Course

Title : DATA SCIENCE - Professional Course

Hours : 60 Hrs

Batches : Weekday ( Mon - Fri )|Weekend ( Sat & Sun )

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60 Hours of
Class Room Training

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30 Sessions of
Class Room Training

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90 Hours of
Coding Assignment

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50 Coding Tasks
For Interview Purpose

Course Overview

We provide a Professional level Data Science Course that will establish your mastery of data science and analytics techniques using Python Libs, you’ll learn the essential concepts and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing.

Prerequisites

  • Anyone aspiring to learn new technology and pursue their career in Data Analytics can take this course.
  • Python Programming knowledge is desirable, but not mandatory.

Batches

Weekday Batch:
4:30 PM to 6:30 PM | Monday to Friday | 5 Days/Week | 6 Weeks Course

Weekend Batch:
4:30 PM to 6:30 PM | Saturday & Sunday | 2 Days/Week | 15 Weeks Course

Curriculum

Download Curriculum
  • Class-1 : Overview of Analytics
  • Class-2 : Basics of Statistics
  • Class-3 : Probability
  • Class-4 : Statistical Measures
  • Class-5 : Hypothesis, Parametric & Non-Parametric Tests
  • Class-6 : Introduction to Data Management
  • Class-7 : Statistics and EDA
  • Class-8 : Data Visualization
  • Class-9 : Linear Regression
  • Class-10 : Logistic Regression
  • Class-11 : Time Series
  • Class-12 : Machine Learning
  • Class-13 : Decision Trees and Random Forests
  • Class-14 : K-Means Clustering
  • Class-15 : Principal Component Analysis & Cross Validation
  • Class-16 : Naive Bayes
  • Class-17 : Neural Network Basics
  • Class-18 : Installation and Python Basics
  • Class-19 : Python Basics and String Manipulation
  • Class-20 : Data Structures in Python
  • Class-21 : Data Frame Manipulation
  • Class-22 : Libraries like Numpy,Pandas
  • Class-23 : Simple Regression Analysis using Python
  • Class-24 : Multiple Regression using Python
  • Class-25 : Decision Trees using Python
  • Class-26 : Time Series using Python
  • Class-27 : Data Visualization using Matplotlib
  • Class-28 : Introduction to Tabulae
  • Class-29 : Real World Case study -1
  • Class-30 : Real World Case study -2

Class Features