Python for Data Analysis and Visualization with Automation (Pandas, NumPy, Seaborn, Matplotlib)

Categories: Python
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About Course

Welcome to Python for Data Analysis and Visualization (Pandas, NumPy, Seaborn, Matplotlib)! This all-encompassing course is your gateway to becoming a proficient data analyst, armed with the essential skills to thrive in the dynamic world of data.

 

Starting with the fundamentals, you’ll learn Python programming with a focus on data analysis. From variable naming and data types to more advanced concepts like lists, dictionaries, dataframes, sets, loops, and functions, you’ll build a solid Python foundation. Once confident in the basics, you’ll progress to mastering data cleaning, sorting, filtering, manipulation, transformation, and preprocessing techniques, all critical for effective data analysis.

 

The course goes beyond the basics by unlocking the potential of Python for data visualization, exploratory analysis, statistical methods, and hypothesis testing. You’ll also take a step into the world of machine learning, gaining hands-on experience with these cutting-edge techniques. This course blends theory with practice, ensuring you grasp the concepts through real-world application.

 

What truly sets this masterclass apart is its focus on practical, hands-on learning. You won’t just study theory—you’ll practice through 85+ coding exercises, 10 quizzes with 100+ questions, and practical assignments, all aimed at reinforcing your skills. These exercises ensure you develop critical problem-solving abilities essential for any data analyst.

 

To crown your learning journey, you’ll complete a capstone project that involves analyzing sports data, giving you the chance to apply all the skills you’ve learned to a real-world scenario. This project will showcase your complete understanding of the data analysis process in Python.

 

Whether you’re an experienced professional looking to upskill or a beginner stepping into the world of data analysis, this course is designed to equip you with the confidence and expertise to excel. Join us on this exciting journey and unlock your potential as a Python-powered data analyst!

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What Will You Learn?

  • You will become skilled in Python for thorough data analysis and prepare for a career as a data analyst by gaining practical skills and experience.
  • You will learn the basics of data analytics, including important concepts, statistical analysis, hypothesis testing, and machine learning.
  • You will understand key Python programming fundamentals such as naming variables, data types, lists, dictionaries, dataframes, sets, loops, and functions.
  • You will become proficient in techniques for cleaning, sorting, filtering, manipulating, transforming, and preparing data in Python.
  • You will use Python to create data visualizations, explore data, perform statistical analysis, test hypotheses, and build machine learning models.
  • You will work on real data analysis projects to apply what you’ve learned and improve your problem-solving skills with hands-on exercises.
  • Throughout the course, you will complete practical assignments, over 85 coding exercises, and 10 quizzes with 100+ questions on all topics.
  • At the end of the course, you will complete a capstone project analyzing sports data to demonstrate your understanding of the entire data analysis process in Python.

Course Content

Course Welcome and Setup

  • Course Overview
  • Python Overview
  • Anaconda Distribution Installation
  • Jupyter Notebook 101
  • Jupyter Notebook – Adding Comments in Cells
  • Course Resources – Important!

Objects, Variables and Data Types

Control Flow and Loops

Functions

Challenge Section – Core Python

Modules, Packages and Libraries

NumPy (Numerical Array Operations)

Challenge Section – NumPy

Pandas (Data Analysis and Manipulation)

Challenge Section – Pandas

Connecting to Data Sources

Matplotlib (Data Vizualization)

Challenge Section – Matplotlib

Seaborn (Statistical Data Visualization)

Challenge Section – Seaborn

Automating Excel Operations

Web Scraping and Data Collection

Automating Data Import/Export

Automating Email Reports

API Integration for Data Automation

Automating Repetitive Tasks

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