Data Science

GET YOUR DREAM CAREER!!!

[3-4-MONTHS EXTENSIVE TRAINING]

New Batch from 9th May

About This Program

We have designed our course after extensive research, and in accordance with the MARKET REQUIREMENTS. IT IS A COMPLETE PROGRAM TO MAKE YOU INDUSTRY READY.

Students will learn Machine Learning, Deep learning, Natural Language Processing, Computer Vision and Reinforcement Techniques which prominently feature in technical interviews.



  • If you are in any year of college or a pass-out from an engineering college.
  • If you want to upgrade your job profile.

Course Curriculum

1 Introduction to Data Science

  • What is Machine Learning, Deep Learning, Natural Language Processing, Reinforcement techniques?
  • Types and General Overview
  • What is Machine Learning, Deep Learning, Natural Language Processing, Reinforcement techniques?
  • Types and General Overview

2 Python

  • Basics
  • List
  • Tupples
  • Sets
  • Dictionary
  • File Handling
  • OOPs
  • Error Handling
  • Basics
  • List
  • Tupples
  • Sets
  • Dictionary
  • File Handling
  • OOPs
  • Error Handling

3 Statistics & Probability

  • Theory of inferential statistics
  • Statistical significance
  • Parameter estimation
  • Hypothesis testing
  • Correlation and regression
  • Exploratory data analysis
  • Probability
  • Theory of inferential statistics
  • Statistical significance
  • Parameter estimation
  • Hypothesis testing
  • Correlation and regression
  • Exploratory data analysis
  • Probability

4 Data Gathering

  • Web Scraping With Beautiful Soup
  • Automation with Selenium
  • Web Scraping With Beautiful Soup
  • Automation with Selenium

5 Data Cleaning and Handling

  • Numpy and Pandas
  • Numpy and Pandas

6 Data Visualization

  • Matplotlib
  • Plotly
  • Seaborn
  • Matplotlib
  • Plotly
  • Seaborn

7 Supervised Learning

  • Linear Regression
  • Logistic Regression
  • Decision Tree
  • Bagging
  • Boosting Random Forest
  • Naive Bayes
  • SVM
  • KNN
  • Linear Regression
  • Logistic Regression
  • Decision Tree
  • Bagging
  • Boosting Random Forest
  • Naive Bayes
  • SVM
  • KNN

8 Unsupervised Learning

  • PCA(Dimensionality Reduction Technique)
  • Clustering(K-means Clustering, Hierarchical Clustering, DBSCAN, Birch, Mean-Shift, Affinity Propagation, Spectral Clustering)
  • Gaussian mixture
  • Bayesian Gaussian mixture models
  • Anomaly detection
  • PCA(Dimensionality Reduction Technique)
  • Clustering(K-means Clustering, Hierarchical Clustering, DBSCAN, Birch, Mean-Shift, Affinity Propagation, Spectral Clustering)
  • Gaussian mixture
  • Bayesian Gaussian mixture models
  • Anomaly detection

9 Deep Learning

  • Intro To Deep Learning, Perceptron
  • Neural Networks
  • Back Propagation Maths
  • Activation Functions
  • Optimizers
  • Loss Functions
  • Artificial Neural Network
  • Creating Neural Network from Scratch
  • Convolutional Neural Networks
  • CNN Architecture
  • YOLO All Versions
  • Object Detection
  • Semantic Segmentation
  • Instance Segmentation
  • UNet
  • TensorFlow, Keras and PyTorch
  • Intro To Deep Learning, Perceptron
  • Neural Networks
  • Back Propagation Maths
  • Activation Functions
  • Optimizers
  • Loss Functions
  • Artificial Neural Network
  • Creating Neural Network from Scratch
  • Convolutional Neural Networks
  • CNN Architecture
  • YOLO All Versions
  • Object Detection
  • Semantic Segmentation
  • Instance Segmentation
  • UNet
  • TensorFlow, Keras and PyTorch

10 Natural Language Processing

  • Intro, Background
  • Text Processing
  • Text Normalization
  • Frequency Distribution
  • String Tokenization
  • Lemmetization
  • Sentimental Analysis
  • Spacey Library
  • Hugging Face
  • NLTK
  • Word Embedding
  • RNN
  • LSTM
  • Bi-LSTM
  • Project - Text To Speech, Speech to Text, ChatBot
  • Intro, Background
  • Text Processing
  • Text Normalization
  • Frequency Distribution
  • String Tokenization
  • Lemmetization
  • Sentimental Analysis
  • Spacey Library
  • Hugging Face
  • NLTK
  • Word Embedding
  • RNN
  • LSTM
  • Bi-LSTM
  • Project - Text To Speech, Speech to Text, ChatBot

11 Computer Vision

  • OpenCV Library and Project
  • Media Pipe Library with Project
  • OpenCV Library and Project
  • Media Pipe Library with Project

12 Reinforcement Techniques

  • Introduction
  • Bellman Equation
  • Markov Decision Process
  • Monte Carlo Method
  • Dynamic Programming
  • Temporal Difference Learning
  • Q learning & Deep Q Learning
  • Introduction
  • Bellman Equation
  • Markov Decision Process
  • Monte Carlo Method
  • Dynamic Programming
  • Temporal Difference Learning
  • Q learning & Deep Q Learning

13 Projects

  • 40+ Mini Projects
  • 3 Capstone projects
  • 40+ Mini Projects
  • 3 Capstone projects

14 Early Bird Addons

  • Hadoop
  • Model Deployment
  • Hadoop
  • Model Deployment

The Time - Factor

Batch details will be as followed:


  Start Date: 9th May
  Duration - 3-4 Months
  Live classes
  Doubt Support via videos and one on one sessions
  Regular Tests
  Freelancing opportunities via weekly hackathons
  Placement Assistance: Placement opportunities (6+ lakhs)

Final Message

Get your dream job with Pepcoding's Data Science Program for just   ₹30,000   ₹24,000

Enroll Now For The Course!!!

If you wish to register for this course, contact us on +91-7048971481 or +91-7048994628.
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