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Easy Learning with Python for Data Science: Numpy and Pandas Libraries for Data
Development > Data Science
6h 56m
Free
4.2 ★★★★★

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Language: English

Master Data Science with Python: NumPy & Pandas

What you will learn:

  • Master NumPy for data analysis and data science.
  • Efficiently manipulate and process data with NumPy.
  • Utilize NumPy for image processing.
  • Become proficient in Pandas for data manipulation and analysis.
  • Use Pandas for data visualization.
  • Learn to interact with databases (PostgreSQL) using Python and Pandas.
  • Master web scraping techniques using Python.
  • Conduct comprehensive data analysis using real-world datasets.
  • Develop a strong data storytelling ability.
  • Learn foundational Python programming skills.

Description

Unlock the power of data with this comprehensive Python course! Designed for beginners and experienced programmers alike, this course dives deep into the essential Python libraries – NumPy and Pandas – that form the bedrock of modern data science. You'll master core Python concepts, from data types and control flow to object-oriented programming, then leverage NumPy for powerful numerical computing and Pandas for data manipulation and analysis. Through hands-on projects, including creating engaging games and performing in-depth data analysis of real-world datasets (like Google App Store data!), you’ll build a robust portfolio showcasing your newly acquired skills.

This practical learning experience goes beyond theory. We cover data visualization techniques, error handling, efficient file management, database interaction (using PostgreSQL), and even web scraping to extract valuable data. Prepare to analyze, visualize, and interpret data with confidence. Quizzes and step-by-step guidance ensure you'll grasp every concept, laying a solid foundation for a successful career in data science.

By the end of this course, you won't just understand the theory; you'll be proficient in applying NumPy and Pandas to solve real-world data science challenges. The course includes two engaging projects, a color choices game and a hangman game, to solidify your Python programming understanding.

What you'll gain:

  • Foundational Python programming skills.
  • Proficiency in NumPy for numerical computation and array manipulation.
  • Expertise in Pandas for data cleaning, manipulation, analysis, and visualization.
  • Experience with database interaction (PostgreSQL).
  • Web scraping techniques.
  • A strong portfolio showcasing your data science skills.

Enroll now and transform your data science potential!

Curriculum

Introduction

This introductory section sets the stage for your data science journey. You'll get acquainted with Python, covering essential concepts like setting up your environment, comparing Python 2 and 3, and understanding fundamental data types. Lectures cover setting up your Python environment, understanding the differences between Python 2 and Python 3, and the core data types that you'll be using throughout your work.

Python Refresher

This section serves as a solid refresher for your Python knowledge. Topics covered include mastering variables, operators, data types, string manipulation, control flow (loops and conditionals), various data structures like lists and dictionaries, robust error handling techniques, the creation and utilization of functions, and effective file and module management. The aim is to consolidate your foundational Python skills in preparation for more advanced topics.

Object Oriented Programming (OOP) In Python

This section delves into the powerful paradigm of object-oriented programming (OOP) in Python. You'll learn about classes, constructors, dunder methods, inheritance (single and multiple), encapsulation, overriding methods, and decorators— essential concepts for writing efficient and maintainable code. The focus is on practical application and building a strong understanding of OOP principles for data science.

Project Color Choices Game

Put your newly acquired Python skills to the test by building a fun Color Choices game. The section includes a walkthrough of the project, helpful notes to guide your development, and a complete project solution to ensure your understanding of the concepts and how to put them into practice. This project reinforces your ability to build applications in Python.

Project Hangman Game

This section guides you through building a classic Hangman game using Python. This project builds further on the programming concepts covered earlier in the course, providing more hands-on experience and building confidence in applying the programming concepts. You’ll receive a walkthrough, helpful notes, and a solution divided into parts to ease your learning process.

Numpy Python Library

This section introduces the powerful NumPy library, essential for numerical computing in Python. You'll learn to create and manipulate arrays, understand NumPy's shape and size attributes, perform calculations and aggregations, use NumPy's unique function, master array slicing, reshape and transpose arrays, apply comparisons, and even process images using NumPy. This section is packed with practical exercises to help you master NumPy's capabilities.

Python Pandas Data Analysis & Visualization

Dive into Pandas, the go-to library for data manipulation and analysis in Python. You’ll learn to install Jupyter Lab and Pandas, connect to and interact with a PostgreSQL database, efficiently load data from databases using Pandas, understand and use 'Fetchmany' and 'Fetchall' functions, effectively query data using Pandas, master various Pandas methods and functions for data wrangling, and apply data visualization techniques using Pandas and explore data analysis methods, including discussions on sampling error. This section empowers you to handle data with precision and visualise insights effectively.

Web Scraping & Data Analysis Using Python & SQL

In this section, you'll learn to leverage Python's capabilities for web scraping. You'll learn how to extract data from websites, specifically targeting tables using Pandas and LXML. You will also learn how to visualize the extracted data and efficiently save it to a database. This empowers you to gather and analyze data from a wide range of online sources, extending your data science skillset.

Project Google App Data Analysis

This substantial project lets you apply all your acquired skills by performing a comprehensive analysis of Google App Store data. You’ll explore the data visually, clean and preprocess it, visualize key insights using various techniques, perform statistical analysis and hypothesis testing, create engaging data stories, and draw insightful conclusions. This project provides a realistic data science experience, mimicking real-world workflows and challenges.

Bonus

A brief concluding section expressing gratitude for your participation.

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