Course description

One of the most important skills of successful data scientists and data analysts is the ability to tell a compelling story by visualizing data and findings in an approachable and stimulating way. In this course you will learn many ways to effectively visualize both small and large-scale data. You will be able to take data that at first glance has little meaning and present that data in a form that conveys insights.

You will learn hands-on by completing numerous labs and a final project to practice and apply the many aspects and techniques of Data Visualization using Jupyter Notebooks and a Cloud-based IDE. You will learn to implement data visualization techniques and plots using Python libraries, such as Matplotlib, Seaborn and Plotly.

What will i learn?

  • Create beautiful visualizations with Seaborn
  • Practice with tons of exercises and challenges
  • Learn the ins and outs of Matplotlib
  • Learn the ins and outs of Matplotlib
  • Merge datasets together in Pandas

Requirements

  • Python basics

  • Python Intro, syntax, variables, data types
  • Python Operators, Control Statements
  • Python Loops, Numbers, Strings
  • Python Collections - List, Tuple, Dictionary & Set
  • Functions, Local & Global Variables
  • Python OOPs

  • Data analytics Impact and Importance, Type of Data analytics, Descriptive analytics, Diagnostic analytics, Predictive analytics, Prescriptive analytics
  • Data analytics vs Decision making, Data analytics vs cost reduction, Dealing with different type of data
  • Qualitative and Quantitative data, Normal distribution of data, Statistical parameters

  • Pandas Introduction
  • Pandas Series and DataFrames
  • Pandas Read CSV and Read JSON
  • Pandas Analysing Data

  • Numpy basic – ndarray and basic arithmetic operation
  • Slicing, coy and view, Mathematical function of numpy
  • Introduction to Scipy, Scipy sub package Integration and Optimization
  • Calculation of Eigenvalues, Eigenvector Scipy sub package

  • Introduction to Data visualization tools
  • Data visualization Using Matplotlib
  • Data Visualization using Seaborn
  • Data Visualization using Plotly

  • Real-time project

Swathi Niharika Kunja

Free

Lectures

22

Skill level

Beginner

Expiry period

Lifetime

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