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Analytics using Pandas and Numpy – Qualitative and Quantitative Studies

Learn to transform data into powerful dataframes specifically designed for recommendation and predictive applications.
25,000

Description

This course facilitates major part of a data science project activity. In reality data scientists spends much of their time transforming, shaping-reshaping data to serve to several machine learning models. The activity to clean, transform and process the data will be the prime focus of this program. This program will also demonstrate simple to complex data visualizations using Pandas visualization library, seaborn library and matplotLib.

Numpy will be used to convert series data into N-dimensional arrays to feed into predictive models. Random numbers, math operations and statistics using Numpy will also be featured.

TECHNOLOGY USED: Python General Purpose, Anaconda Jupyter Notebooks, Pandas, Numpy

What Will I Learn?

  • Get familiar to data manipulation and numerical operations on multidimensional arrays
  • Learn to create data structures for machine learning
  • How to render visuals charts and their interpretations
  • Handle complex data formats
  • Build data reasoning

Topics for this course

39 Lessons20h

Introduction to Pandas

Installing and using Pandas
What are objects in Pandas
Objects example in Pandas i.e. Series Object, DataFrame & Index object

Data selections in Pandas

Data Group by and Aggregations

Handling Time Period data in Pandas

How to leverage pandas for a machine learning project?

Exploring Matplotlib

Exploring seaborn

Numpy in python

End of the topic project

About the instructors

Pedagogy Trainings

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With a pure blend of Mathematics, Statistics, Data Analysis and Interpretation,we deliver training in numerous technologies ranging from basic report authoring, building large scale data integration, data quality, data visualization, data mining and the new generation distributed computing using big data.
17 Courses
2 students

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Course Details

  • Level: Beginner
  • Categories: Data Science
  • Total Hour: 20h
  • Total Lessons: 39
  • Total Enrolled: 0
  • Last Update: April 23, 2020

Requirements

  • Python Core for Analytics

Target Audience

  • All working professionals wanting to know how to deal with data
  • Existing software coders and developers
  • Students & Professionals looking for a competitive edge in data science and machine learning