Course Description:

This is the only online Data Science with Python course where you can have complete industrial knowledge and experience in analyzing data and building modules. Our Data science courses will give you not only the Data Science knowledge but also good hands-on experience of building modules in day to day activities. This course consists of 60 hours lesson followed by 120 hours practice session in the live project. This course is perfect for every beginner to experienced Data Science, as the course starts from scratch to complete complex analysis of data and modules.

Learning Outcomes:

• • Over 60 hours of training and 120 hours of practice in a live project
  • LIVE PROJECT End to End Application development with cloud, Patching, troubleshooting Training Included.
  • Learn Data Science with Python basics from a professional trainer from your own lab.
  • Information packed practical training starting from basics to advanced Data Science with Python techniques.
  • Best suitable for beginners to advanced level users and who learn faster when demonstrated.
  • Course content designed by considering current data science with python and the job market.
  • Practical assignments (type-1) of 2 hours at the end of every day’s session.
  • Practical assignments (type-2) of 3 hours at the end of every Week module.
  • The practical learning experience with live project work and examples.

Modules:

• Introduction

• Python Programming Basic

• • Basic Syntax
  • Build-in Data Structures
  • Conditional Statements
  • Loops
  • User defined functions/ Built in Functions
• Essential Package for Data Science

1. • Numpy
   • Pandas
   • Visualization

• Data Understanding and Statistics
• a.Descriptive Stats

1. •  Measure of Count
   •  The measure of Central Tendencies
   •   Measure of Spread

• b. Inferential Stats

1. •  Confidence Interval
   •  Hypothesis Testing
   •   Correlation

• c. Predictive Analytics
  • Linear Regression
  •  Logistic Regression
  • Supervised Learning Models
  • Unsupervised Learning Models
  • Feature Reduction
•  Natural Language Processing
• Assessment and Test