NumPy, Pandas, Matplotlib in Python for Machine Learning

Learn NumPy, Pandas, Matplotlib in Python for Machine Learning and Data Science in an engaging and exciting way

Contents and Overview

What you’ll learn

  • Go from absolute beginner to become a confident Python NumPy, Pandas and Matplotlib user.
  • Student will learn Data Visualization techniques using matplotlib.
  • Students will get practical hands on with real world data.
  • Students will learn various data preprocessing techniques using pandas.
  • With more than 50+ exercise questions provided along with course, we will help students to master these libraries.

Course Content

  • Introduction –> 3 lectures • 9min.
  • NumPy –> 18 lectures • 36min.
  • Pandas –> 16 lectures • 38min.
  • Matplotlib –> 11 lectures • 21min.
  • Practice –> 1 lecture • 3min.

NumPy, Pandas, Matplotlib in Python for Machine Learning


  • Just a little knowledge of Python.

Contents and Overview

Welcome to the crash course on Numpy, Pandas, Matplotlib by Teaching Bee. In this course we will go through, basics to advance concepts for each library which are prerequisite of data science field.

In the first module we will cover important concepts of numpy from basic concepts like difference between numPy array with python list, creating numpy arrays to some advance concepts like Boolean indexing broadcasting etc.

In the next section we will be covering concepts of pandas with hands on real world movies dataset and also  see various data preprocessing steps which are involved in machine learning using pandas library

In the third section we will see how to visualise and interpret data using matplotlib library on real world dataset and also see which type plot is used in different scenarios.

As it is said “Practice Makes a Man Perfect”, so in last section we will discuss few of the 50+ curated exercise questions provided along with course on the above library which we will help you to master these libraries.


Know your instructor

Teaching bee is a group of industrial professionals with aim to build the required skillset of students using practical hands On. All of our teachers have more than 4 years of industrial experience in there respective domain therefore having required knowledge not only about the subject but also about the requirements of software industry.

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