Data Analytics using Python Course

Data Analytics using Python online training course will provide the various skills you need to kickstart a career in data analytics.

  • 50000
  • 55000
  • 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. Visualize data using matplotlib in Python.
  • Learn how to work with various data within python, including: Excel Data,Geographical data,Text Data and Time Series Dat...

Requirements

  • basic understanding of Computer Programming Languages. A basic understanding of statistics

Description

|| About Data Analytics using Python Training Course

Many Data analysts believe that the only way to analyze data is by creating simple charts and estimating simple linear models. However, to truly extract the key information buried inside your business data—information that is important for making sound and reasonable business decisions—you need to perform sophisticated, high-powered analyses.Objective of Data Analytics using Python online training course is to impart knowledge on use of text mining techniques for deriving business intelligence to achieve organizational goals. Use of Python based software platform to build, assess, and compare models based on real datasets and cases with an easy-to-follow learning curve. In this course data visualization and statistical methods implemented in Python for analyzing business data, whether sales, personnel, logistics, marketing, or financial. You'll explore the nature of business data, the application and interpretation of statistical and machine learning methods for gaining insight into your business, and how to present conclusions in tabular and graphical formats.

 

This analytics certification course is for all those aspirants who want to switch into the field of data science and begin their career as a Data analyst. With the aim to provide all the aspirant's world-class Data Science and Data Analytics skills irrespective of their location. This is one of the best Data Analytics certification for candidates who do not have any prior background in analytics but want to jump-start their career in Analytics. After completing this course, you will be able to contribute like an experienced team member in analysing Data for decision making.

Course Content

Live Lecture

·      Different Sectors Using Data Science

·      The Purpose and Components of Python

·      The Data Analytics Process

·      Exploratory the Data Analysis (EDA)

·      EDA-Quantitative Technique

·      EDA - Graphical Technique

·      The Data Analytics Conclusion or Predictions

·      The Data Analytics Communication

·      The Data Types for Plotting

·      Practical Exercise              

Live Lecture

·      Introduction to the Statistics

·      About Statistical and Non-statistical Analysis

·      The Major Categories of Statistics

·      About the Statistical Analysis Considerations

·      The Population and Sample

·      What is the Statistical Analysis Process?

·      The Data Distribution

·      Dispersion

·      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