[kryptora] Data Science Training Module with Python


Introduction of Data Science with Python

Data Science is a new, exponentially-growing field in today’s world, which consists of a set of tools and techniques used to extract useful information from data. Data Science is an interdisciplinary, problem-solving oriented subject that learns to apply scientific techniques to practical problems. Data Science and analytics techniques using Python by enrolling in this Data Science with Python course. You will learn the essential concepts of Python programming and gain in-depth knowledge of data analytics,tableau machine learning, data visualization, web scraping, and natural language processing. Data Science with Tableau: Learn how to use Tableau in Data Science workflows.This course provides a high-level overview of Tableau’s built-in analytics features and contains detailed information about using external services to leverage analytical programming languages in Tableau.

Data Science Content:

List of data science content:

  • Program Introduction
  • Prerequisites
  • Data Science course phases
  • The key learning of Data Science
  • Topics of Data Science
  • Who is the target audience


To understand data science with a python course, it is recommended that you begin with these courses

  • Python Basics
  • Applying advanced statistical techniques in Python
  • Mathematics Refresher
  • Data Science in Real Life
  • Statistics Essentials for Data Science

The key learning of Data Science:

Python for Data Science training course will provide you to:

  • Data wrangling, data exploration, data visualization, hypothesis building, and testing; and the basics of statistics.
  • Implementing a comprehensive set of machine learning algorithms from scratch
  • Perform high-level mathematical computations using the NumPy and SciPy packages and their large library of mathematical functions
  • Perform data analysis with the Pandas package.
  • Perform data analysis with tableau.
  • learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline
  • matplotlib library of Python for data visualization.

Data Science course phases:

Phases are :

  • Fundamentals
  • Intermediate
  • Advanced
  • Visual Analytics
  • Data Science with Tableau

The following topics will be covered by this Data Science course:

The following topics will be covered by this Data Science course:

  • Python
  • Data mining
  • Advance Statistics
  • Machine learning
  • Information visualization
  • Network analysis
  • Natural language processing
  • Algorithms
  • Software engineering
  • Databases
  • Distributed systems
  • Big data
  • Tableau