Getting Digital

The Complete Data Analysis and Visualization in Python 2025

Master data science & ai from fundamentals to advanced concepts with this comprehensive course.

Online Course
Self-paced learning
Flexible Schedule
Learn at your pace
Expert Instructor
Industry professional
Certificate
Upon completion
What You'll Learn
Master the fundamentals of data science & ai
Apply best practices and industry standards
Build practical projects to demonstrate your skills
Understand advanced concepts and techniques

Skills you'll gain:

Professional SkillsBest PracticesIndustry StandardsPython
Prerequisites & Target Audience

Skill Level

IntermediateSome prior knowledge recommended

Requirements

Basic understanding of data science & ai
Enthusiasm to learn
Access to necessary software/tools
Commitment to practice

Who This Course Is For

Professionals working in data science & ai
Students and career changers
Freelancers and consultants
Anyone looking to improve their skills
Course Information

About This Course

In this course, you will learn Python libraries from scratch. So, if you don't have coding experience, that is very fine. NumPy and Pandas are necessary libraries to do data analysis and preprocessing.

In these course, most important concepts will be covered and after completing Pandas lectures, you will do Data Analysis exercise using Pandas for test score dataset. This is important step and aims to polish up your data preprocessing skill. Then, we will learn Matplotlib which is fundamental package for data visualization.

In these lectures, we will learn all necessary concepts for data visualization. After, we will dive into Seaborn, statistical package with beautiful charts. First we will explore most important and used charts using Seaborn's built-in dataset - tips.

After completing these lectures, we will dive into full data analysis and visualization exercise using complex datasets. Our first full data analysis exercise will be done using Netflix dataset where you will see how to do complex data preprocessing and applying Matplotlib functions to draw charts on progression and history. For second data analysis, dataset about diamond was used where you will explore Seaborn's full possibility.

Provider
Udemy
Estimated Duration
20-40 hours
Language
English
Category
Technology & Programming

Topics Covered

Data Science & AIPythonVisualizationComplete Course

Course Details

Format
Online, Self-Paced
Access
Lifetime
Certificate
Upon Completion
Support
Q&A Forum
Course Details
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This course includes:

Lifetime access to course content
Access on mobile and desktop
Certificate of completion
Downloadable resources

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