL configurations
• Captured Parameters Working with include()
• Extra URL configurations Options Working with include()

• Using Generic Views
• Generic Views of Objects
• Extending Generic Views
• Making “Friendly” Template Contexts
• Adding Extra Context
• Viewing Subsets of Objects
• Complex Filtering with Wrapper Functions
• Performing Extra Work

● Serializers, views and URL
● Creating API and Web ServiceS
● Working on POSTMAN
● GET
● POST
● PUT
● DELETE
● PATCH
● Testing our API

  • Introduction
  • Application Deployment

Extra Sessions

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

Fee Structure

Indian Fee

Price: ₹59,999/- (Flat 75% off) => ₹25,000/-  
(Limited Period Special Offer)

International Fee

Price: $1200 (Flat 75% off) => $300
(Limited Period Special Offer)

Fee Can be Paid as No Cost EMI @2500/Month

Cashback Policy

  • You will get your Unique Referral Code after successful paid registration.
  • You will get ₹2000 Cashback directly in your account for each paid registration from your Unique Referral Code on monthly basis(After Closing Registrations of this program) .
  • For Example:- If we received 10 paid registration from your Unique Referral Code then you will receive ₹2000*10 = ₹20,000 on monthly basis.
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(Batches Start from April, May, June & July 2024)

*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*