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Data Analysis using Python

Data Analysis using Python online training course will help to understanding of the data ecosystem and the fundamentals of data analysis, such as data gathering or data mining.

  • 50000
  • 55000
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  • Course Includes
  • Live Class Practical Oriented Training
  • 120 + Hrs Instructor LED Training
  • 60 + Hrs Practical Exercise
  • 35 + Hrs Project Work & Assignment
  • Timely Doubt Resolution
  • Dedicated Student Success Mentor
  • Certification & Job Assistance
  • Free Access to Workshop & Webinar
  • No Cost EMI Option
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What you will learn

  • How to use several Python packages for business analysis, including pandas for data manipulation; StatsModels, SciPy, an...
  • To divide data into training and test datasets for validation
  • To visualize data. To estimate and interpret statistical models, such as OLS and logistic regression
  • Deal with different data sources: json, CSV, API. Use Numpy library to create and manipulate arrays.
  • Use the pandas module with Python to create and structure data.

Requirements

  • basic understanding of Computer Programming Languages.

Description

|| About Data Analysis using Python Training Course

Learn how to analyze data using Python. Data Analysis using Python online training course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data. Data analyst responsible for conducting, analyzing, and interpreting data for key business decisions, and you want to learn how to use Python and its main packages.This course will help to expand your knowledge of and experience with toolsets for analysis methods, such as machine learning, and software so you can provide the best insights to your clients and advance your career. Data Analysis courses, covering everything you need to learn to work as a data analyst using Python. It's designed so that there are no prerequisites and no prior experience required. Everything you need to learn to work as a data analyst, you'll learn on this path! As you learn, you'll apply each concept immediately by writing code right in your browser that's automatically checked by our system to give you near-instant feedback on your progress.

 

Throughout this course you will learn the key aspects to data analysis. You will begin to explore the fundamentals of gathering data, and learning how to identify your data sources. You will then learn how to clean, analyze, and share your data with the use of visualizations and dashboard tools. This all comes together in the final project where it will test your knowledge of the course material, explore what it means to be a Data Analyst, and provide a real-world scenario of data analysis.

Course Content

Live Lecture

·      Introduction to Python Language

·      Features, the advantages of Python over other programming languages

·      Python installation – Windows, Mac & Linux distribution for Anaconda Python

·      Deploying Python IDE

·      Basic Python commands

·      Data types

·      Variables

·      Keywords and more

·      Practical Exercise              

Live Lecture

·      The Companies using Python

·      Different Applications where Python is used

·      Discuss Python Scripts on UNIX/Windows

·      Values, Types, Variables

·      Operands and Expressions

·      Conditional Statements

·      Loops

·      Command Line Arguments

·      Writing to the screen

·      Practical Exercise              

Live Lecture

·      Python files I/O Functions

·      Numbers

·      Strings and related operations

·      Tuples and related operations

·      Lists and related operations

·      Dictionaries and related operations

·      Sets and related operations

·      Practical Exercise              

Live Lecture

·      Functions

·      Function Parameters

·      Global Variables

·      Variable Scope and Returning Values

·      Lambda Functions

·      Object-Oriented Concepts

·      Standard Libraries

·      Modules Used in Python

·      The Import Statements

·      Module Search Path

·      Package Installation Ways

·      Errors and Exception Handling

·      Handling Multiple Exceptions

·      Practical Exercise