Getting Digital

500 Exercises to Master Python Pandas

Develop essential data science & ai skills with expert instruction and practical examples.

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

Who is this course for. This course is for those who plan to take a step into the field of data science and beginner to intermediate level data analyst, data scientist, and data engineers. Most of the exercises are based on my experience of working as a data scientist with real-life datasets so you can benefit from this course even if you are already using Pandas at your job.

If you have never used Pandas before or have little experience, you can learn a lot because the exercises are created in a way that is simple and easy-to-understand. All you need is a basic level of Python knowledge. What is needed to take this course.

Lectures are structured as me going over Jupyter notebooks explaining exercises. Notebooks can be found in the description of each lecture. If you want to download the notebooks and follow along, make sure you also download the relevant datasets available in the data folder in the course repository.

You also need to have Jupyter notebook installed on your computer. You can also Google Colab, which allows for running Jupyter notebooks in your browser for free. Course structureThe course is divided into 6 chapters:IntroductionData exploration and manipulationData filteringCombining DataFramesData analysis and visualizationUse casesMore learningsEach chapter contains multiple lectures with each one focusing on a particular task such as how to filter a DataFrame, how to create pipelines with multiple steps, and how to use Python dictionaries to enhance the power of Pandas functions.

Provider
Udemy
Estimated Duration
10-20 hours
Language
English
Category
Technology & Programming

Topics Covered

Data Science & AIPython

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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