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Data Analysis Masterclass: A-Z Data Analysis in Python

Publicado en 30 Apr 2024

Udemy UK

What you'll learn

  • You will get proficient in Python for thorough data analysis. Prepare for a career as a data analyst by acquiring practical skills and expertise.
  • You will master the fundamentals of data analytics, including facts and theories, statistical analysis, hypothesis testing, and machine learning.
  • You will learn the important Python programming basics such as variables naming, data types, lists, dictionaries, dataframes, sets, loops, functions etc.
  • You will master a range of methods and techniques for data cleaning, sorting, filtering, data manipulation, transformation, and data preprocessing in Python.
  • You will learn to use Python for data visualizations, exploratory data analysis, statistical analysis, hypothesis testing methods and machine learning models.
  • You will work on practical data analysis projects to apply learned skills. Enhance problem-solving abilities through hands-on data analysis exercises.
  • You will pass practical assignments, 85+ coding exercises, 10 quizzes with 100+ questions, on all the topics over the entire course.
  • You will accomplish one capstone project on Sport data analysis at the end to get the full view of data analysis workflow in Python.

Requirements

  • Access to computer and internet
  • Basic computer literacy
  • No coding experience required

Description

Welcome to the Data Analysis Bootcamp: A-Z Data Analysis in Python! In this comprehensive course, you'll embark on a journey from Python novice to proficient data analyst, equipped with the essential skills and knowledge to excel in the field.


Throughout this course, you will delve deep into the realm of Python programming, focusing on its application in data analysis. Starting from the basics, you'll master fundamental concepts such as variable naming, data types, lists, dictionaries, dataframes, sets, loops, and functions. With a solid foundation in Python, you'll seamlessly transition to advanced topics, including data cleaning, sorting, filtering, manipulation, transformation, and preprocessing.


But that's not all. As you progress, you'll learn how to harness the power of Python for data visualization, exploratory data analysis, statistical analysis, hypothesis testing, and even delve into the exciting world of machine learning. Through a combination of theoretical understanding and hands-on practice, you'll gain proficiency in a wide range of methods and techniques essential for data analysis.


What sets this course apart is its emphasis on practical application. You won't just learn the theory; you'll put your newfound knowledge to the test through practical data analysis projects and hands-on exercises. With over 85 coding exercises, 10 quizzes featuring 100+ questions, and practical assignments covering all topics, you'll have ample opportunities to reinforce your skills and enhance your problem-solving abilities.


As the culmination of your journey, you'll undertake a capstone project focused on sports data analysis. This final project will allow you to apply all the skills you've acquired throughout the course, providing you with a comprehensive understanding of the data analysis workflow in Python.


Whether you're a seasoned professional looking to upskill or someone just starting their journey in data analysis, this course is designed to equip you with the expertise and confidence needed to succeed. Join us on this exciting adventure and unlock your potential as a data analyst in Python.

Who this course is for:

  • Those who are highly interested in learning complete data analytics using Python.
  • This course is NOT for those who are interested to learn data science or advanced machine learning application.

Debes tener en cuenta que los cupones duran maximo 4 dias o hasta agotar 1000 inscripciones,pero puede vencer en cualquier momento. Obten el curso con cupon haciendo clic en el siguiente boton:

(Cupón válido para las primeras 1000 inscripciones): 1ECFD9F23E3BEAC8C896
Udemy UK
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