LunarTech – Python for Data Science 2024-12

LunarTech – Python for Data Science 2024-12 Downloadly IRSpace

LunarTech – Python for Data Science 2024-12
LunarTech – Python for Data Science 2024-12

Python for Data Science Course. This comprehensive course will help you gain essential Python skills for data analysis, visualization, statistical analysis, and machine learning. This course provides a solid foundation for your data science journey. This data science bootcamp is designed to provide you with the most comprehensive and relevant curriculum available.

What you will learn:

  • Getting Started in Data Science: Learn the Python basics essential for data analysis, visualization, and broader data science workflows.
  • The Essential Data Science Toolkit: Learn how to confidently clean, manipulate, and examine data using Python – core competencies for data entry roles.
  • Speak the language of data: Develop the ability to explain your Python analyses, statistical findings, and visualizations to non-technical stakeholders.
  • Using Python in real projects: Tackle A/B testing and basic machine learning concepts, and demonstrate your ability to solve data-driven problems.

Who is this course suitable for?

  • This course is suitable for anyone looking to enter the world of data science. Whether you are a beginner or have little programming experience, this course will help you gain the skills you need to succeed in the field.
  • Data science enthusiasts
  • Data analysts
  • Data Engineers
  • Researchers
  • Anyone who wants to use data to make better decisions

Python for Data Science Course Specifications

  • Publisher: LunarTech
  • Instructor: Tatev Aslanyan
  • Training level: Beginner to advanced
  • Training duration: 6 hours and 22 minutes
  • Number of lessons: 21

Course headings

Python for Data Science

Course images

 

Python for Data Science

Sample course video

Installation Guide

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Subtitles: None

Quality: 720p

Download link

Download file – 566 MB

File(s) password: www.downloadly.ir

File size

566 MB