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DevelopmentData ScienceData Visualization

Machine Learning for Absolute Beginners - Level 3

Learn to Master Data Visualization and perform Exploratory Data Analysis (EDA) using Python, Matplotlib and Seaborn
Rating: 4.6 out of 54.6 (54 ratings)
11,738 students
Created by Idan Gabrieli
Last updated 2/2021
English
English [Auto]

What you'll learn

  • Perform Exploratory Data Analysis (EDA) for any Dateset
  • Visualise Data using a Variety of Chart Types
  • Learn Matplotlib and Seaborn Fundamentals
  • Creating Bar, Grouped Bar, Stacked Bar, Lollipop charts
  • Creating Pie, Tree-map charts
  • Creating Line, Area, Stacked Area charts
  • Creating Histogram, Density, Box-and-Whisker, Swarm charts
  • Creating Scatter, Correlogram, Heat-Map, Hexbin-Map charts

Requirements

  • Python Basic Syntax
  • Highly skilled working with the Pandas Library - Loading Datasets and Manipulating Data in a Data Frame.
  • It is recommended to start with the Level 1 and Level 2 of the "Machine Learning for Absolute Beginners" training program

Description

Unleash the Power of ML

Machine Learning is one of the most exciting fields in the hi-tech industry, gaining momentum in various applications. Companies are looking for data scientists, data engineers, and ML experts to develop products, features, and projects that will help them unleash the power of machine learning. As a result, a data scientist is one of the top ten wanted jobs worldwide!

Machine Learning for Absolute Beginners

The “Machine Learning for Absolute Beginners” training program is designed for beginners looking to understand the theoretical side of machine learning and to enter the practical side of data science. The training is divided into multiple levels, and each level is covering a group of related topics for a continuous step-by-step learning path.

Level 3 – Data Visualization with Matplotlib and Seaborn

The third course, as part of the training program, aims to help you to perform Exploratory Data Analysis (EDA) by visualizing a dataset using a variety of charts. You will learn the fundamentals of data visualization in Python using the well-known Matplotlib and Seaborn data science libraries, including:

  • Matplotlib fundamentals

  • Seaborn fundamentals

  • Selecting the right chart for the right job

  • Bar, Grouped Bar, Stacked Bar, Lollipop charts

  • Pie, Three-map charts

  • Line, Area, Stacked Area charts

  • Histogram, Density, Box-and-Whisker, Swarm charts

  • Scatter, Correlogram, Heatmap, Hexbin charts

Each section has a summary exercise as well as a complete solution to practice new knowledge.

The Game just Started!

Enroll in the training program and start your journey to become a data scientist!

Who this course is for:

  • Developers curious about Data Science projects
  • Beginner Data Scientists
  • AI Product Managers
  • ML Engineers
  • AI/ML Consultants

Instructor

Idan Gabrieli
Online Teacher | Data, Cloud, AI
Idan Gabrieli
  • 4.5 Instructor Rating
  • 5,339 Reviews
  • 132,204 Students
  • 16 Courses

For the past decade, Idan Gabrieli has been working in various engineering positions at the heart of Israel's high-tech industry, also called the start-up nation. Through his career, Idan has gained extensive experience working with hundreds of business companies, helping them transform challenges and opportunities into practical use cases while leveraging cutting-edge technologies.

Idan has comprehensive knowledge that spans multiple domains, including cloud computing, machine learning, data science, electronics, and more. In 2014, Idan started to create and publish online courses on various topics while teaching thousands of students worldwide. In 2021-2022, Idan was recognized as a top-seller and high-rated instructor in multiple leading educational providers.

As part of his teaching style, Idan is well-known for simplifying complex technology topics and providing high-quality educational content suitable to the relevant audience. Every course has specific learning objectives, easy-to-follow structure, and straight-to-point material while combining various multimedia teaching options.

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