DataScience - ML & DL

About The Program:

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

REGex Software Services’s “DataScience – Machine Learning & Deep Learning” course is a valuable resource for beginners and experts. This course will introduce you to Classification, Clustering Algorithm and Working on Object Detection & Image Recognition from Basics to Advance. If you are preparing for a coding interview, REGex introduce this course for you.

Batch 1

Starting from 21st Dec, 2020
Timing: 06:00 PM – 08:00 PM (MWF)
Platform: Google Meet
Duration: 8 Weeks

Batch 2

Starting from 4th Jan, 2021
Timing: 06:00 PM – 08:00 PM (MWF)
Platform: Google Meet
Duration: 8 Weeks

Batch 3

Starting from 11th Jan, 2021
Timing: 06:00 PM – 08:00 PM (MWF)
Platform: Google Meet
Duration: 8 Weeks

What People Tell About Us


What you will Learn

  • Python basics, Machine Learning & Deep Learning
  • Supervised and Unsupervised Learning
  • Regression, Classification and Clustering Algorithms
  • Working of Regression and Classification Algorithms from scratch
  • Deep Learning and Working of Deep Neural Networks
  • Image Recognition & Object Detection
  • Handwritten Digit Recognition

Study Material

  • E-Notes
  • Assignments per day
  • Poll test per day
  • Weekly Tests
  • 60+ hours on demand Live Video Lectures
  • Offline Access of Lecture Videos & Notes
  • 24*7 Mentorship Support

  • Working on Live Projects


  • Able to think out of the box
  • Understand different types of machine learning: Supervised, Unsupervised & Reinforcement
  • Understand working of ML models and neural networks from scratch
  • Build and save your ML models using scikit learn
  • Build projects such as handwritten digit recognition, image Classification, object detection etc
  • Build Deep Neural Networks using Tensorflow
  • Work on more then 10 Use CASES
  • Learn to deploy your models on AWS Sagemaker or Google cloud Platform

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


REGex provides Internship / Job opportunities to the best Students in different Companies.

Our Students Placed In


Course Content

Machine learning
○ Machine learning applications
○ ML vs DL
Data Cleaning & Munging with – Python
○ 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
Understanding all concepts of Machine Learning
○ What is actual machine learning
○ Various Aspects of Data – type, Variables & Category
○ Machine Learning & its Various types
Supervised & Unsupervised machine Learning
Understanding with Simple Linear Regression
Multiple Linear Regression Intuition
○ Understanding the P -Value
What is Regression with its use cases
○ Support Vector Regression
Decision Tree Regression & Random forest Regression
Logistic Regression
○ K-NN [K-Nearest Neighbors]
Support Vector Machines
Bayes Theorem
○ Naive Bayes Intuition
Dimension Reduction & Feature Selection
○ Principal Component analysis (PCA – Theory)
○ PCA with Case-Study
○ Linear Discriminant Analysis(LDA) for Dimension Reduction
○ Feature Selection to Select the Most Relevant Predictors
Evaluating classification models performance
○ Confusion matrix
○ Accuracy Paradox
○ CAP Curve
K-Mean Clustering
○ K-Mean Clustering Intuition
○ K-Mean selecting Numbers of Cluster
Reinforcement learning
Traditional A/B Testing
○ NLP Intuition
○ Types of NLP
○ Classification vs Deep Learning Models
Understanding about Deep Learning
○ The Neuron
○ Activation function
○ How Neural network work & learn by itself
○ Gradient Descent
○ Stochastic Gradient Descent
○ Ethics of Deep Learning
Deep Dive with ANN
○ What are convolutional neural networks [CNN] ?
○ CNN Architecture
○ CNN Code preparation
○ Recurrent Neural Networks
○ Several layers
■ ReLLu Operation
■ Pooling
■ Flattering
■ Full Connection
Statistics and probability Refresher
○ Learn about mean, median, mode
○ Variation
○ Standard Deviation
○ Density Functions
○ Probability Mass function
○ Percentiles
○ Covariance & Correlation
Computer Vision & OpenCV
○ What is computer vision & its application
○ Face Detection
■ Adding more features & Categorization
■ Object Detection
■ Image creation
■ Working with Images
■ Working with Vectors
○ Facial Expression Recognition in Code (Binary / Sigmoid / Logistic Regression)
Natural Language Processing [ NLP]
○ What are Vectors
○ Working with word Analogy
○ Text Classification
○ Pre Trained word vectors from word2vec
○ Language Models
TensorFlow / Keras
○ Introduction to Tensorflow / Keras
○ Most used right now
○ Resources gathering
○ Keras dealing with Missing Data
○ Dealing with Categorical data
AWS SageMaker
○ Create your own ML models
○ Deploy ML models
○ AWS Rekognition
Capstone Project

Fee Structure

(for each program)

Indian Fee

Price: ₹4999/- (Flat 80% off) => ₹999/- 

International Fee

Price: $100 (Flat 70% off) => $30 
For Frequent Course Updates and Information, Join our Telegram Group
For Webinar Videos and Demo Session, Join our Youtube Channel

Enroll Now

(Registration Open till 15th Jan, 2021)

*It will help us to reach more
*Seats can be filled or Price can be increased at any time*