Description

Python Data Science: Data Prep & EDA with Python is designed as a practical, project-based guide to help you master the fundamentals of data science using the Python programming language. In this educational journey, we begin by establishing a strong understanding of the fundamental concepts of data science and machine learning. To that end, we will explain the key distinctions between supervised and unsupervised learning approaches, and we will also carefully examine the data science workflow framework that will serve as our roadmap throughout this course.

After this introductory phase, our main focus will be on the heart of the data science process, namely the stages of Data Preparation and Exploratory Data Analysis (EDA). In these crucial sections, you will get to know the perspective of a data scientist and learn how to envision and plan a data science project from scratch to its final stages. Proficiency in working with the powerful Pandas library in Python will allow you to collect data from various sources and effectively deal with common data cleansing challenges. You will also learn advanced EDA techniques, including intelligent data filtering, meaningful grouping, and data visualization using powerful visualization tools to uncover patterns and insights hidden in the data.

What will you learn in this course?

• Mastering the core building blocks of Python, which are a prerequisite for entering the world of data science and using machine learning algorithms.
• Ability to define and constrain data science projects by setting clear objectives, selecting appropriate techniques, and identifying the data sources needed to perform accurate analyses.
• Proficiency working with the Pandas library to import and export data from a variety of sources including plain text files, Excel spreadsheets, and SQL database tables.
• Ability to cleanse and prepare data by converting data types, managing common data quality issues, and creating new columns to enrich the analysis process.
• Mastery of exploratory data analysis (EDA) techniques including sorting, filtering, grouping, and visualizing data to uncover patterns, trends, and valuable insights.
• Skill in preparing data for use in machine learning models by merging different tables, adjusting the level of detail of the data, and applying feature engineering techniques to extract useful information.

Who is this course for?

• Data scientists looking to learn fundamental techniques and best practices in data preparation and exploratory data analysis.
• Users of the Python programming language who want to acquire the basic skills needed to enter the field of artificial intelligence and machine learning models.
• Data analysts or business intelligence (BI) professionals looking to change careers and enter the exciting field of data science.
• Any interested person who wants to learn one of the most popular open source programming languages ​​in the world, Python, in the field of data science.

Python Data Science: Data Prep & EDA with Python Course Details

• Publisher : Udemy
• Teacher : Maven Analytics • 1,500,000 Learners , Alice Zhao
• Language: English
• Level : All Levels
• Lectures : 180
• Duration : 8 hours and 41 minutes

Course topics

Prerequisites for the Python Data Science: Data Prep & EDA with Python course

• Jupyter Notebooks (free download, we’ll walk through the installation)
• Familiarity with basic Python and Pandas is recommended, but not required

Course images

Sample course video

The 2025/6 version has decreased the number of lessons by 12 and the duration increased by 3 minutes compared to 2025/4.

The 2026/6 version has no changes in the number of lessons and duration of the course compared to the 2025/6 version, but the volume of some of the videos has changed.

Download link

Downloadly

Download Part 1 – 1 GB

Download Part 2 – 1 GB

Download Part 3 – 989 MB

Rapidgator

Download Part 1 – 1 GB

Download Part 2 – 1 GB

Download Part 3 – 989 MB

File(s) password: www.downloadly.ir

File size

2.98 GB